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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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