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DESCRIPTION:Click for Latest Location Information: http://smartdata2017.dataversity.net/sessionPop.cfm?confid=110&proposalid=9452\nMALLET is an open source toolkit for statistical natural language processing (NLP), topic modeling, clustering, and other machine learning (ML) applications over text.  \nTopic modeling is a ML approach to analyze large volumes of unlabeled data and automatically extract latent "topics" from the text.  Such topics can be used to identify document similarity in a deeply contextual way.\nIn this session, we demonstrate how to use the open source tool MALLET for textual ML including topic modeling.  We then go on to demonstrate how we have applied this ML technique to develop an application for fast, deep document similarity matching.
DTSTART:20170201T133000
SUMMARY:Textual Machine Learning for Topic Extraction and Document Similarity Matching
DTEND:20170201T141459
LOCATION: See Description
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