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Textual and visual information retri...

Shaila, S. G.

Textual and visual information retrieval using query refinement and pattern analysis

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Textual and visual information retrieval using query refinement and pattern analysisby S. G. Shaila, A. Vadivel.
作者:	Shaila, S. G.
其他作者:	Vadivel, A.
出版者:	Singapore :Springer Singapore :2018.
面頁冊數:	xxvi, 123 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Information retrieval.
電子資源:	https://doi.org/10.1007/978-981-13-2559-5
ISBN:	9789811325595$q(electronic bk.)

Textual and visual information retrieval using query refinement and pattern analysis
Shaila, S. G.

Textual and visual information retrieval using query refinement and pattern analysis[electronic resource] /by S. G. Shaila, A. Vadivel. - Singapore :Springer Singapore :2018. - xxvi, 123 p. :ill., digital ;24 cm.

Chapter 1. Architecture Specification of Rule-Based Deep Web Crawler with Indexer -- Chapter 2. Information Classification and Organization using Neuro-Fuzzy Model Event Retrieval. Chapter 3. N-Gram Thesaurus Generation for Query Expansion and Refinement using Tag Term Weight for Information Retrieval -- Chapter 4. Smooth Weighted Color Histogram using Human Visual Perception for CBIR Applications -- Chapter 5. Indexing and Encoding Color Histogram with Bin Overlapped Similarity Measure for Image Retrieval -- Chapter 6. Summary and Conclusion.

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.

ISBN: 9789811325595$q(electronic bk.)

Standard No.: 10.1007/978-981-13-2559-5doiSubjects--Topical Terms:

215224
Information retrieval.

LC Class. No.: ZA3075

Dewey Class. No.: 025.04

Textual and visual information retrieval using query refinement and pattern analysis
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505 0 $a Chapter 1. Architecture Specification of Rule-Based Deep Web Crawler with Indexer -- Chapter 2. Information Classification and Organization using Neuro-Fuzzy Model Event Retrieval. Chapter 3. N-Gram Thesaurus Generation for Query Expansion and Refinement using Tag Term Weight for Information Retrieval -- Chapter 4. Smooth Weighted Color Histogram using Human Visual Perception for CBIR Applications -- Chapter 5. Indexing and Encoding Color Histogram with Bin Overlapped Similarity Measure for Image Retrieval -- Chapter 6. Summary and Conclusion.
520 $a 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.
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