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Data Mining Trends and Research Frontiers - Kelompok Bo Cuan Gpp
 
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Video Presentasi Data Mining Trends and Research Frontiers Kelompok Bo Cuan Gpp
Views: 587 Ria Liuswani
Top 10 Global Current Trends in Data Mining 2018
 
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Top 10 Global #Data #Mining trends and predictions 2018 - #Outsourcebigdata provide suggestions for the data mining outsourcing industry, worldwide latest global mining industry overview and mining technology predictions to watch in 2018. To check hottest #dataminingtrends to be aware of in 2018, subscribe our channel at https://goo.gl/znWAEF Follow Us: Facebook - https://www.facebook.com/OutsourceBigData Instagram - https://www.instagram.com/outsourcebigdata/ Twitter - https://twitter.com/OBigdata LinkedIn - https://www.linkedin.com/company/outsource-bigdata/ Google+ - https://plus.google.com/u/0/+Outsourcebigdata Pinterest - https://in.pinterest.com/outsourcebigdata/ YouTube - https://www.youtube.com/user/OutsourceBigData/videos For more detail about data mining future trends contact: https://outsourcebigdata.com outsource data, outsource data entry, outsource data mining
Views: 185 BIG DATA
What is Data Mining?
 
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NJIT School of Management professor Stephan P Kudyba describes what data mining is and how it is being used in the business world.
Views: 356559 YouTube NJIT
Moore Methods - Text and Data Mining (2017 update)
 
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Researchers often have to go through lots of articles and papers to find key information for their own work. This can take quite a long time but what if there was a method that could help? In this video, we give an overview of Text and Data Mining (TDM). TDM is an interesting technique that can help with analysing text and other information quickly, allowing you to get results and get on with your work. Want to take things further? Check out our blog for more learning opportunities and activities: https://23researchthingscam.wordpress.com/2016/11/23/thing-19-text-and-data-mining/
Views: 198 Moore Library
Social media data mining for counter-terrorism | Wassim Zoghlami | TEDxMünster
 
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Using public social media data from twitter and Facebook, actions and announcements of terrorists – in this case ISIS – can be monitored and even be predicted. With his project #DataShield Wassim shares his idea of having a tool to identify oncoming threats and attacks in order to protect people and to induce preventive actions. Wassim Zoghlami is a Tunisian Computer Engineering Senior focussing on Business Intelligence and ERP with a passion for data science, software life cycle and UX. Wassim is also an award winning serial entrepreneur working on startups in healthcare and prevention solutions in both Tunisia and The United States. During the past years Wassim has been working on different projects and campaigns about using data driven technology to help people working to uphold human rights and to promote civic engagement and culture across Tunisia and the MENA region. He is also the co-founder of the Tunisian Center for Civic Engagement, a strong advocate for open access to research, open data and open educational resources and one of the Global Shapers in Tunis. At TEDxMünster Wassim will talk about public social media data mining for counter-terrorism and his project idea DataShield. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at http://ted.com/tedx
Views: 1674 TEDx Talks
TCT SAS Data Mining and Risk Management Technology and Job Market Trends(04).mp4
 
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Mr. Yin Cui is a Manager in Basel Analytic, Risk Management in Scotiabank. He worked as a Portfolio Risk Specialist in CIBC's risk management group before he joined Scotia Bank. Mr. Yin Cui has excellent understanding of retail lending risk management and strong expertise in SAS. He holds a Master Degree in Statistics and has been certified by SAS Institution in various trainings.
Views: 93 TorontoCollegeTCT
Introduction to Data Mining for Educational Researchers
 
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Recording of a tutorial held at the second annual Learning Analytics Summer Institute on Data Mining aimed at Educational Researchers.
Views: 1007 Christopher Brooks
Webinar: How analyzing data patterns can improve IT service delivery
 
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Watch this webinar to know how to use Analytics Plus to- 1. Identify data patterns using visual analysis to spot trends easily. 2. Correlate data from multiple sources and get unified visibility into your IT. 3. Create live dashboards to make continuous improvements in ITSM processes.
Views: 409 ManageEngine
Hidden connections - Data analysis in brain and supermarket
 
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Neuroscientist Sonja Grün uses methods from retailing market research to understand how neurons cooperate.The statistical method known as "frequent itemset mining" (FIM) finds groups of objects in large volumes of data quickly and efficiently and counts their frequencies. In retailing market research, this is used, for example, to identify products that are often purchased together. In brain research, a modified version of the FIM method helps to distinguish behaviour-dependent activity patterns from random patterns. This enabled Jülich scientists to establish which of the simultaneously active neurons form a functional group, for instance while the eye focuses on a given object. (mb) A film by Johannes Faber and Gunnar Grah
TCT SAS Data Mining and Risk Management Technology and Job Market Trends(07).mp4
 
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Mr. Yin Cui is a Manager in Basel Analytic, Risk Management in Scotiabank. He worked as a Portfolio Risk Specialist in CIBC's risk management group before he joined Scotia Bank. Mr. Yin Cui has excellent understanding of retail lending risk management and strong expertise in SAS. He holds a Master Degree in Statistics and has been certified by SAS Institution in various trainings.
Views: 158 TorontoCollegeTCT
Healthcare Data Mining with Matrix Models (Part 1)
 
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Authors: Joel Dudley, Icahn School of Medicine at Mount Sinai Ping Zhang, IBM Thomas J. Watson Research Center Fei Wang, Department of Healthcare Policy and Research, Cornell University Abstract: In the last decade, advances in high-throughput technologies, growth of clinical data warehouses, and rapid accumulation of biomedical knowledge provided unprecedented opportunities and challenges to researchers in biomedical informatics. One distinct solution, to efficiently conduct big data analytics for biomedical problems, is the application of matrix computation and factorization methods such as non-negative matrix factorization, joint matrix factorization, tensor factorization. Compared to probabilistic and information theoretic approaches, matrix-based methods are fast, easy to understand and implement. In this tutorial, we provide a review of recent advances in algorithms and methods using matrix and their potential applications in biomedical informatics. We survey various related articles from data mining venues as well as from biomedical informatics venues to share with the audience key problems and trends in matrix computation research, with different novel applications such as drug repositioning, personalized medicine, and electronic phenotyping. More on http://www.kdd.org/kdd2016/ KDD2016 Conference is published on http://videolectures.net/
Views: 587 KDD2016 video
Data trends in 2018: 7 things you need to know
 
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We’re on the verge of a data boom—are you taking full advantage of the data you’re collecting? See all trends that will impact your data strategy in 2018: https://www.pluralsight.com/blog/data-professional/data-trends-2018 Visit us at: Facebook: https://www.facebook.com/pluralsight Twitter: https://twitter.com/pluralsight LinkedIn: https://www.linkedin.com/company/pluralsight Instagram: http://instagram.com/pluralsight Blog: https://www.pluralsight.com/thehub
Views: 943 Pluralsight
More data management by the buy-side
 
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Marion Leslie, Managing Director, Enterprise, Thomson Reuters, talks about the current buy-side trends from an enterprise data perspective, how customers describe their needs given these market trends, and what customers can do to adapt and evolve in order to drive future success. For all your fintech-related news, please visit https://www.finextra.com.
Views: 26 Finextra Research
International Journal of Data Mining & Knowledge Management Process
 
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International Journal of Data Mining & Knowledge Management Process (IJDKP) ISSN : 2230 - 9608 [Online] ; 2231 - 007X [Print] http://airccse.org/journal/ijdkp/ijdkp.html Call for papers :- Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. There is an urgent need for a new generation of computational theories and tools to assist researchers in extracting useful information from the rapidly growing volumes of digital data. This Journal provides a forum for researchers who address this issue and to present their work in a peer-reviewed open access forum. Authors are solicited to contribute to the Journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to these topics only. Topics of interest include, but are not limited to, the following: Data mining foundations Parallel and distributed data mining algorithms, Data streams mining, Graph mining, spatial data mining, Text video, multimedia data mining, Web mining,Pre-processing techniques, Visualization, Security and information hiding in data mining Data mining Applications Databases, Bioinformatics, Biometrics, Image analysis, Financial modeling, Forecasting, Classification, Clustering, Social Networks, Educational data mining. Knowledge Processing Data and knowledge representation, Knowledge discovery framework and process, including pre- and post-processing, Integration of data warehousing, OLAP and data mining, Integrating constraints and knowledge in the KDD process , Exploring data analysis, inference of causes, prediction, Evaluating, consolidating, and explaining discovered knowledge, Statistical techniques for generation a robust, consistent data model, Interactive data exploration/visualization and discovery, Languages and interfaces for data mining, Mining Trends, Opportunities and Risks, Mining from low-quality information sources. Paper Submission Authors are invited to submit papers for this journal through E-mail: [email protected] or [email protected] Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. For other details please visit : http://airccse.org/journal/ijdkp/ijdkp.html
Views: 144 aircc journal
International Journal of Data Mining & Knowledge Management Process ( IJDKP )
 
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International Journal of Data Mining & Knowledge Management Process ( IJDKP ) http://airccse.org/journal/ijdkp/ijdkp.html ISSN : 2230 - 9608[Online] ; 2231 - 007X [Print] Call for Papers Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. There is an urgent need for a new generation of computational theories and tools to assist researchers in extracting useful information from the rapidly growing volumes of digital data. This Journal provides a forum for researchers who address this issue and to present their work in a peer-reviewed open access forum.Authors are solicited to contribute to the workshop by submitting articles that illustrate research results, projects,surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to these topics only. Data mining foundations Parallel and distributed data mining algorithms, Data streams mining, Graph mining, spatial data mining, Text video, multimedia data mining,Web mining,Pre-processing techniques, Visualization, Security and information hiding in data mining. Data mining Applications Databases, Bioinformatics, Biometrics, Image analysis, Financial modeling, Forecasting, Classification, Clustering, Social Networks,Educational data mining. Knowledge Processing Data and knowledge representation, Knowledge discovery framework and process, including pre- and post-processing, Integration of data warehousing,OLAP and data mining, Integrating constraints and knowledge in the KDD process , Exploring data analysis, inference of causes, prediction, Evaluating, consolidating, and explaining discovered knowledge, Statistical techniques for generation a robust, consistent data model, Interactive data exploration/visualization and discovery, Languages and interfaces for data mining, Mining Trends, Opportunities and Risks, Mining from low-quality information sources. Paper submission Authors are invited to submit papers for this journal through e-mail: [email protected]. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. For other details please visit : http://airccse.org/journal/ijdkp/ijdkp.html
Views: 47 aircc journal
Data Mining Marketing Research ChannelAide
 
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http://www.channelaide.com/ marketing research done for your online selling
Views: 194 Mike Gerts
Document Management Trends
 
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Dan Wajzner explains in this video how businesses rely on information, from simple records to the use of data mining tools, into which document management (DM) introduces efficiencies in any industry sector. DM today comprises logically grouped data as well as historical paper documents, which means DM is often essential infrastructure, rather than a standalone application, that is capable of providing a BI dashboard of opportunities and threats.
Views: 221 Document Logistix
International Journal of Data Mining & Knowledge Management Process (IJDKP)
 
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International Journal of Data Mining & Knowledge Management Process ( IJDKP ) http://airccse.org/journal/ijdkp/ijdkp.html ISSN : 2230 - 9608[Online] ; 2231 - 007X [Print] Call for Papers Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. There is an urgent need for a new generation of computational theories and tools to assist researchers in extracting useful information from the rapidly growing volumes of digital data. This Journal provides a forum for researchers who address this issue and to present their work in a peer-reviewed open access forum. Authors are solicited to contribute to the workshop by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to these topics only. Data Mining Foundations Parallel and Distributed Data Mining Algorithms, Data Streams Mining, Graph Mining, Spatial Data Mining, Text video, Multimedia Data Mining, Web Mining,Pre-Processing Techniques, Visualization, Security and Information Hiding in Data Mining Data Mining Applications Databases, Bioinformatics, Biometrics, Image Analysis, Financial Mmodeling, Forecasting, Classification, Clustering, Social Networks, Educational Data Mining Knowledge Processing Data and Knowledge Representation, Knowledge Discovery Framework and Process, Including Pre- and Post-Processing, Integration of Data Warehousing, OLAP and Data Mining, Integrating Constraints and Knowledge in the KDD Process , Exploring Data Analysis, Inference of Causes, Prediction, Evaluating, Consolidating and Explaining Discovered Knowledge, Statistical Techniques for Generation a Robust, Consistent Data Model, Interactive Data Exploration Visualization and Discovery, Languages and Interfaces for Data Mining, Mining Trends, Opportunities and Risks, Mining from Low-Quality Information Sources Paper submission Authors are invited to submit papers for this journal through e-mail [email protected] . Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal.
Views: 159 ijdkp jou
The most important skills of data scientists | Jose Miguel Cansado | TEDxIEMadrid
 
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How big data starts to drive the world, and what kind of skills will you need to interpret it? General Director of Alto Data Analytics, Jose Miguel Cansado, has developed his international career in IMB Watson and Alcatel-Lucent, including eight years in pacific Asia as Head of Multimedia and Mobile Communications. He is a telecommunication engineer and holds a master’s in marketing from INSEAD, as well as executive MBA from IE Business School. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx
Views: 85785 TEDx Talks
International Journal of Data Mining & Knowledge Management Process ( IJDKP )
 
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International Journal of Data Mining & Knowledge Management Process ( IJDKP ) http://airccse.org/journal/ijdkp/ijdkp.html ISSN : 2230 - 9608[Online] ; 2231 - 007X [Print] **************************************************************************************** Call for Papers ============== Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. There is an urgent need for a new generation of computational theories and tools to assist researchers in extracting useful information from the rapidly growing volumes of digital data. This Journal provides a forum for researchers who address this issue and to present their work in a peer-reviewed open access forum. Authors are solicited to contribute to the workshop by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to these topics only. Data Mining Foundations ======================= Parallel and Distributed Data Mining Algorithms, Data Streams Mining, Graph Mining, Spatial Data Mining, Text video, Multimedia Data Mining, Web Mining,Pre-Processing Techniques, Visualization, Security and Information Hiding in Data Mining Data Mining Applications ======================== Databases, Bioinformatics, Biometrics, Image Analysis, Financial Mmodeling, Forecasting, Classification, Clustering, Social Networks, Educational Data Mining Knowledge Processing ==================== Data and Knowledge Representation, Knowledge Discovery Framework and Process, Including Pre- and Post-Processing, Integration of Data Warehousing, OLAP and Data Mining, Integrating Constraints and Knowledge in the KDD Process , Exploring Data Analysis, Inference of Causes, Prediction, Evaluating, Consolidating and Explaining Discovered Knowledge, Statistical Techniques for Generation a Robust, Consistent Data Model, Interactive Data Exploration/ Visualization and Discovery, Languages and Interfaces for Data Mining, Mining Trends, Opportunities and Risks, Mining from Low-Quality Information Sources Paper submission **************** Authors are invited to submit papers for this journal through e-mail [email protected] Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal.
Views: 3 aircc journal
Big Data (Introduction for Business Students)
 
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This short revision video introduces the concept of big data. Big data is the process of collecting and analysing large data sets from traditional and digital sources to identify trends and patterns that can be used in decision-making. These large data sets are both structured (e.g. sales transactions from an online store) and unstructured (e.g. posts) on social media. The quantity of data generated is growing exponentially, including data generated by: Retail e-commerce databases User-interactions with websites and mobile apps Usage of logistics, transportation systems, financial and health care Social media data Location data (e.g. GPS-generated) Internet of Things (IoT) data generated New forms of scientific data (e.g. human genome analysis) Some important uses of big data include: Tracking and monitoring the performance, safety and reliability of operational equipment (e.g. data generated by sensors) Generating marketing insights into the needs and wants of customers, based on the transactions, feedback, comments (e.g. from e-commerce analytics, social media posts). Big data is revolutionising traditional market research. Improved decision-making - for example analysing the real-time impact of pricing changes or other elements of the marketing mix (the use of big data to drive dynamic pricing is a great example of this). Better security of business systems: big data can be analysed to identify unusual activity, for example on secure-access systems More efficient management of capacity: the increasing use of big data to inform decision-making about capacity management (e.g, in transportation and logistics systems) is a great example of how big data can help a business operate more efficiently
Views: 1699 tutor2u
Trends in Data Management
 
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Interview with Mike Dye
International Journal of Data Mining & Knowledge Management Process ( IJDKP )
 
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International Journal of Data Mining & Knowledge Management Process ( IJDKP ) http://airccse.org/journal/ijdkp/ijdkp.html ISSN : 2230 - 9608[Online] ; 2231 - 007X [Print] ******************************************************************* Call for Papers ============== Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. There is an urgent need for a new generation of computational theories and tools to assist researchers in extracting useful information from the rapidly growing volumes of digital data. This Journal provides a forum for researchers who address this issue and to present their work in a peer-reviewed open access forum. Authors are solicited to contribute to the workshop by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to these topics only. Data Mining Foundations ======================= Parallel and Distributed Data Mining Algorithms, Data Streams Mining, Graph Mining, Spatial Data Mining, Text video, Multimedia Data Mining, Web Mining,Pre-Processing Techniques, Visualization, Security and Information Hiding in Data Mining Data Mining Applications ======================== Databases, Bioinformatics, Biometrics, Image Analysis, Financial Mmodeling, Forecasting, Classification, Clustering, Social Networks, Educational Data Mining Knowledge Processing ==================== Data and Knowledge Representation, Knowledge Discovery Framework and Process, Including Pre- and Post-Processing, Integration of Data Warehousing, OLAP and Data Mining, Integrating Constraints and Knowledge in the KDD Process , Exploring Data Analysis, Inference of Causes, Prediction, Evaluating, Consolidating and Explaining Discovered Knowledge, Statistical Techniques for Generation a Robust, Consistent Data Model, Interactive Data Exploration/ Visualization and Discovery, Languages and Interfaces for Data Mining, Mining Trends, Opportunities and Risks, Mining from Low-Quality Information Sources Paper submission **************** Authors are invited to submit papers for this journal through e-mail [email protected] Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. For other details please visit http://airccse.org/journal/ijdkp/ijdkp.html
Views: 43 aircc journal
International Journal of Data Mining & Knowledge Management Process ( IJDKP )
 
00:10
Call for Papers Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. There is an urgent need for a new generation of computational theories and tools to assist researchers in extracting useful information from the rapidly growing volumes of digital data. This Journal provides a forum for researchers who address this issue and to present their work in a peer-reviewed open access forum. Authors are solicited to contribute to the workshop by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to these topics only. Data Mining Foundations Parallel and Distributed Data Mining Algorithms, Data Streams Mining, Graph Mining, Spatial Data Mining, Text video, Multimedia Data Mining, Web Mining,Pre-Processing Techniques, Visualization, Security and Information Hiding in Data Mining Data Mining Applications Databases, Bioinformatics, Biometrics, Image Analysis, Financial Mmodeling, Forecasting, Classification, Clustering, Social Networks, Educational Data Mining Knowledge Processing Data and Knowledge Representation, Knowledge Discovery Framework and Process, Including Pre- and Post-Processing, Integration of Data Warehousing, OLAP and Data Mining, Integrating Constraints and Knowledge in the KDD Process , Exploring Data Analysis, Inference of Causes, Prediction, Evaluating, Consolidating and Explaining Discovered Knowledge, Statistical Techniques for Generation a Robust, Consistent Data Model, Interactive Data Exploration/ Visualization and Discovery, Languages and Interfaces for Data Mining, Mining Trends, Opportunities and Risks, Mining from Low-Quality Information Sources Paper submission Authors are invited to submit papers for this journal through e-mail [email protected] Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal.
Views: 17 aircc journal
International Journal of Data Mining & Knowledge Management Process ( IJDKP )
 
00:10
http://airccse.org/journal/ijdkp/ijdkp.html ISSN : 2230 - 9608[Online] ; 2231 - 007X [Print] **************************************************************************************** Call for Papers ============== Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. There is an urgent need for a new generation of computational theories and tools to assist researchers in extracting useful information from the rapidly growing volumes of digital data. This Journal provides a forum for researchers who address this issue and to present their work in a peer-reviewed open access forum. Authors are solicited to contribute to the workshop by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to these topics only. Data Mining Foundations ======================= Parallel and Distributed Data Mining Algorithms, Data Streams Mining, Graph Mining, Spatial Data Mining, Text video, Multimedia Data Mining, Web Mining,Pre-Processing Techniques, Visualization, Security and Information Hiding in Data Mining Data Mining Applications ======================== Databases, Bioinformatics, Biometrics, Image Analysis, Financial Mmodeling, Forecasting, Classification, Clustering, Social Networks, Educational Data Mining Knowledge Processing ==================== Data and Knowledge Representation, Knowledge Discovery Framework and Process, Including Pre- and Post-Processing, Integration of Data Warehousing, OLAP and Data Mining, Integrating Constraints and Knowledge in the KDD Process , Exploring Data Analysis, Inference of Causes, Prediction, Evaluating, Consolidating and Explaining Discovered Knowledge, Statistical Techniques for Generation a Robust, Consistent Data Model, Interactive Data Exploration/ Visualization and Discovery, Languages and Interfaces for Data Mining, Mining Trends, Opportunities and Risks, Mining from Low-Quality Information Sources Paper submission **************** Authors are invited to submit papers for this journal through e-mail [email protected] Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. Important Dates **************** Submission Deadline : June 09, 2018 Notification : July 09, 2018 Final Manuscript Due : July 16, 2018 Publication Date : Determined by the Editor-in-Chief For other details please visit http://airccse.org/journal/ijdkp/ijdkp.html
Views: 3 aircc journal
Big Data & Analytics for Healthcare
 
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http://ibm.co/healthcareanalytics Healthcare organizations are leveraging the IBM Big Data & Analytics platform to capture all of the information about a patient to get a more complete view for insight into care coordination and outcomes-based reimbursement models, population health management, and patient engagement and outreach. Successfully harnessing big data unleashes the potential to achieve the three critical objectives for healthcare transformation: Build sustainable healthcare systems Collaborate to improve care and outcomes Increase access to healthcare
Views: 54936 IBM Analytics
Webinar: The Process Revolution - How Data and Science Are Fueling Next Generation BPM
 
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Michal Rosik and Richard Lipovsky of Minit.io share their knowledge and experience with process mining projects. Watch the webinar to learn: - Why Process Mining is on the rise according to Gartner - Which industries are leading process mining adoption and other trends - Case studies demonstrating real results from implementing process mining - Demo of the comprehensive process analysis capabilities of Minit platform Learn more about Minit platform at www.minit.io
International Journal of Data Mining & Knowledge Management Process ( IJDKP )
 
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Call for Papers Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. There is an urgent need for a new generation of computational theories and tools to assist researchers in extracting useful information from the rapidly growing volumes of digital data. This Journal provides a forum for researchers who address this issue and to present their work in a peer-reviewed open access forum. Authors are solicited to contribute to the workshop by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to these topics only. Data Mining Foundations Parallel and Distributed Data Mining Algorithms, Data Streams Mining, Graph Mining, Spatial Data Mining, Text video, Multimedia Data Mining, Web Mining,Pre-Processing Techniques, Visualization, Security and Information Hiding in Data Mining Data Mining Applications Databases, Bioinformatics, Biometrics, Image Analysis, Financial Mmodeling, Forecasting, Classification, Clustering, Social Networks, Educational Data Mining Knowledge Processing Data and Knowledge Representation, Knowledge Discovery Framework and Process, Including Pre- and Post-Processing, Integration of Data Warehousing, OLAP and Data Mining, Integrating Constraints and Knowledge in the KDD Process , Exploring Data Analysis, Inference of Causes, Prediction, Evaluating, Consolidating and Explaining Discovered Knowledge, Statistical Techniques for Generation a Robust, Consistent Data Model, Interactive Data Exploration/ Visualization and Discovery, Languages and Interfaces for Data Mining, Mining Trends, Opportunities and Risks, Mining from Low-Quality Information Sources Paper submission Authors are invited to submit papers for this journal through e-mail [email protected] Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal.
Views: 20 aircc journal
International Journal of Data Mining & Knowledge Management Process ( IJDKP )
 
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International Journal of Data Mining & Knowledge Management Process ( IJDKP ) http://airccse.org/journal/ijdkp/ijdkp.html ISSN : 2230 - 9608[Online] ; 2231 - 007X [Print] **************************************************************************************** Call for Papers ============== Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. There is an urgent need for a new generation of computational theories and tools to assist researchers in extracting useful information from the rapidly growing volumes of digital data. This Journal provides a forum for researchers who address this issue and to present their work in a peer-reviewed open access forum. Authors are solicited to contribute to the workshop by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to these topics only. Data Mining Foundations ======================= Parallel and Distributed Data Mining Algorithms, Data Streams Mining, Graph Mining, Spatial Data Mining, Text video, Multimedia Data Mining, Web Mining,Pre-Processing Techniques, Visualization, Security and Information Hiding in Data Mining Data Mining Applications ======================== Databases, Bioinformatics, Biometrics, Image Analysis, Financial Mmodeling, Forecasting, Classification, Clustering, Social Networks, Educational Data Mining Knowledge Processing ==================== Data and Knowledge Representation, Knowledge Discovery Framework and Process, Including Pre- and Post-Processing, Integration of Data Warehousing, OLAP and Data Mining, Integrating Constraints and Knowledge in the KDD Process , Exploring Data Analysis, Inference of Causes, Prediction, Evaluating, Consolidating and Explaining Discovered Knowledge, Statistical Techniques for Generation a Robust, Consistent Data Model, Interactive Data Exploration/ Visualization and Discovery, Languages and Interfaces for Data Mining, Mining Trends, Opportunities and Risks, Mining from Low-Quality Information Sources Paper submission **************** Authors are invited to submit papers for this journal through e-mail [email protected] Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. For other details please visit http://airccse.org/journal/ijdkp/ijdkp.html
Views: 11 aircc journal
International Journal of Data Mining & Knowledge Management Process  IJDKP
 
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International Journal of Data Mining & Knowledge Management Process ( IJDKP ) http://airccse.org/journal/ijdkp/ijdkp.html ISSN : 2230 - 9608[Online] ; 2231 - 007X [Print] Call for Papers Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. There is an urgent need for a new generation of computational theories and tools to assist researchers in extracting useful information from the rapidly growing volumes of digital data. This Journal provides a forum for researchers who address this issue and to present their work in a peer-reviewed open access forum. Authors are solicited to contribute to the workshop by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to these topics only. Data mining foundations Parallel and distributed data mining algorithms, Data streams mining, Graph mining, spatial data mining, Text video, multimedia data mining, Web mining,Pre-processing techniques, Visualization, Security and information hiding in data mining Data mining Applications Databases, Bioinformatics, Biometrics, Image analysis, Financial modeling, Forecasting, Classification, Clustering, Social Networks, Educational data mining Knowledge Processing Data and knowledge representation, Knowledge discovery framework and process, including pre- and post-processing, Integration of data warehousing, OLAP and data mining, Integrating constraints and knowledge in the KDD process , Exploring data analysis, inference of causes, prediction, Evaluating, consolidating, and explaining discovered knowledge, Statistical techniques for generation a robust, consistent data model, Interactive data exploration/ visualization and discovery, Languages and interfaces for data mining, Mining Trends, Opportunities and Risks, Mining from low-quality information sources Paper submission Authors are invited to submit papers for this journal through e-mail [email protected] Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal.
New Research Trends in the Field of Data Analytics and Internet of Things (IoT) - Part 01
 
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Informative Speech by Mr. Sandar Ali Khowaja on New Research Trends in the Field of Data Analytics and Internet of Things (IoT) and Its Applications in Healthcare Industry
Views: 28 K D
International Journal of Data Mining & Knowledge Management Process ( IJDKP )
 
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International Journal of Data Mining & Knowledge Management Process ( IJDKP ) http://airccse.org/journal/ijdkp/ijdkp.html ISSN : 2230 - 9608[Online] ; 2231 - 007X [Print] Call for Papers Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. There is an urgent need for a new generation of computational theories and tools to assist researchers in extracting useful information from the rapidly growing volumes of digital data. This Journal provides a forum for researchers who address this issue and to present their work in a peer-reviewed open access forum.Authors are solicited to contribute to the workshop by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to these topics only. Data mining foundations Parallel and distributed data mining algorithms, Data streams mining, Graph mining, spatial data mining, Text video, multimedia data mining, Web mining,Pre-processing techniques, Visualization, Security and information hiding in data mining Data mining Applications Databases, Bioinformatics, Biometrics, Image analysis, Financial modeling, Forecasting, Classification, Clustering, Social Networks, Educational data mining Knowledge Processing Data and knowledge representation, Knowledge discovery framework and process, including pre- and post-processing, Integration of data warehousing, OLAP and data mining, Integrating constraints and knowledge in the KDD process , Exploring data analysis, inference of causes, prediction, Evaluating, consolidating, and explaining discovered knowledge, Statistical techniques for generation a robust, consistent data model, Interactive data exploration/ visualization and discovery, Languages and interfaces for data mining, Mining Trends, Opportunities and Risks, Mining from low-quality information sources Paper submission Authors are invited to submit papers for this journal through e-mail [email protected] Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. For other details please visit http://airccse.org/journal/ijdkp/ijdkp.html
Views: 18 aircc journal
International Journal of Data Mining & Knowledge Management Process (IJDKP)
 
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International Journal of Data Mining & Knowledge Management Process (IJDKP) ISSN : 2230 - 9608 [Online] ; 2231 - 007X [Print] http://airccse.org/journal/ijdkp/ijdkp.html Call for papers :- Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. There is an urgent need for a new generation of computational theories and tools to assist researchers in extracting useful information from the rapidly growing volumes of digital data. This Journal provides a forum for researchers who address this issue and to present their work in a peer-reviewed open access forum. Authors are solicited to contribute to the Journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to these topics only. Topics of interest include, but are not limited to, the following: Data mining foundations Parallel and distributed data mining algorithms, Data streams mining, Graph mining, spatial data mining, Text video, multimedia data mining, Web mining,Pre-processing techniques, Visualization, Security and information hiding in data mining Data mining Applications Databases, Bioinformatics, Biometrics, Image analysis, Financial modeling, Forecasting, Classification, Clustering, Social Networks, Educational data mining. Knowledge Processing Data and knowledge representation, Knowledge discovery framework and process, including pre- and post-processing, Integration of data warehousing, OLAP and data mining, Integrating constraints and knowledge in the KDD process , Exploring data analysis, inference of causes, prediction, Evaluating, consolidating, and explaining discovered knowledge, Statistical techniques for generation a robust, consistent data model, Interactive data exploration/visualization and discovery, Languages and interfaces for data mining, Mining Trends, Opportunities and Risks, Mining from low-quality information sources. Paper Submission Authors are invited to submit papers for this journal through E-mail: [email protected] or [email protected] Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. For other details please visit : http://airccse.org/journal/ijdkp/ijdkp.html
Views: 90 Sivakumar Arumugam
International Journal of Data Mining & Knowledge Management Process ( IJDKP )
 
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International Journal of Data Mining & Knowledge Management Process ( IJDKP ) http://airccse.org/journal/ijdkp/ijdkp.html ISSN : 2230 - 9608[Online] ; 2231 - 007X [Print] **************************************************************************************** Call for Papers ============== Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. There is an urgent need for a new generation of computational theories and tools to assist researchers in extracting useful information from the rapidly growing volumes of digital data. This Journal provides a forum for researchers who address this issue and to present their work in a peer-reviewed open access forum. Authors are solicited to contribute to the workshop by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to these topics only. Data Mining Foundations ======================= Parallel and Distributed Data Mining Algorithms, Data Streams Mining, Graph Mining, Spatial Data Mining, Text video, Multimedia Data Mining, Web Mining,Pre-Processing Techniques, Visualization, Security and Information Hiding in Data Mining Data Mining Applications ======================== Databases, Bioinformatics, Biometrics, Image Analysis, Financial Mmodeling, Forecasting, Classification, Clustering, Social Networks, Educational Data Mining Knowledge Processing ==================== Data and Knowledge Representation, Knowledge Discovery Framework and Process, Including Pre- and Post-Processing, Integration of Data Warehousing, OLAP and Data Mining, Integrating Constraints and Knowledge in the KDD Process , Exploring Data Analysis, Inference of Causes, Prediction, Evaluating, Consolidating and Explaining Discovered Knowledge, Statistical Techniques for Generation a Robust, Consistent Data Model, Interactive Data Exploration/ Visualization and Discovery, Languages and Interfaces for Data Mining, Mining Trends, Opportunities and Risks, Mining from Low-Quality Information Sources Paper submission **************** Authors are invited to submit papers for this journal through e-mail [email protected] Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. Important Dates **************** Submission Deadline : August 05, 2017 Notification : September 05, 2017 Final Manuscript Due : September 13, 2017 Publication Date : Determined by the Editor-in-Chief For other details please visit http://airccse.org/journal/ijdkp/ijdkp.html
Views: 31 aircc journal
Welche Trends bestimmen 2018 den digitalen Handel? | dotSource Research
 
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Big und smart Data, Hearables, Wearables, Content Commerce und Data Mining - die Buzzword-Schlacht im digitalen Handel geht auch 2018 in eine neue Runde. Handelskraft Digital-Evangelist Oliver Kling erklärt dir in diesem Video, welche Trends 2018 den digitalen Handel bestimmen werden. Trends, Zahlen, Fakten und Brancheninsights gibt es exklusiv für Händler und Hersteller in unserem Digital-Business Kompass Handelskraft 2018 »Vorwärts zur digitalen Exzellenz«. Das Trendbuch kann hier zum kostenlosen Download angefordert werden: http://bit.ly/2CP7aT7 Für aktuelle Trends, Expertenwissen und Klartext statt überstrapazierter Buzzworte sicher dir jetzt dein Ticket für die Handelskraft 2019 am 28. März in der Klassikstadt in Frankfurt am Main: https://bit.ly/2N06c89 Musik: ajstream - AJStream Opening #2 https://soundcloud.com/ajstream/the-stream-opening
Views: 774 dotSource GmbH
Analyze Stock Data with Microsoft Excel
 
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Visualization of data is a powerful method to see trends and make decisions. Microsoft Excel trending capabilities are tools to visualize large data sets, such as financial information on company performance.
Views: 10910 APMonitor.com
Introduction to Regression Analysis
 
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This video introduced analysis and discusses how to determine if a given regression equation is a good model using r and r^2.
Views: 171314 Mathispower4u
International Journal of Data Mining & Knowledge Management Process ( IJDKP )
 
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International Journal of Data Mining & Knowledge Management Process ( IJDKP ) http://airccse.org/journal/ijdkp/ijdkp.html ISSN : 2230 - 9608[Online] ; 2231 - 007X [Print] Call for Papers Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. There is an urgent need for a new generation of computational theories and tools to assist researchers in extracting useful information from the rapidly growing volumes of digital data. This Journal provides a forum for researchers who address this issue and to present their work in a peer-reviewed open access forum. Authors are solicited to contribute to the workshop by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to these topics only. Data Mining Foundations Parallel and Distributed Data Mining Algorithms, Data Streams Mining, Graph Mining, Spatial Data Mining, Text video, Multimedia Data Mining, Web Mining,Pre-Processing Techniques, Visualization, Security and Information Hiding in Data Mining Data Mining Applications Databases, Bioinformatics, Biometrics, Image Analysis, Financial Mmodeling, Forecasting, Classification, Clustering, Social Networks, ducational Data Mining Knowledge Processing Data and Knowledge Representation, Knowledge Discovery Framework and Process, Including Pre- and Post-Processing, Integration of Data Warehousing, OLAP and Data Mining, Integrating Constraints and Knowledge in the KDD Process , Exploring Data Analysis, Inference of Causes, Prediction, Evaluating, Consolidating and Explaining Discovered Knowledge, Statistical Techniques for Generation a Robust, Consistent Data Model, Interactive Data Exploration Visualization and Discovery, Languages and Interfaces for Data Mining, Mining Trends, Opportunities and Risks, Mining from Low-Quality Information Sources Paper submission Authors are invited to submit papers for this journal through e-mail [email protected] . Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. For other details please visit http://airccse.org/journal/ijdkp/ijdkp.html
Views: 21 aircc journal
International Journal of Data Mining & Knowledge Management Process ( IJDKP )
 
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International Journal of Data Mining & Knowledge Management Process ( IJDKP ) http://airccse.org/journal/ijdkp/ijdkp.html ISSN : 2230 - 9608[Online] ; 2231 - 007X [Print] Call for Papers Data mining and knowledge discovery in databases have been attracting a significant amount of research, industry, and media attention of late. There is an urgent need for a new generation of computational theories and tools to assist researchers in extracting useful information from the rapidly growing volumes of digital data. This Journal provides a forum for researchers who address this issue and to present their work in a peer-reviewed open access forum. Authors are solicited to contribute to the workshop by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to these topics only. Data Mining Foundations Parallel and Distributed Data Mining Algorithms, Data Streams Mining, Graph Mining, Spatial Data Mining, Text video, Multimedia Data Mining, Web Mining,Pre-Processing Techniques, Visualization, Security and Information Hiding in Data Mining Data Mining Applications Databases, Bioinformatics, Biometrics, Image Analysis, Financial Mmodeling, Forecasting, Classification, Clustering, Social Networks, Educational Data Mining Knowledge Processing Data and Knowledge Representation, Knowledge Discovery Framework and Process, Including Pre- and Post-Processing, Integration of Data Warehousing, OLAP and Data Mining, Integrating Constraints and Knowledge in the KDD Process , Exploring Data Analysis, Inference of Causes, Prediction, Evaluating, Consolidating and Explaining Discovered Knowledge, Statistical Techniques for Generation a Robust, Consistent Data Model, Interactive Data Exploration/ Visualization and Discovery, Languages and Interfaces for Data Mining, Mining Trends, Opportunities and Risks, Mining from Low-Quality Information Sources Paper submission Authors are invited to submit papers for this journal through e-mail [email protected] Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal. For other details please visit http://airccse.org/journal/ijdkp/ijdkp.html
Views: 17 Ijaia Journal
Where Big Data and Innovation Management are Headed in 2015
 
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Presented by: Huub Rutten, VP Research and Steven Kleynenberg Senior Software Engineer for Sopheon Huub and Steven delve deeper into the topic of Big Data and Innovation Management. In a previous webinar on September 11th 2014 we discussed Big Data at a high level. Now we are giving you the opportunity to learn specific methods around: • How to find white spaces • Generating trends • Predicting topics • Using Big Data to improve your innovation ROI in 2015 Our goal is for participants to learn some basic methodologies around using Big Data for better and more mature Innovation Management Techniques. Our presenters will illustrate these methods with concrete examples, supported by some nice text and data mining software from the Sopheon Research lab. View the entire webinar at: http://budurl.com/bubr
Views: 140 Sopheon
Time Series: Measurement of Trend in Hindi under E-Learning Program
 
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It covers in detail various methods of measuring trend like Moving Averags & Least Square. Lecture by: Rajinder Kumar Arora, Head of Department of Commerce & Management
MATLAB Tools for Scientists: Introduction to Statistical Analysis
 
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Free MATLAB Trial: https://goo.gl/yXuXnS Request a Quote: https://goo.gl/wNKDSg Contact Us: https://goo.gl/RjJAkE Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe ------------------------------------------------------------------------- Researchers and scientists have to commonly process, visualize and analyze large amounts of data to extract patterns, identify trends and relationships between variables, prove hypothesis, etc. A variety of statistical techniques are used in this data mining and analysis process. Using a realistic data from a clinical study, we will provide an overview of the statistical analysis and visualization capabilities in the MATLAB product family. Highlights include: • Data management and organization • Data filtering and visualization • Descriptive statistics • Hypothesis testing and ANOVA • Regression analysis
Views: 10405 MATLAB
Healthcare Data Mining with Matrix Models (Part 2)
 
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Authors: Joel Dudley, Icahn School of Medicine at Mount Sinai Ping Zhang, IBM Thomas J. Watson Research Center Fei Wang, Department of Healthcare Policy and Research, Cornell University Abstract: In the last decade, advances in high-throughput technologies, growth of clinical data warehouses, and rapid accumulation of biomedical knowledge provided unprecedented opportunities and challenges to researchers in biomedical informatics. One distinct solution, to efficiently conduct big data analytics for biomedical problems, is the application of matrix computation and factorization methods such as non-negative matrix factorization, joint matrix factorization, tensor factorization. Compared to probabilistic and information theoretic approaches, matrix-based methods are fast, easy to understand and implement. In this tutorial, we provide a review of recent advances in algorithms and methods using matrix and their potential applications in biomedical informatics. We survey various related articles from data mining venues as well as from biomedical informatics venues to share with the audience key problems and trends in matrix computation research, with different novel applications such as drug repositioning, personalized medicine, and electronic phenotyping. More on http://www.kdd.org/kdd2016/ KDD2016 Conference is published on http://videolectures.net/
Views: 166 KDD2016 video
Second International Conference on Data Mining & Knowledge Management Process (DKMP 2014)
 
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The Second International Conference on Data Mining & Knowledge Management Process (DKMP 2014) is jointly organized by AIRCC's Computer Science & Information Technology Community (CSITC) and Vel Tech Dr. RR & Dr. SR Technical University, Chennai, India. Second International Conference on Data Mining & Knowledge Management Process (DKMP 2014) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Data Mining and knowledge management process. The goal of this conference is to bring together researchers and practitioners from academia and industry to focus on understanding Modern data mining concepts and establishing new collaborations in these areas. http://airccj.org/2014/dkmp/index.html
Views: 147 IJNGN
Machine Learning with Small Data Sets in the Age of Deep Learning
 
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Dr. Lei Tang and Dr. Xin Xu will talk about how they apply machine learning with small data sets in sales management and forecast. The recent successes of machine learning and deep learning can be largely attributed to three factors: emergence of abundant data, development of innovative algorithms, and availability of machine learning tools and computing resources. Unfortunately, not all application spaces provide data sets large enough to be used in the usual or obvious ways. In this talk, Lei and Xin focus on one specific domain, enterprise sales, where data is often limited in volume, always noisy, and constantly evolving. They describe how machine learning, and in particular deep learning, can help, and how we address the data challenges described. They specifically discuss how to select model architectures appropriate for these limited data situations, for example, how deep our networks should be. By sifting through sales records and associated sales activities Lei and Xin enable identification of at-risk opportunities as well as project and estimated the time required to close each deal. This, in turn, contributes to the generation of a reliable business forecast for sales managers and executives. Lessons and findings learned through the process is shared. Speaker Bios: Dr. Lei Tang is the Chief Data Scientist at Clari Inc., a startup backed by Sequoia Capital and Bain Capital ventures, focusing on predictive analytics for sales execution and forecasting. Lei received his Ph.D. in computer science from Arizona State University in 2010, and B.S. from Fudan University, China. He is passionate about reshaping variety of businesses, driving business growth and decision through data science and machine learning. From 2012-2014, Lei was the lead data scientist at Demand Generation of @WalmartLabs, where he worked closely with marketing team to drive traffic to site, impacting hundreds of revenue each year. Before that, Lei had 2-year stint at advertising sciences in Yahoo! Labs, working on targeting, user profiling/segmentation by mining user behavioral, social and content information. Lei has co-authored one book on “community detection and mining in social media” (top-download in the corresponding data mining lecture series), held 4 patents, published over 30 papers at top-notch conferences and journals on data mining/machine learning, with over 4000 citations. Dr. Xin Xu is currently working as a data scientist in Clari. Before this, She received her Ph.D degree in Computer Engineering from North Carolina State University in 2015. She also did summer intern in Bell Labs and Akamai Technology in 2014 and 2015 respectively. Her current research interest mainly focuses on applying data mining, machine learning and advanced analytics to solve practical problems in sales domain.
Planning Tools: Google Trends
 
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Boost your marketing with this powerful planning tool. For more Google insights and trends visit thinkwithgoogle.co.uk
Views: 18948 Think with Google UK