Soft Computing in Information Retrieval Techniques and Applications

Soft Computing in Information Retrieval Techniques and Applications / edited by Fabio Crestani, Gabriella Pasi.

Information retrieval (IR) aims at defining systems able to provide a fast and effective content-based access to a large amount of stored information. The aim of an IR system is to estimate the relevance of documents to users' information needs, expressed by means of a query. This is a very dif...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Crestani, Fabio (Editor), Pasi, Gabriella (Editor)
Format: eBook
Language:English
Published: Heidelberg : Physica-Verlag HD : Imprint: Physica, 2000.
Edition:1st ed. 2000.
Series:Studies in Fuzziness and Soft Computing, 50
Springer eBook Collection.
Subjects:
Information storage and retrieval.
Artificial intelligence.
Information technology.
Business—Data processing.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • I. Fuzzy Set Theory
  • A Framework for Linguistic and Hierarchical Queries in Document Retrieval
  • Application of Fuzzy Set Theory to Extend Boolean Information Retrieval
  • A Model of Intelligent Information Retrieval Using Fuzzy Tolerance Relations Based on Hierarchical Co-Occurrence of Words
  • II. Neural Networks
  • Visual Keywords: from Text Retrieval to Multimedia Retrieval
  • Document Classification with Unsupervised Artificial Neural Networks
  • The Java Search Agent Workshop
  • A Connectionist Approach to Content Access in Documents: Application to Detection of Jokes
  • III. Genetic Algorithms
  • Connectionist and Genetic Approaches for Information Retrieval
  • Large Population or Many Generations for Genetic Algorithms? Implications in Information Retrieval
  • IV. Evidential and Probabilistic Reasoning
  • A Logical Information Retrieval Model Based on a Combination of Propositional Logic and Probability Theory
  • Bayesian Network Models for Information Retrieval
  • Probabilistic Learning by Uncertainty Sampling with Non-Binary Relevance
  • V. Rough Sets Theory, Multivalued Logics, and Other Approaches
  • Granulär Information Retrieval
  • A Framework for the Retrieval of Multimedia Objects Based on Four-Valued Fuzzy Description Logics
  • Rough and Fuzzy Sets for Data Mining of a Controlled Vocabulary for Textual Retrieval
  • Rough Sets and Multisets in a Model of Information Retrieval.

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