Using Noun Phrase Heads to Extract Document Keyphrases
AI '00 Proceedings of the 13th Biennial Conference of the Canadian Society on Computational Studies of Intelligence: Advances in Artificial Intelligence
Learning to link with wikipedia
Proceedings of the 17th ACM conference on Information and knowledge management
Named Entity Disambiguation: A Hybrid Statistical and Rule-Based Incremental Approach
ASWC '08 Proceedings of the 3rd Asian Semantic Web Conference on The Semantic Web
Entity disambiguation for knowledge base population
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Entity linking leveraging: automatically generated annotation
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Exploring Wikipedia and text features for named entity disambiguation
ACIIDS'10 Proceedings of the Second international conference on Intelligent information and database systems: Part II
Local and global algorithms for disambiguation to Wikipedia
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Collective entity linking in web text: a graph-based method
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
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With the wide usage of Wikipedia in research and applications,disambiguation of concepts and entities to Wikipedia is an essential component in natural language processing. This paper addresses the task of identifying and linking specific words or phrases in a text to their referents described by Wikipedia articles. In this work, we propose a method that combines some heuristics with a statistical model for disambiguation. The method exploits disambiguated entities to disambiguate the others in an incremental process. Experiments are conducted to evaluate and show the advantages of the proposed method.