Knowledge-Based Information Retrieval and Filtering from the Web
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 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;
-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.