Detecting candidate named entities in search queries

Authors:
Areej Alasiry;Mark Levene;Alexandra Poulovassilis
Affiliations:
Birkbeck, University of London, London, United Kingdom;Birkbeck, University of London, London, United Kingdom;Birkbeck, University of London, London, United Kingdom
Venue:
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Year:
2012

Citing 5
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Abstract

The information extraction task of Named Entities Recognition (NER) has been recently applied to search engine queries, in order to better understand their semantics. Here we concentrate on the task prior to the classification of the named entities (NEs) into a set of categories, which is the problem of detecting candidate NEs via the subtask of query segmentation.We present a novel method for detecting candidate 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. The proposed method addresses the problem of accurately setting boundaries of NEs and the detection of multiple NEs in queries.