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@inproceedings{695254, author = {Popelínský, Lubomír and Blaťák, Jan}, address = {Ostrava}, booktitle = {Znalosti 2006}, edition = {1}, keywords = {text filtering; information extraction; term extraction}, language = {cze}, location = {Ostrava}, isbn = {80-248-1001-8}, pages = {130-138}, publisher = {VŠB--Technická univerzita Ostrava}, title = {Mining situations and actions from news}, year = {2006} }
TY - JOUR ID - 695254 AU - Popelínský, Lubomír - Blaťák, Jan PY - 2006 TI - Mining situations and actions from news PB - VŠB--Technická univerzita Ostrava CY - Ostrava SN - 8024810018 KW - text filtering KW - information extraction KW - term extraction N2 - The definite goal of this project is building tools for automatic filtering news reports on flood, for extracting information from such reports and the use of this extracted information for finding important terms (single words, name/verb phrases, named entities etc.) and eventually building a domain ontology. In this paper we focus on classifying sentences that describe either a situation or an action by means of machine learning. The results of various learning algorithms are discussed. We also bring first results on term extraction. ER -
POPELÍNSKÝ, Lubomír a Jan BLAŤÁK. Mining situations and actions from news. In \textit{Znalosti 2006}. 1. vyd. Ostrava: VŠB--Technická univerzita Ostrava, 2006, s.~130-138. ISBN~80-248-1001-8.
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