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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