Screen LibraryTextual and visual information retrieval using query refinement and pattern analysis /
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 detecti...
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| Main Authors: | |
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| Published: |
Springer,
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| Publisher Address: | Singapore : |
| Publication Dates: | [2018] |
| Literature type: | Book |
| Language: | English |
| Subjects: | |
| Summary: |
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. |
| Carrier Form: | xxvi, 123 pages : illustrations (some color) ; 25 cm |
| Bibliography: | Includes bibliographical references. |
| ISBN: |
9789811325588 9811325588 9789811325601 981132560X |
| Index Number: | ZA3075 |
| CLC: | G254.9 |
| Call Number: | G254.9/S526 |
| Contents: | Intelligent rule-based deep web crawler -- Information classification and organization using neuro-fuzzy model for event pattern retrieval -- Constructing thesaurus using TAG term wight for query expansion in information retreival application -- Smooth weighted colour histogram using human visual perception for content-based image retrieval applications -- Cluster indexing and GR encoding with similarity measure for CBIR applications. |