Search (3 results, page 1 of 1)

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Abstract

For introductory information retrieval courses at the undergraduate and graduate level in computer science, information science and computer engineering departments. Written by a leader in the field of information retrieval, Search Engines: Information Retrieval in Practice, is designed to give undergraduate students the understanding and tools they need to evaluate, compare and modify search engines. Coverage of the underlying IR and mathematical models reinforce key concepts. The book's numerous programming exercises make extensive use of Galago, a Java-based open source search engine. SUPPLEMENTS / Extensive lecture slides (in PDF and PPT format) / Solutions to selected end of chapter problems (Instructors only) / Test collections for exercises / Galago search engine

LCSH

Search engines / Programming

Subject

Search engines / Programming

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Content

Inhalt Collaborating to search effectively in different searcher modes through cues and specialty search / Naresh Kumar Agarwal and Danny C.C. Poo -- Collaborative querying using a hybrid content and results-based approach / Chandrani Sinha Ray ... [et al.] -- Collaborative classification for group-oriented organization of search results / Keiichi Nakata and Amrish Singh -- A case study of use-centered descriptions : archival descriptions of what can be done with a collection / Richard Butterworth -- Metadata for social recommendations : storing, sharing, and reusing evaluations of learning resources / Riina Vuorikari, Nikos Manouselis, and Erik Duval -- Social network models for enhancing reference-based search engine rankings / Nikolaos Korfiatis ... [et al.] -- From PageRank to social rank : authority-based retrieval in social information spaces / Sebastian Marius Kirsch ... [et al.] -- Adaptive peer-to-peer social networks for distributed content-based Web search / Le-Shin Wu ... [et al.] -- The ethics of social information retrieval / Brendan Luyt and Chu Keong Lee -- The social context of knowledge / Daniel Memmi -- Social information seeking in digital libraries / George Buchanan and Annika Hinze -- Relevant intra-actions in networked environments / Theresa Dirndorfer Anderson -- Publication and citation analysis as a tool for information retrieval / Ronald Rousseau -- Personalized information retrieval in a semantic-based learning environment / Antonella Carbonaro and Rodolfo Ferrini -- Multi-agent tourism system (MATS) / Soe Yu Maw and Myo-Myo Naing -- Hybrid recommendation systems : a case study on the movies domain / Konstantinos Markellos ... [et al.].

LCSH

Web search engines

Subject

Web search engines

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Abstract

Class-tested and coherent, this textbook teaches information retrieval, including web search, text classification, and text clustering from basic concepts. Ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students. Slides and additional exercises are available for lecturers. - This book provides what Salton and Van Rijsbergen both failed to achieve. Even more important, unlike some other books in IR, the authors appear to care about making the theory as accessible as possible to the reader, on occasion including short primers to certain topics or choosing to explain difficult concepts using simplified approaches. Its coverage [is] excellent, the quality of writing high and I was surprised how much I learned from reading it. I think the online resources are impressive.

Content

Inhalt: Boolean retrieval - The term vocabulary & postings lists - Dictionaries and tolerant retrieval - Index construction - Index compression - Scoring, term weighting & the vector space model - Computing scores in a complete search system - Evaluation in information retrieval - Relevance feedback & query expansion - XML retrieval - Probabilistic information retrieval - Language models for information retrieval - Text classification & Naive Bayes - Vector space classification - Support vector machines & machine learning on documents - Flat clustering - Hierarchical clustering - Matrix decompositions & latent semantic indexing - Web search basics - Web crawling and indexes - Link analysis Vgl. die digitale Fassung unter: http://nlp.stanford.edu/IR-book/pdf/irbookprint.pdf.