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.
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Alasiry, A., Levene, M., Poulovassilis, A. (2012). Extraction and Evaluation of Candidate Named Entities in Search Engine Queries. In: Wang, X.S., Cruz, I., Delis, A., Huang, G. (eds) Web Information Systems Engineering - WISE 2012. WISE 2012. Lecture Notes in Computer Science, vol 7651. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35063-4_35
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DOI: https://doi.org/10.1007/978-3-642-35063-4_35
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-35062-7
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