Textual and Visual Information Retrieval using Query Refinement and Pattern Analysis
Başlık:
Textual and Visual Information Retrieval using Query Refinement and Pattern Analysis
Yazar:
Shaila, S.G. author.
ISBN:
9789811325595
Yazar:
Edisyon:
1st ed. 2018.
Fiziksel Niteleme:
XXVI, 123 p. 53 illus., 34 illus. in color. online resource.
İçindekiler:
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.
Özet:
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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Elektronik Erişim:
https://doi.org/10.1007/978-981-13-2559-5