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Abstract

This book offers a helpful starting point in the scattered, rich, and complex body of literature on Mobile Information Retrieval (Mobile IR), reviewing more than 200 papers in nine chapters. Highlighting the most interesting and influential contributions that have appeared in recent years, it particularly focuses on both user interaction and techniques for the perception and use of context, which, taken together, shape much of today's research on Mobile IR. The book starts by addressing the differences between IR and Mobile IR, while also reviewing the foundations of Mobile IR research. It then examines the different kinds of documents, users, and information needs that can be found in Mobile IR, and which set it apart from standard IR. Next, it discusses the two important issues of user interfaces and context-awareness. In closing, it covers issues related to the evaluation of Mobile IR applications. Overall, the book offers a valuable tool, helping new and veteran researchers alike to navigate this exciting and highly dynamic area of research.

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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.