Advanced Topics in Information Retrieval by Maristella Agosti (auth.), Massimo Melucci, Ricardo PDF

By Maristella Agosti (auth.), Massimo Melucci, Ricardo Baeza-Yates (eds.)

ISBN-10: 3642209459

ISBN-13: 9783642209451

Information retrieval is the technological know-how serious about the powerful and effective retrieval of records ranging from their semantic content material. it truly is hired to satisfy a few info want from a great number of electronic files. Given the ever-growing quantity of files on hand and the heterogeneous info constructions used for garage, info retrieval has lately confronted and tackled novel applications.

In this e-book, Melucci and Baeza-Yates current a wide-spectrum representation of modern examine ends up in complex components concerning details retrieval. Readers will locate chapters on e.g. aggregated seek, electronic advertisements, electronic libraries, discovery of junk mail and evaluations, info retrieval in context, multimedia source discovery, quantum mechanics utilized to details retrieval, scalability demanding situations in internet se's, and interactive info retrieval evaluate. All chapters are written by means of famous researchers, are thoroughly self-contained and finished, and are complemented through an built-in bibliography and topic index.

With this option, the editors give you the latest survey of subject matters often no longer addressed extensive in conventional (text)books on info retrieval. The presentation is meant for a large viewers of individuals attracted to info retrieval: undergraduate and graduate scholars, post-doctoral researchers, teachers, and business researchers.

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Lateral browsing for an image “from behind the pitcher in a baseball game . . ” . . . . . . . . . . . . . Alternative ways to browse for images “from behind the pitcher . . ” . . . . . . . . . . . . . . . Geo-temporal browsing in action . . . . . . . . . Ambisense model of context . . . . . . . . . . . Google’s Related searches . . . . . . . . . . . Keywords in context . . . . . . . . . . . .

Radial visualisation . . . . . . . . . . . . . Visual search for images of dark doors starting with a bright-door example . . . . . . . . . . . . . . . . A relevance feedback . . . . . . . . . . . . Lateral browsing for an image “from behind the pitcher in a baseball game . . ” . . . . . . . . . . . . . Alternative ways to browse for images “from behind the pitcher . . ” . . . . . . . . . . . . . . . Geo-temporal browsing in action .

Cambazoglu and R. Baeza-Yates Given the very high rate of growth in the number of web pages and the number of issued queries, the scalability of large-scale search engines becomes a real challenge. Increasing the investment on hardware in order to cope with this growth has certain financial implications for search engine companies. Therefore, designing efficient and scalable search systems is crucial to reduce the running cost of web search engines. In this chapter, we provide a survey of the scalability challenges in designing a large-scale web search engine.

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Advanced Topics in Information Retrieval by Maristella Agosti (auth.), Massimo Melucci, Ricardo Baeza-Yates (eds.)


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