Textual and Visual Information Retrieval using Query Refinement and Pattern Analysis

Description

This book offers comprehensive coverage of information retrieval by considering both Text Based Information Retrieval (TBIR) and Content Based Image Retrieval (CBIR), together with new research topics. The approach to TBIR is based on creating a thesaurus, as well as event classification and detection. N-gram thesaurus generation for query refinement offers a new method for improving the precision of retrieval, while event classification and detection approaches aid in the classification and organization of information using web documents for domain-specific retrieval applications. In turn, with regard to content based image retrieval (CBIR) the book presents a histogram construction method, which is based on human visual perceptions of color. The book’s overarching goal is to introduce readers to new ideas in an easy-to-follow manner. Front Matter ....Pages i-xxvi Intelligent Rule-Based Deep Web Crawler (S. G. Shaila, A. Vadivel)....Pages 1-19 Information Classification and Organization Using Neuro-Fuzzy Model for Event Pattern Retrieval (S. G. Shaila, A. Vadivel)....Pages 21-54 Constructing Thesaurus Using TAG Term Weight for Query Expansion in Information Retrieval Application (S. G. Shaila, A. Vadivel)....Pages 55-75 Smooth Weighted Colour Histogram Using Human Visual Perception for Content-Based Image Retrieval Applications (S. G. Shaila, A. Vadivel)....Pages 77-92 Cluster Indexing and GR Encoding with Similarity Measure for CBIR Applications (S. G. Shaila, A. Vadivel)....Pages 93-122 Back Matter ....Pages 123-123