Linking named entities in tweets with knowledge base via user interest modeling

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn Part F128815, Issue , 2013, Pages 68-76

  Shen, Wei ^a   Wang, Jianyong ^a   Luo, Ping ^b   Wang, Min ^c  

^a TSINGHUA UNIVERSITY   (China)

^b HEWLETT PACKARD LABORATORIES   (United States)

^c GOOGLE INC   (United States)

Author keywords

Knowledge base; Tweet entity linking; User interest modeling

Indexed keywords

DATA MINING; GRAPHIC METHODS; KNOWLEDGE BASED SYSTEMS;

CONTEXT INFORMATION; KNOWLEDGE BASE; LOCAL INFORMATION; PERSONALIZED RECOMMENDATION; PRACTICAL IMPORTANCE; REAL-WORLD ENTITIES; TWEET ENTITY LINKING; USER INTEREST MODEL;

NATURAL LANGUAGE PROCESSING SYSTEMS;

EID: 85015278545     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2487575.2487686     Document Type: Conference Paper

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