Knowledge-Based Information Retrieval and Filtering from the Web / Edition 1

Knowledge-Based Information Retrieval and Filtering from the Web / Edition 1

by Witold Abramowicz
     
 

ISBN-10: 1441953760

ISBN-13: 9781441953766

Pub. Date: 12/06/2010

Publisher: Springer US

In today's business arena information is one of the most important resources possessed by enterprises. In order to support proper information flow, businesses deploy transactional systems, build decision support systems or launch management information systems. Unfortunately, the majority of information systems do not take advantage of recent developments in

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Overview

In today's business arena information is one of the most important resources possessed by enterprises. In order to support proper information flow, businesses deploy transactional systems, build decision support systems or launch management information systems. Unfortunately, the majority of information systems do not take advantage of recent developments in knowledge management, thus exposing companies to the risk of missing important information, or what is even worse, leading them to misinterpret information.

Knowledge-Based Information Retrieval and Filtering from the Web contains fifteen chapters, contributed by leading international researchers, addressing the matter of information retrieval, filtering and management of the information on the Internet. The research presented in these chapters deals with the need to find proper solutions for the description of the information found on the Internet, the description of the information consumers need, the algorithms for retrieving documents (and indirectly, the information embedded in them), and the presentation of the information found. The chapters include:
-Ontological representation of knowledge on the WWW;
-Information extraction;
-Information retrieval and administration of distributed documents;
-Hard and soft modeling based knowledge capture;
-Summarization of texts found on the WWW;
-User profiles and personalization for web-based information retrieval system;
-Information retrieval under constricted bandwidth;
-Multilingual WWW;
-Generic hierarchical classification using the single-link clustering;
-Clustering of documents on the basis of text fuzzy similarity;
-Intelligent agents for document categorization and adaptive filtering;
-Multimedia retrieval and data mining for E-commerce and E-business;
-A Web-based approach to competitive intelligence;
-Learning ontologies for domain-specific information retrieval;
-An open, decentralized architecture for searching for, and publishing information in distributed systems.

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Product Details

ISBN-13:
9781441953766
Publisher:
Springer US
Publication date:
12/06/2010
Series:
The Springer International Series in Engineering and Computer Science, #746
Edition description:
Softcover reprint of hardcover 1st ed. 2003
Pages:
303
Product dimensions:
0.67(w) x 9.21(h) x 6.14(d)

Table of Contents

Preface
Contributing authors
Ch. 1Towards an Ontological Representation of Knowledge on the Web1
Ch. 2Advances in Information Extraction23
Ch. 3Information Retrieval and Administration of Distributed Documents in Internet53
Ch. 4Hard and Soft Modelling Based Knowledge Capture for Information Flow Management75
Ch. 5Summarization of Texts Found on the World Wide Web101
Ch. 6Model of User Profiles and Personalization for Web-based Information Retrieval System121
Ch. 7An open, decentralised architecture for searching for, and publishing, information in distributed systems137
Ch. 8Information Retrieval under Constricted Bandwidth153
Ch. 9Multilingual WWW165
Ch. 10Generic Hierarchical Classification Using the Single-Link Clustering185
Ch. 11Clustering of Documents on the Basis of Text Fuzzy Similarity219
Ch. 12Intelligent Agents for Document Categorization and Adaptive Filtering Using a Neural Network Approach and Fuzzy Logic231
Ch. 13The Virtual Boutique: Multimedia Retrieval and Data Mining for E-commerce and E-business in the framework of a virtual environment251
Ch. 14A Web-based approach to Competitive Intelligence269
Ch. 15Learning Ontologies for Domain-Specific Information Retrieval285

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