Titlebook: Distributed Multimedia Information Retrieval; SIGIR 2003 Workshop Jamie Callan,Fabio Crestani,Mark Sanderson Conference proceedings 2004 S

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0302-9743 the topic to round off coverage of the core issues. The papers are devoted to recent research on the design and implementation of methods and tools for resource discovery, resource description, resource selection, data fusion, and user interaction..978-3-540-20875-4978-3-540-24610-7Series ISSN 0302-9743 Series E-ISSN 1611-3349

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The Commonwealth of the Bahamaso one or more formats such that each library can process the query. Finally, data fusion is used to gather all retrieved documents and conveniently arrange them for presentation to the user..In this paper, we introduce an original framework for collection fusion in the context of image databases. In

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Harvesting: Broadening the Field of Distributed Information Retrievalfor distributed IR. We highlight the use of the Open Archives Initiative Protocol for Metadata Harvesting, illustrating its use in three projects: OAD, NDLTD, and CITIDEL. We explain how traditional services can be extended in a user-centered fashion, providing details of our new: ESSEX search engin

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Using Query Probing to Identify Query Language Features on the Webically probes the resource’s search interface with a set of selected probe queries and analyzes the returned pages to recognize supported query language features. The automatic discovery assumes that the number of matches a server returns for a submitted query is available on the first result page.

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Decision-Theoretic Resource Selection for Different Data Types in MINDies a query should be routed. In this paper, we describe a novel technique that is used in the MIND project. Our approach, decision-theoretic framework (DTF), differs from existing algorithms like CORI in two ways: It computes a selection which minimises the overall costs (e.g. retrieval quality, ti

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Distributed Web Search as a Stochastic Gameetasearchers distribute user’s queries to only the most suitable search engines. Previous research has investigated methods for engine selection and merging of search results (i.e. performance improvements from the user’s perspective). We focus instead on performance from the service provider’s poin

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