Extraction and evaluation of candidate named entities in search engine queries

Alasiry, Areej and Levene, Mark and Poulovassilis, Alexandra (2012) Extraction and evaluation of candidate named entities in search engine queries. In: Wang, X.S. and Cruz, I. and Delis, A. and Huang, G. (eds.) Web Information Systems Engineering - WISE 2012. Lecture Notes in Computer Science 7651. Berlin, Germany: Springer Verlag, pp. 483-496. ISBN 9783642350634.

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Official URL: http://dx.doi.org/10.1007/978-3-642-35063-4_35

Abstract

Named Entity Recognition (NER) has recently been applied to search queries, in order to better understand their semantics. We present a novel method for detecting candidate named entities (NEs) using grammar annotation and query segmentation with the aid of top-n snippets from search engine results, and a web n-gram model to accurately identify NE boundaries. We then evaluate this method automatically using DBpedia as a rich data source of NEs, with the aid of a small representative random sample that is manually annotated. Finally, an analysis of the types of named entities that often occur in a query log is conducted, from which a search query driven named entity taxonomy is presented.

Metadata

Item Type:	Book Section
School:	Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
Research Centres and Institutes:	Innovation Management Research, Birkbeck Centre for, Bioinformatics, Bloomsbury Centre for (Closed), Birkbeck Knowledge Lab
Depositing User:	Sarah Hall
Date Deposited:	30 May 2013 16:41
Last Modified:	09 Aug 2023 12:33
URI:	https://eprints.bbk.ac.uk/id/eprint/7145

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