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Named Entity Disambiguation: A Hybrid Statistical and Rule-based Incremental Approach

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• published: 02 Jun 2016
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Don't hesitate to comment below if you have any questions or additional phrases BK TP.HCM Named Entity Disambiguation: A Hybrid Statistical and Rule-based Incremental Approach Hien Nguyen*(Ton Duc Thang University, Vietnam) Tru Cao (Ho Chi Minh City University of Technology, Vietnam) Semantic Web Group (VN-KIM) Faculty of Computer Science & Engineering Ho Chi Minh City University of Technology *Email: hien@tut.edu.vn ,Outline Introduction Wikipedia Algorithm Experimental results Concluding remarks ,Introduction: Named Entities Named Entities (NE) are considered: people, organizations, locations, date, time, money, measures, percentage, etc. Example “Ms. Washington's candidacy is being championed by several powerful lawmakers including her boss, Chairman John Dingell (D., Mich.) of the House Energy and Commerce Committee.” ,Introduction: Problem Different NEs may have the same name. “John McCarthy has been a staple of the Ultimate Fighting Championship since its second event on March 11, 1994.” John McCarthy John McCarthy(referee) “John McCarthy, professor of computer science at Stanford University, who developed LISP.” John McCarthy John McCarthy(computer scientist) “John McCarthy, Britain's longest-held hostage in Lebanon, has been set free after more than five years in captivity.” John McCarthy John McCarthy(journalist) ,Introduction: Motivation Web searches Queries about Named Entities (NEs) constitute a significant portion of popular web queries (Bunescu et al., EACL 2006). ~ 30% of search engine queries include person names (R. Guha et al., WWW 2004) Named entity disambiguation can lead to improve effectiveness of search results on the web for popular named entities. Web-based Information Extraction Identifying exactly NEs in web pages can improve accuracy in IE tasks (e.g. extracting relationships between NEs). Question & Answering Identifying exactly NEs in questions can improve accuracy of answers ,Introduction: NE Disambiguation Mapping entity names (in a text) to actual entities in a KB of discourse (e.g. Wikipedia). An ambiguous entity names are out of the KB An ambiguous entity names occur in the KB, but they refer to named entities out of the KB An ambiguous entity names refer to two or more than named entities in the KB ,Introduction: NE disambiguation But much like the first presidential debate held two weeks ago in Oxford, Mississippi, a draw for Obama would be considered a win. ,Introduction: NE disambiguation Gamsakhurdia is seen as a national hero by those who mourn him Zviad Gamsakhurdia, Georgia's first president after independence from the USSR, has been buried in the capital Tbilisi 14 years after his death. ,NE disambiguation John McCarthy, 'great man' of computer science, wins major award ,Introduction: Approach Disambiguation based on context Co-occurring entity names Co-occurring NE identifiers Tokens in a window context centered at a name in consideration Disambiguation based on a KB We view that instances in the KB have two in formation Attributes Relations We represent those instances by their attributes and relations ,Introduction: Approach Text containing ambiguous names Wikipedia article All keywords in the window text centred around the ambiguous name The whole text is extended with page titles of the previously identified NEs enclosed Entity page titles Redirecting page titles Category labels Hyperlink labels Heuristics +TF-IDF vector similarity ,Wikipedia Wikipedia is a free encyclopedia written by a collaborative effort of global community of more than 150,000 volunteers These volunteers have contributed more than 11 million articles in 265 languages More than 275 million people visit Wikipedia site every month 2,697,848 articles in English version (visiting Jan 14th, 2009) ,Wikipedia – Pages &Titles Page Titles (ID) ,Wikipedia – Pages &Titles Disambiguation text ,Wikipedia – Category Category ,Wikipedia – Redirect pages Redirect page titles ,Wikipedia – Hype