Linking Named Entities in Tweets with Knowledge Base via User Interest Modeling. KDD’13. Task. The task: is to link the named entity mentions detected from tweets with the corresponding real world entities in the knowledge Application : personalized recommendation , user interest discovery.By ianna
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Mentions d’honneur 2010. L’AQPC rend hommage aux enseignantes et aux enseignants qui se sont distingu és par la qualité de leur travail ainsi que par leur contribution à l’ évo lution de l’enseignement au coll égial . Leur engagement p éda gogique a été remarqué par leurs pairs et
Mentions d’honneur 2008. L’AQPC rend hommage aux enseignantes et aux enseignants qui se sont distingués par la qualité de leur travail et par leur contribution à l’évolution de l’enseignement. Cégep de l’Abitibi-Témiscamingue. Équipe. Miguel CHARLEBOIS Isabelle LAUZON Martin BARON
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Mutation Grounding Algorithm Jonas B. Laurila 1 , Rajaraman Kanagasabai 2 and Christopher J. O. Baker 1 1 University of New Brunswick, Saint John. 2 Institute for Infocomm Research, Singapore. April 13th, 2010. Motivation
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The Quran mentions some food items. Taken from various sources on the Internet Slideshow by Dr. Hashim. Discussed in this slideshow:. Honey Milk Figs Olives Bananas Pomegranate Dates Grapes Herbs Cucumbers Garlic Lentils Onions Fruits. العسل Honey سورة محمد - سورة 47 - آية 15.
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Joint Modeling of Entity-Entity Links and Entity-Annotated Text. Ramnath Balasubramanyan, William W. Cohen Language Technologies Institute and Machine Learning Department, School of Computer Science, Carnegie Mellon University,. Motivation: Toward Re-usable “Topic Models”.