Techniques for Named Entity Recognition: A Survey

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Author(s): Girish Keshav Palshikar (Tata Research Development and Design Centre, India)
Copyright: 2012
Pages: 27
Source title: Collaboration and the Semantic Web: Social Networks, Knowledge Networks, and Knowledge Resources
Source Author(s)/Editor(s): Stefan Brüggemann (Astrium Space Transportation, Germany)and Claudia d’Amato (University of Bari, Italy)
DOI: 10.4018/978-1-4666-0894-8.ch011

Keywords: Computer Science & IT / Information Science Reference / Semantic Web / Social Computing

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Abstract

While building and using a fully semantic understanding of Web contents is a distant goal, named entities (NEs) provide a small, tractable set of elements carrying a well-defined semantics. Generic named entities are names of persons, locations, organizations, phone numbers, and dates, while domain-specific named entities includes names of for example, proteins, enzymes, organisms, genes, cells, et cetera, in the biological domain. An ability to automatically perform named entity recognition (NER) – i.e., identify occurrences of NE in Web contents – can have multiple benefits, such as improving the expressiveness of queries and also improving the quality of the search results. A number of factors make building highly accurate NER a challenging task. Given the importance of NER in semantic processing of text, this chapter presents a detailed survey of NER techniques for English text.

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Techniques for Named Entity Recognition: A Survey

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