Rules and fuzzy rules in text: concept, extraction and usage

Several concepts and techniques have been imported from other disciplines such as Machine Learning and Artificial Intelligence to the field of textual data. In this paper, we focus on the concept of rule and the management of uncertainty in text applications. The different structures considered for the construction of the rules, the extraction of the knowledge base and the applications and usage of these rules are detailed. We include a review of the most relevant works of the different types of rules based on their representation and their application to most of the common tasks of Information Retrieval such as categorization, indexing and classification.

[1]  David D. Lewis,et al.  Learning in Intelligent Information Retrieval , 1991, ML.

[2]  Donald H. Kraft,et al.  Combining fuzzy clustering and fuzzy inferencing in information retrieval , 2000, Ninth IEEE International Conference on Fuzzy Systems. FUZZ- IEEE 2000 (Cat. No.00CH37063).

[3]  Fabrizio Sebastiani,et al.  Trends in ... a Critical Review: On the Role of Logic in Information Retrieval , 1998, Inf. Process. Manag..

[4]  Peter Willett,et al.  The limitations of term co-occurrence data for query expansion in document retrieval systems , 1991, J. Am. Soc. Inf. Sci..

[5]  Rajeev Motwani,et al.  Beyond Market Baskets: Generalizing Association Rules to Dependence Rules , 1998, Data Mining and Knowledge Discovery.

[6]  William W. Cohen Fast Effective Rule Induction , 1995, ICML.

[7]  Janusz Kacprzyk,et al.  Intelligent Exploration of the Web , 2003, Studies in Fuzziness and Soft Computing.

[8]  James C. Bezdek,et al.  Knowledge-assisted document retrieval. I: The natural-language interface , 1987 .

[9]  Daniel Sánchez,et al.  Mining Text Data: Special Features and Patterns , 2002, Pattern Detection and Discovery.

[10]  William W. Cohen Learning Rules that Classify E-Mail , 1996 .

[11]  Donald H. Kraft,et al.  Textual Information Retrieval with User Profiles Using Fuzzy Clustering and Inferencing , 2003, Intelligent Exploration of the Web.

[12]  Michael McGill,et al.  Introduction to Modern Information Retrieval , 1983 .

[13]  Karen Spärck Jones The role of artificial intelligence in information retrieval , 1991, J. Am. Soc. Inf. Sci..

[14]  Peter J. F. Lucas,et al.  Principles of expert systems , 1991, International computer science series.

[15]  Amihai Motro,et al.  Uncertainty Management in Information Systems: From Needs to Solution , 1996 .

[16]  Daniel Sánchez,et al.  Fuzzy association rules: general model and applications , 2003, IEEE Trans. Fuzzy Syst..

[17]  Didier Dubois,et al.  Readings in Fuzzy Sets for Intelligent Systems , 1993 .

[18]  Ellen M. Voorhees,et al.  Query expansion using lexical-semantic relations , 1994, SIGIR '94.

[19]  Osmar R. Zaïane,et al.  Text document categorization by term association , 2002, 2002 IEEE International Conference on Data Mining, 2002. Proceedings..

[20]  W. Bruce Croft,et al.  I3R: A new approach to the design of document retrieval systems , 1987, J. Am. Soc. Inf. Sci..

[21]  W. Bruce Croft,et al.  I 3 R: a new approach to the design of document retrieval systems , 1987 .

[22]  Yoram Singer,et al.  Context-sensitive learning methods for text categorization , 1996, SIGIR '96.

[23]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[24]  Daniel Sánchez,et al.  Association Rule Extraction for Text Mining , 2002, FQAS.

[25]  W. Bruce Croft,et al.  Uncertainty in Information Retrieval Systems , 1996, Uncertainty Management in Information Systems.

[26]  Sholom M. Weiss,et al.  Automated learning of decision rules for text categorization , 1994, TOIS.

[27]  Ramon López de Mántaras,et al.  Approximate Reasoning Models , 1990 .

[28]  M. Vila,et al.  Intelligent filtering with genetic algorithms and fuzzy logic , 2002 .

[29]  Donald H. Kraft,et al.  Fuzzy Sets and Generalized Boolean Retrieval Systems , 1983, Int. J. Man Mach. Stud..

[30]  James C. Bezdek,et al.  Knowledge-assisted document retrieval: I. The natural-language interface , 1987, J. Am. Soc. Inf. Sci..

[31]  Gloria Bordogna,et al.  Fuzzy Approaches to Extend Boolean Information Retrieval , 1995 .

[32]  Richard A. Frost,et al.  Introduction to Knowledge Base Systems , 1986 .

[33]  Rakesh Agarwal,et al.  Fast Algorithms for Mining Association Rules , 1994, VLDB 1994.

[34]  Henri Prade,et al.  What are fuzzy rules and how to use them , 1996, Fuzzy Sets Syst..

[35]  Fei Song,et al.  Knowledge-Based Approaches to Query Expansion in Information Retrieval , 1996, Canadian Conference on AI.

[36]  David D. Lewis,et al.  Representation and Learning in Information Retrieval , 1991 .

[37]  W. B. Cavnar,et al.  Using An N-Gram-Based Document Representation With A Vector Processing Retrieval Model , 1994, TREC.

[38]  Daniel G. Shapiro,et al.  RUBRIC: A System for Rule-Based Information Retrieval , 1985, IEEE Transactions on Software Engineering.

[39]  Gerard Salton,et al.  Term-Weighting Approaches in Automatic Text Retrieval , 1988, Inf. Process. Manag..

[40]  Edward A. Fox,et al.  Development of the coder system: A testbed for artificial intelligence methods in information retrieval , 1987, Inf. Process. Manag..

[41]  Yves Kodratoff,et al.  Comparing Machine Learning and Knowledge Discovery in DataBases: An Application to Knowledge Discovery in Texts , 2001, Machine Learning and Its Applications.

[42]  Susan Gauch,et al.  Intelligent Information Retrieval: An Introduction , 1992, J. Am. Soc. Inf. Sci..

[43]  Padhraic Smyth,et al.  From Data Mining to Knowledge Discovery: An Overview , 1996, Advances in Knowledge Discovery and Data Mining.

[44]  Karen Spärck Jones,et al.  Information Retrieval and Artificial Intelligence , 1999, Artif. Intell..

[45]  Sukhamay Kundu,et al.  A Sound and Complete Fuzzy Logic System Using Zadeh's Implication Operator , 1996, ISMIS.

[46]  Donald H. Kraft,et al.  Integrating and Extending Fuzzy Clustering and Inferencing to Improve Text Retrieval Performance , 2000, FQAS.

[47]  Donald H. Kraft,et al.  Fuzzy Set Techniques in Information Retrieval , 1999 .

[48]  Vijay V. Raghavan,et al.  Automatic construction of rule-based trees for conceptual retrieval , 2000, Proceedings Seventh International Symposium on String Processing and Information Retrieval. SPIRE 2000.

[49]  Marti A. Hearst Untangling Text Data Mining , 1999, ACL.

[50]  Lotfi A. Zadeh,et al.  Fuzzy logic, neural networks, and soft computing , 1993, CACM.