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Location recognition with fuzzy grammar


Mohd Sharef, Nurfadhlina (2012) Location recognition with fuzzy grammar. In: Knowledge Technology. Communications in Computer and Information Science (295). Springer, Berlin, pp. 254-261. ISBN 9783642328251; EISBN: 9783642328268


Fuzzy grammar has been introduced as an approach to represent and learn text fragments where the set of learned patterns are represented by combining similar segments to represent regularities and marking interchangeable segments. This paper is dedicated to present a procedural scheme towards learning text fragment in text categorization task facilitated by fuzzy grammars. A few issues are involved in developing fuzzy grammars which are (i) determination of the number of text classes to develop (ii) the selection of text fragments, F relevant to each text class (iii) determining frequent and important terms or keywords, V to develop the set of terminal, T and compound grammars, N. (iv) Conversion of text fragments into grammars, (v) Combination of grammars into a compact form. Comparison between fuzzy grammar and other location entity identifier such as LbjTagger, LingPipe, Newswire and Open Calais is observed where results have shown that this method outperforms other standard machine learning and statistical-based approach.

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Additional Metadata

Item Type: Book Section
Divisions: Faculty of Computer Science and Information Technology
DOI Number: https://doi.org/10.1007/978-3-642-32826-8_26
Publisher: Springer
Keywords: Fuzzy grammar; Text categorization; Evolving fuzzy grammar; Text mining
Depositing User: Nurul Ainie Mokhtar
Date Deposited: 19 Jan 2016 04:26
Last Modified: 19 Jan 2016 04:26
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1007/978-3-642-32826-8_26
URI: http://psasir.upm.edu.my/id/eprint/26092
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