@article{
 title = {Text classification and named entities for new event detection},
 type = {article},
 year = {2004},
 identifiers = {[object Object]},
 pages = {297-304},
 websites = {http://portal.acm.org/citation.cfm?doid=1008992.1009044},
 publisher = {ACM Press},
 editors = {[object Object],[object Object],[object Object],[object Object]},
 id = {8491c3f5-5f6e-3b42-a222-0da4b9852efb},
 created = {2011-12-28T07:04:55.000Z},
 file_attached = {true},
 profile_id = {5284e6aa-156c-3ce5-bc0e-b80cf09f3ef6},
 group_id = {066b42c8-f712-3fc3-abb2-225c158d2704},
 last_modified = {2017-03-14T14:36:19.698Z},
 tags = {named entities},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Kumaran2004},
 private_publication = {false},
 abstract = {New Event Detection is a challenging task that still offers scope for great improvement after years of effort. In this paper we show how performance on New Event Detection (NED) can be improved by the use of text classification techniques as well as by using named entities in a new way. We explore modifications to the document representation in a vector space-based NED system. We also show that addressing named entities preferentially is useful only in certain situations. A combination of all the above results in a multi-stage NED system that performs much better than baseline single-stage NED systems.},
 bibtype = {article},
 author = {Kumaran, Giridhar and Allan, James},
 journal = {Proceedings of the 27th annual international conference on Research and development in information retrieval SIGIR 04}
}

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