@article{
 title = {Weakly-supervised discovery of named entities using web search queries},
 type = {article},
 year = {2007},
 identifiers = {[object Object]},
 keywords = {knowledge acquisition,named entities,query logs,supervised information extraction,unstructured text,weakly},
 pages = {683},
 websites = {http://portal.acm.org/citation.cfm?doid=1321440.1321536},
 publisher = {ACM Press},
 id = {b269b509-1ccd-3ffd-adf0-412e42881537},
 created = {2011-02-27T18:33:21.000Z},
 file_attached = {false},
 profile_id = {5284e6aa-156c-3ce5-bc0e-b80cf09f3ef6},
 group_id = {066b42c8-f712-3fc3-abb2-225c158d2704},
 last_modified = {2017-03-14T14:36:19.698Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Pasca2007},
 private_publication = {false},
 abstract = {A seed-based framework for textual information extraction allows for weakly supervised extraction of named entities from anonymized Web search queries. The extraction is guided by a small set of seed named entities, without any need for handcrafted extraction patterns or domain-specific knowledge, allowing for the acquisition of named entities pertaining to various classes of interest to Web search users. Inherently noisy search queries are shown to be a highly valuable, albeit little explored, resource for Web-based named entity discovery.},
 bibtype = {article},
 author = {Paşca, Marius},
 journal = {Proceedings of the sixteenth ACM conference on Conference on information and knowledge management CIKM 07}
}

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