Cooperative Information Retrieval enhanced by formal concept analysis

Along with the growth of the World Wide Web, information retrieval systems gain importance since they are often the only way to find the few documents actually relevant to a specific question in the vast quantities of text available. Moreover, with the advent of the Web along with the unprecedented amount of information available in electronic format and its distributed structure, Formal Concept Analysis (FCA) is more useful and practical than ever, because this technology addresses important limitations of the systems that currently support users in their quest for information. Over the last few years, the range of functionality has been expanded to include new tasks such as data reduction and collaborative (or cooperative) information retrieval. In fact, due to the huge quantity of available information and its distributed structure, it is necessary to abstract it and eliminate the redundancy data. In this context, a method for data reduction based on the formal concept analysis is proposed in [16,17]. At the same time, new IR domains have been investigated including different types of information (email messages, web documents,..). Thus, there is nowadays a much better awareness of the strengths and limitations of this technique for organising and searching distributed information. We are interested by searching in distributed information.

[1]  Claudio Carpineto,et al.  A lattice conceptual clustering system and its application to browsing retrieval , 2004, Machine Learning.

[2]  Bernhard Ganter,et al.  Formal Concept Analysis: Mathematical Foundations , 1998 .

[3]  L. Beran,et al.  [Formal concept analysis]. , 1996, Casopis lekaru ceskych.

[4]  Claudio Carpineto,et al.  FUB at TREC-10 Web Track: A Probabilistic Framework for Topic Relevance Term Weighting , 2001, TREC.

[5]  Rokia Missaoui,et al.  Experimental Comparison of Navigation in a Galois Lattice with Conventional Information Retrieval Methods , 1993, Int. J. Man Mach. Stud..

[6]  Olivier Ridoux,et al.  A File System Based on Concept Analysis , 2000, Computational Logic.

[7]  Robert Godin,et al.  Lattice model of browsable data spaces , 1986, Inf. Sci..

[8]  S. Elloumi,et al.  Conceptual information retrieval based on cooperative conceptual data reduction , 2004, Proceedings. 2004 International Conference on Information and Communication Technologies: From Theory to Applications, 2004..

[9]  Stamatios V. Kartalopoulos,et al.  Proceedings of the 12th WSEAS international conference on Computers , 2008 .

[10]  Claudio Carpineto,et al.  Effective Reformulation of Boolean Queries with Concept Lattices , 1998, FQAS.

[11]  Gerard Salton,et al.  Automatic Text Processing: The Transformation, Analysis, and Retrieval of Information by Computer , 1989 .

[12]  Peter W. Eklund,et al.  Browsing Semi-structured Web Texts Using Formal Concept Analysis , 2001, ICCS.

[13]  Hafedh Mili,et al.  Building and maintaining analysis-level class hierarchies using Galois Lattices , 1993, OOPSLA '93.

[14]  Samir Elloumi,et al.  Using Concept Formal Analysis for Cooperative Information Retrieval , 2004, CLA.

[15]  J. Bordat Calcul pratique du treillis de Galois d'une correspondance , 1986 .

[16]  Ali Jaoua,et al.  May reasoning be reduced to an information retrieval problem? , 1998, RelMiCS.

[17]  Claudio Carpineto,et al.  Using Concept Lattices for Text Retrieval and Mining , 2005, Formal Concept Analysis.

[18]  Claude Chrisment,et al.  Querying a Hypertext Information Retrieval System by the Use of Classification , 1993, Inf. Process. Manag..

[19]  Mohamed Mohsen Gammoudi,et al.  A formal method for inheritance graph hierarchy construction , 2002, Inf. Sci..

[20]  Claudio Carpineto,et al.  Information retrieval through hybrid navigation of lattice representations , 1996, Int. J. Hum. Comput. Stud..