Textual and Visual Information Retrieval using Query Refinement and Pattern Analysis

• Κύριοι συγγραφείς: Shaila, S.G (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut), Vadivel, A. (http://id.loc.gov/vocabulary/relators/aut)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Singapore : Springer Singapore : Imprint: Springer, 2018.
• Έκδοση: 1st ed. 2018.
• Θέματα: Information storage and retrieval.; Multimedia information systems.; Data mining.; Pattern recognition.; Information Storage and Retrieval.; Multimedia Information Systems.; Data Mining and Knowledge Discovery.; Pattern Recognition.
• Φυσική περιγραφή: XXVI, 123 p. 53 illus., 34 illus. in color. online resource.
• ISBN: 9789811325595
• DOI: 10.1007/978-981-13-2559-5

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.