'Text mining' presentation slideshows

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.

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.

Text Mining Chapter 20. Text data . Structured data Unstructured data Text Video Audio. Applications of Text Mining – HR Forms. Employment applications Match with job requirements Processing of applications. Applications, cont. Medical triage/diagnosis

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.

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

Mixture Language Models. ChengXiang Zhai Department of Computer Science University of Illinois, Urbana-Champaign. Central Questions to Ask about a LM: “ADMI”. Application : Why do you need a LM? For what purpose? Data: What kind of data do you want to model?

Going beyond Turnitin and Plagiarism Serge Noiret EUI History Information Specialist (Ph.D.) Introduction to Good Academic Practice and the Avoidance of Plagiarism organized by Prof. Lucy Riall, Prof. Stéphane Van Damme and Dr. Serge Noiret Tuesday 8 October 2013, 13:10-15:00

CARTIC RAMAKRISHNAN MEENAKSHI NAGARAJAN AMIT SHETH. TEXT ANALYSIS FOR SEMANTIC COMPUTING. Preparing for a Tutorial. A Great way to find out…. How little you really know. Acknowledgements.

A DoD DCMO Enterprise Information Web. Dr. Brand Niemann Director and Senior Enterprise Architect – Data Scientist Semantic Community http://semanticommunity.info/ AOL Government Blogger http://gov.aol.com/bloggers/brand-niemann/ February 6, 2012

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

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

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.

Literature Database (e.g. MEDLINE). Journal articles for cancer risk assessment. Cancer risk assessment taxonomy. Annotation of cancer risk assessment corpus. Text Mining technology. Identify chemicals’ ”modes of action”. Text mining tool.

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:

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 ).

PAnG – Finding Patterns in Annotation Graphs. Philip Anderson, Andreas Thor, Joseph Benik , Louiqa Raschid, Maria Esther Vidal. Motivation. Approach. Abundance of data High-throughput lab experiments in systems biology. Annotated datasets adorned with CV terms from ontologies .

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.

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.

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

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.