@inProceedings{
 title = {Discovery of business opportunities on the internet with information extraction},
 type = {inProceedings},
 year = {2005},
 pages = {47-54},
 websites = {http://www.iro.umontreal.ca/~aimeur/publications/Workshop20.pdf#page=53},
 city = {Edinburgh, Scotland},
 id = {401b938f-01bb-3c11-90d9-103ba2498202},
 created = {2012-12-24T15:02:36.000Z},
 accessed = {2012-11-26},
 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 = {Paradis2005},
 private_publication = {false},
 abstract = {In this paper we describe a tool for the discovery of business opportunities on the Web. The aim of our system is to help a user decide which call for tenders should be examined further. The project and its goals will be presented. We then focus on one aspect, named entity extraction, and its use to improve classification and user navigation. We show that filtering contents improves the classifica- tion results, but so far we did not get a significant improvement by combining named entities and ex- traction. However there are benefits to the interface to facilitate query refinement and collection browsing.},
 bibtype = {inProceedings},
 author = {Paradis, Francois and Nie, Jian-Yun and Tajarobi, Arman},
 booktitle = {Workshop on Multi-Agent Information Retrieval and Recommender Systems (IJCAI)}
}

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