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Skorkovská, L. : Dynamic Threshold Selection Method for Multi-label Newspaper Topic Identification . Text, Speech and Dialogue, Lecture Notes in Computer Science, vol. 8082, p. 209-216, Springer, Heidelberg, 2013.

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Abstract

Nowadays, the multi-label classification is increasingly required in modern categorization systems. It is especially essential in the task of newspaper article topics identification. This paper presents a method based on general topic model normalisation for finding a threshold defining the boundary between the "correct" and the "incorrect" topics of a newspaper article. The proposed method is used to improve the topic identification algorithm which is a part of a complex system for acquisition and storing large volumes of text data. The topic identification module uses the Naive Bayes classifier for the multiclass and multi-label classification problem and assigns to each article the topics from a defined quite extensive topic hierarchy - it contains about 450 topics and topic categories. The results of the experiments with the improved topic identification algorithm are presented in this paper.

Detail of publication

Title: Dynamic Threshold Selection Method for Multi-label Newspaper Topic Identification
Author: Skorkovská, L.
Language: English
Date of publication: 1 Sep 2013
Year: 2013
Type of publication: Papers in journals
Title of journal or book: Text, Speech and Dialogue
Series: Lecture Notes in Computer Science
Číslo vydání: 8082
Page: 209 - 216
DOI: 10.1007/978-3-642-40585-3_27
ISBN: 978-3-642-40584-6
ISSN: 0302-9743
Publisher: Springer
Address: Heidelberg
Date: 1 Sep 2013 - 5 Sep 2013
/ 2013-09-10 15:10:27 /

Keywords

topic identification, multi-label text classification, language modeling, Naive Bayes classification

BibTeX

@ARTICLE{SkorkovskaL_2013_DynamicThreshold,
 author = {Skorkovsk\'{a}, L.},
 title = {Dynamic Threshold Selection Method for Multi-label Newspaper Topic Identification},
 year = {2013},
 publisher = {Springer},
 journal = {Text, Speech and Dialogue},
 address = {Heidelberg},
 volume = {8082},
 pages = {209-216},
 series = {Lecture Notes in Computer Science},
 ISBN = {978-3-642-40584-6},
 ISSN = {0302-9743},
 doi = {10.1007/978-3-642-40585-3_27},
 url = {http://www.kky.zcu.cz/en/publications/SkorkovskaL_2013_DynamicThreshold},
}