'Text mining' diaporamas de présentation

TEXT ANALYSIS FOR SEMANTIC COMPUTING

1.25k views • 125 slides

Mixture Language Models

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User

User. Warehouse. Data Warehouse. DBMS A. DBMS B. DBMS C. Database. Database. Database. Data warehouse example. User. Data Mining Tools. Warehouse. Data Warehouse Manager. DBMS C. DBMS A. DBMS B. Database. Database. Database.

904 views • 66 slides

Analytics in Strategic Decision Making Brazil Executive Seminar, April 2014

Analytics in Strategic Decision Making Brazil Executive Seminar, April 2014. PRESENTED BY DR. FAIZUL HUQ OHIO UNIVERSITY. AGENDA. Introduction to Business Analytics. Example of Analytical Tool Implementation for Supply Chain Sustainability How to make Analytics work for Strategic Success

688 views • 58 slides

Link Analysis: Current State of the Art

Link Analysis: Current State of the Art. Ronen Feldman Computer Science Department Bar-Ilan University, ISRAEL ronenf@gmail.com. Introduction to Text Mining. Actual information buried inside documents. Extract Information from within the documents. TM != Search.

679 views • 56 slides

Social Network Analysis: Concepts, Applications, Analysis of Social Structures Using Secondary Data

Social Network Analysis: Concepts, Applications, Analysis of Social Structures Using Secondary Data. Liaquat Hossain Sciences of Learning Winter Institute Workshop The University of Hong Kong Hong Kong, 14 January 2014 Email: lhossain@hku.hk. Agenda. Introduction to Social Networks

688 views • 40 slides

Research Team

Automatic Extraction of Mental Illnesses from Domestic Violence Event Narratives: a Text Mining Study. George Karystianis , PhD Research Fellow, Justice Health Research Program, Kirby Institute, University of New South Wales. Research Team.

634 views • 35 slides

Components of an effective anti-fraud & corruption compliance program

Anti-Fraud Trends and Analytics Integrating anti-bribery & corruption analytics into your compliance monitoring program Meeting with Verizon October 19, 2012. Components of an effective anti-fraud & corruption compliance program. Setting the Proper Tone. Proactive. Reactive.

2.58k views • 31 slides

Going beyond Turnitin and Plagiarism Serge Noiret EUI History Information Specialist (Ph.D.)

368 views • 26 slides

Text Mining Chapter 20

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Text Mining Concepts

Text Mining Concepts. 85-90 percent of all corporate data is in some kind of unstructured form (e.g., text) Unstructured corporate data is doubling in size every 18 months Tapping into these information sources is not an option, but a need to stay competitive Answer: text mining

1.04k views • 25 slides

Computational Modeling of Hepatic Lipid and Lipoprotein Metabolism

Computational Modeling of Hepatic Lipid and Lipoprotein Metabolism. NCSB / NBIC Modelers-Bioinformatics Meeting 26-02-2010. Leiden University Medical Center. BioModeling & bioInformatics. Biomedical NMR. Overall aim:

437 views • 21 slides

A DoD DCMO Enterprise Information Web

419 views • 20 slides

Computation + journalism in the public interest

Computation + journalism in the public interest. Sarah Cohen, DeWitt Wallace Center. Public interest reporting defined. Information of importance to the public that powerful institutions would prefer to be kept hidden or secret.

289 views • 19 slides

Presenter : Wei- Hao Huang

Discovering Interesting Usage Patterns in Text Collections: Integrating Text Mining with Visualization. Presenter : Wei- Hao Huang

282 views • 14 slides

Text mining : Finding nuggets in mountains of textual data

Author : Jochen Dijrre , Peter Gerstl , Roland Seiffert Proceedings of the 5th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining , San Diego, California, August 15-18, 1999, 398-401. Presented by Xxxxxx. Text mining : Finding nuggets in mountains of textual data.

247 views • 10 slides

IBM SPSS Modeler

IBM SPSS Modeler. Ercan Kaynakca Data Analyst Analysis Express. Knowledge Discovery. Fayyad, Piatetsky -Shapiro & Smyth, 1996. Why Data Mining?. Goal : Extract knowledge from a data set in a human-understandable structure (Fayyad, Piatetsky -Shapiro & Smyth, 1996 ).

1.41k views • 9 slides

OntoSTUDIO as a Ontology Engineering Environment

OntoSTUDIO as a Ontology Engineering Environment. Presented By Stephen Lynn Department of Computer Science Brigham Young University. Semantic Web Tools. Tasks Ontology Creation Manual Learning Reasoning Text Mining Etc. Practical Data Storage Metadata Storage. State of the Art.

232 views • 6 slides

Improved Cancer Risk Assessment Using Text Mining

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171 views • 1 slides