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Techniques for Named Entity Recognition: A Survey

Techniques for Named Entity Recognition: A Survey

Girish Keshav Palshikar (Tata Research Development and Design Centre, India)
Copyright: © 2012 |Pages: 27
ISBN13: 9781466608948|ISBN10: 1466608943|EISBN13: 9781466608955
DOI: 10.4018/978-1-4666-0894-8.ch011
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MLA

Palshikar, Girish Keshav. "Techniques for Named Entity Recognition: A Survey." Collaboration and the Semantic Web: Social Networks, Knowledge Networks, and Knowledge Resources, edited by Stefan Brüggemann and Claudia d’Amato, IGI Global, 2012, pp. 191-217. https://doi.org/10.4018/978-1-4666-0894-8.ch011

APA

Palshikar, G. K. (2012). Techniques for Named Entity Recognition: A Survey. In S. Brüggemann & C. d’Amato (Eds.), Collaboration and the Semantic Web: Social Networks, Knowledge Networks, and Knowledge Resources (pp. 191-217). IGI Global Scientific Publishing. https://doi.org/10.4018/978-1-4666-0894-8.ch011

Chicago

Palshikar, Girish Keshav. "Techniques for Named Entity Recognition: A Survey." In Collaboration and the Semantic Web: Social Networks, Knowledge Networks, and Knowledge Resources, edited by Stefan Brüggemann and Claudia d’Amato, 191-217. Hershey, PA: IGI Global, 2012. https://doi.org/10.4018/978-1-4666-0894-8.ch011

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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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