Abstract | ||
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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. |
Year | DOI | Venue |
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2012 | 10.1145/2348283.2348463 | SIGIR |
Keywords | DocType | Citations |
detecting candidate,novel method,query segmentation,entities recognition,search query,multiple nes,information extraction task,engine query,ne boundary,search engine result,candidate nes,search engine,information extraction | Conference | 5 |
PageRank | References | Authors |
0.41 | 5 | 3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Areej Alasiry | 1 | 10 | 1.25 |
Mark Levene | 2 | 1272 | 252.84 |
Alexandra Poulovassilis | 3 | 1222 | 370.61 |