DocumentCode :
3363023
Title :
From Ambiguous Words to Key-Concept Extraction
Author :
Ajgalik, Marius ; Barla, Michal ; Bielikova, Maria
Author_Institution :
Fac. of Inf. & Inf. Technol., Slovak Univ. of Technol., Bratislava, Slovakia
fYear :
2013
fDate :
26-30 Aug. 2013
Firstpage :
63
Lastpage :
67
Abstract :
Automatic acquisition of keywords for given document is still an area of active research. In this paper, we consider shift from keyword-based representation to other perspective on representation of document´s focus in form of key-concepts. The advantage of using concepts over simple words is that concepts, apart from words, are unambiguous. This leads to better understanding of key-concepts than keywords. We present novel method of key-concept extraction, which provides an efficient way of automatic acquisition of key-concepts in machine processing. We evaluate our approach on classification problem, where we compare it to baseline TF-IDF keyword model and present its competitive results. We discuss its potential of its utilisation on the Web.
Keywords :
Internet; data acquisition; data structures; document handling; pattern classification; Web; ambiguous words; automatic key-concept acquisition; automatic keyword acquisition; baseline TF-IDF keyword model; classification problem; key-concept extraction; keyword-based representation; machine processing; Accuracy; Computational linguistics; Computers; Data mining; Semantics; Vectors; Web pages; PageRank; TF-IDF; TextRank; concept extraction; concepts; information content; inverse document frequency; term extraction; text classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Database and Expert Systems Applications (DEXA), 2013 24th International Workshop on
Conference_Location :
Los Alamitos, CA
ISSN :
1529-4188
Print_ISBN :
978-0-7695-5070-1
Type :
conf
DOI :
10.1109/DEXA.2013.16
Filename :
6621347
Link To Document :
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