Top

Soft Computing

Published in:

01-06-2010 | Focus

Fuzzy optimized self-organizing maps and their application to document clustering

Authors: Francisco P. Romero, Arturo Peralta, Andres Soto, Jose A. Olivas, Jesus Serrano-Guerrero

Published in: Soft Computing | Issue 8/2010

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

In this paper, an approach using fuzzy logic techniques and self-organizing maps (SOM) is presented in order to manage conceptual aspects in document clusters and to reduce the training time. In order to measure the presence degree of a concept in a document, a concept frequency formula is introduced. This formula is based on new fuzzy formulas to calculate the polysemy degree of terms and the synonymy degree between terms. In this approach, new fuzzy improvements such as automatic choice of the topology, heuristic map initialization, a fuzzy similarity measure and a keywords extraction process are used. Some experiments have been carried out in order to compare the proposed system with classic SOM approaches by means of Reuters collection. The system performance has been measured in terms of F-measure and training time. The experimental results show that the proposed approach generates good results with less training time compared to classic SOM techniques.

previous article A new fusion strategy for web metasearch

next article Reasoning about fuzzy temporal information from the web: towards retrieval of historical events

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

http://www.daviddlewis.com/resources/testcollections.

Apté C, Damerau F, Weiss SM (1994) Automated learning of decision rules for text categorization. ACM Trans Inf Syst 12(3):233–251CrossRef

Azcarraga AP, Yap TN (2001) Som-based methodology for building large text archives. In: Proceedings of the 7th international conference on database systems for advanced applications, pp 66–73. IEEE Computer Society, Washington

Baeza-Yates R, Ribeiro-Neto B (1999) Modern information retrieval. ACM Press, New York

Bezdek JC, Tsao EC, Pal NR (1992) Fuzzy kohonen clustering networks. In: Proceedings of the IEEE international conference on fuzzy systems, pp 1035–1043

Bordogna G, Pagani M, Pasi G (2006) A dynamical hierarchical fuzzy clustering algorithm for document filtering. Stud Fuzziness Soft Comput 197:1–23CrossRef

Bouchachia A, Mittermeir R (2006) Towards incremental fuzzy classifiers. Soft Comput 11(2):193–207CrossRef

Cottrell M, Verleysen M (2006) Advances in self-organizing maps. Neural Netw 19(6):721–722CrossRef

Ellman J (2003) Eurowordnet: a multilingual database with lexical semantic networks. Nat Lang Eng 9(4):427–430CrossRef

Fellbaum C (1998) WordNet: an electronic lexical database. MIT Press, Cambridge

Fernandez S, Grana J, Sobrino A (2002) A spanish e-dictionary of synonyms as a fuzzy tool for information retrieval. In: Actas de las I Jornadas de Tratamiento y Recuperacion de Informacion

Garcés P, Olivas J, Romero F (2006) Concept-matching IR systems versus word-matching information retrieval systems: considering fuzzy interrelations for indexing web pages. J Am Soc Inf Sci Technol 57(4):564–576CrossRef

Gonzalo J, Verdejo F, Chugur I (1998) Indexing with wordnet synsets can improve text retrieval. In: Proceedings of the COLING/ACL’98 Workshop on Usage of WordNet for NLP, pp 38–44

Han J (2005) Data Mining: concepts and techniques. Morgan Kaufmann, San Francisco

Hotho A, Staab S, Stumme G (2003) Ontologies improve text document clustering. In: Proceedings of the third IEEE international conference on data mining, pp 541–544. IEEE Press, Washington DC

Huntsberger T, Ajjimarangsee P (1992) Parallel self-organizing feature maps for unsupervised pattern recognition. In: Fuzzy Models for Pattern Recognition, pp 483–495

Kaski S (1998) Dimensionality reduction by random mapping: fast similarity computation for clustering. In: Proceedings international join conference on neural networks, vol 1, pp 413–418

Kohonen T (1982) Self-organized formation of topologically correct feature maps. Biol Cybern 43:59–69MATHCrossRefMathSciNet

Kohonen T (1998) The self-organizing map. Neurocomputing 21:1–6MATHCrossRef

Kong S, Kosko B (1992) Adaptive fuzzy system for backing up a truck-and-trailer. IEEE Trans Neural Netw 3:211–223CrossRef

Lagus K, Honkela T, Kaski S, Kohonen T (1999) Websom for textual data mining. Artif Intell Rev 13(5–6):345–364CrossRef

Lazzerini B, Marcelloni F (2007) A hierarchical fuzzy clustering-based system to create user profiles. Soft Comput 11:157–168MATHCrossRef

Li Y, Chung SM, Holt JD (2008) Text document clustering based on frequent word meaning sequences. Data Knowl Eng 64(1):381–404CrossRef

Lin X, Soergel D, Marchionini G (1991) A self-organizing semantic map for information retrieval. In: Proceedings of the 14th annual international ACM SIGIR conference, pp 262–269. ACM, New York

Merkl D (1998) Text classification with self-organizing maps: some lessons learned. Neurocomputing 21:68–77CrossRef

Miller GA, Beckwith R, Fellbaum C et al (1990) Introduction to wordnet: an on-line lexical database. Int J Lexicogr 3(4):235–244CrossRef

Mitra S, Pal SK (1994) Self-organizing neural network as a fuzzy classifier. IEEE Trans Syst Man Cybern 24(3):385–399CrossRef

Miyamoto S (1990) Fuzzy sets in information retrieval and cluster analysis. Kluwer, Dordrecht

Nürnberger A, Detyniecki M (2006) Externally growing self-organizing maps and its application to e-mail database visualization and exploration. Appl Soft Comput 6(4):357–371CrossRef

Olivas JA, Garcés PJ, Romero FP (2003) An application of the fis-crm model to the fiss metasearcher: using fuzzy synonymy and fuzzy generality for representing concepts in documents. Int J Approx Reason 34:201–209MATHCrossRef

Pascual-Marqui RD, Pascual-Montano AD, Kochi K, Carazo JM (2001) Smoothly distributed fuzzy c-means: a new self-organizing map. Pattern Recognit 34:2395–2402CrossRef

Ritter H, Kohonen T (1989) Self-organizing semantic maps. Biol Cybern 61:241–254CrossRef

Romero FP, Olivas JA, Garcés PJ (2006) A soft approach to hybrid models for document clustering. Proc Inform Process Manag Uncertain Knowl Based Syst 1:1040–1045

Salton G, McGill MJ (1986) Introduction to modern information retrieval. McGraw-Hill, New York

Soto A, Olivas JA, Prieto M (2008) Fuzzy approach of synonymy and polysemy for information retrieval. Stud Fuzziness Soft Comput 224:179–198CrossRef

Steinbach M, Karypis G, Kumara V (2000) A comparison of document clustering techniques. In: Proceedings of the knowledge discovery on databases, pp 3–7

Uchida H, Zhu M, Della ST (1995) UNL: a gift for a millennium. The United Nations University, Tokyo

Van Rijsbergen C (1979) Information retrieval. Butterworth, London

Vuorimaa P (1994) Fuzzy self-organizing map. Fuzzy Sets Syst 66:223–231CrossRef

Wallace M, Akrivas G, Stamou G (2003) Automatic thematic categorization of documents using a fuzzy taxonomy and fuzzy hierarchical clustering. In: Proceedings of the 12th IEEE international conference on fuzzy systems, vol 2, pp 1446–1451

Title: Fuzzy optimized self-organizing maps and their application to document clustering
Authors: Francisco P. Romero
Arturo Peralta
Andres Soto
Jose A. Olivas
Jesus Serrano-Guerrero
Publication date: 01-06-2010
Publisher: Springer-Verlag
Published in: Soft Computing / Issue 8/2010
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-009-0468-3

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

Springer Professional "Technik"

Other articles of this Issue 8/2010

Friendly web services selection exploiting fuzzy formal concept analysis

Guest editorial: soft computing on the web

An extension of a fuzzy reputation agent trust model (AFRAS) in the ART testbed

A quality evaluation methodology for health-related websites based on a 2-tuple fuzzy linguistic approach

Soft computing and Web intelligence for supporting consensus reaching

A flexible multi criteria information filtering model

Premium Partner