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@inproceedings{707192,
author = {Popelínský, Lubomír and Blaťák, Jan},
address = {Ljubljana},
booktitle = {Proceedings of IS-LTC'06},
keywords = {text filtering; information extraction; term extraction},
language = {eng},
location = {Ljubljana},
pages = {35-40},
publisher = {Jožef Stefan Institute},
title = {Mining actions from reports on flood},
year = {2006}
}
TY - JOUR
ID - 707192
AU - Popelínský, Lubomír - Blaťák, Jan
PY - 2006
TI - Mining actions from reports on flood
PB - Jožef Stefan Institute
CY - Ljubljana
KW - text filtering
KW - information extraction
KW - term extraction
N2 - This paper focuses on mining in short reports that describe a situation in a given area and actions performed as reaction to that situation. Such texts are frequent in crisis management in situations like earthquake, fire or flood. For further analysis it is necessary to filter the relevant pieces of text. We found that common machine learning algo rithms fail for filtering such sentences. We describe a novel method based on inductive logic programming which yields in high precision and recall. This method has been successfully used for analysis of reports on flood in Central Europe in 2002. We also discuss different domain knowledge and also various natural language processing tools that we used for preprocessing the documents.
ER -
POPELÍNSKÝ, Lubomír a Jan BLAŤÁK. Mining actions from reports on flood. In \textit{Proceedings of IS-LTC'06}. Ljubljana: Jožef Stefan Institute, 2006, s.~35-40. ISSN~1581-9973.
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