New PDF release: Advances in Information Retrieval: Recent Research from the

By W. Bruce Croft (auth.), W. Bruce Croft (eds.)

ISBN-10: 0306470195

ISBN-13: 9780306470196

ISBN-10: 0792378121

ISBN-13: 9780792378129

The middle for clever info Retrieval (CIIR) used to be shaped within the laptop technological know-how division ofthe collage ofMassachusetts, Amherst in 1992. The middle aid for the guts got here from a countrywide technological know-how Foun- tion State/Industry/University Cooperative learn Center(S/IUCRC) supply, even though there were a giant info retrieval (IR) examine crew for over 10 years ahead of that furnish. Thebasic objective ofthese facilities is to mix uncomplicated examine, utilized learn, and expertise move. The CIIR has been winning in every one of those components, in that it has produced over 270 study papers, has been interested by many winning executive and collaborations, and has had an important position in high-visibility websites and start-ups. due to those efforts, the CIIR has turn into recognized the world over as one of many major learn teams within the sector of knowledge retrieval. The CIIR specializes in examine that ends up in more beneficial and effective entry and discovery in huge, heterogeneous, dispensed, textual content and multimedia databases. The scope of the paintings that's performed within the CIIR is wide and is going considerably past “traditional” components of data retrieval equivalent to retrieval types, cross-lingual seek, and automated question growth. The examine comprises either low-level structures matters equivalent to the layout of protocols and architectures for allotted seek, in addition to extra human-centered subject matters equivalent to person interface layout, visualization and information mining with textual content, and multimedia retrieval.

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Communications of the ACM, 18:613–620. Saracevic, T. and Kantor, P. (1988). A study of information seeking and retrieving. Part 111. Searchers, searches, overlap. Journal of the American Society for Information Science, 39(3): 197–216. Schneiderman, H. and Kanade, T. (1998). Probabilistic modeling of local appearance and spatial relationships for object recognition. In Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR), pages 45–51. Small, H. (1973). Co-citation in scientific literature: A new measure of the relationship between two documents.

Greiff, W. (1999). Maximum entropy, weight of evidence, and information retrieval. PhD thesis, Computer Science Department, University of Massachusetts. , and Turtle, H. (1997). Computationally tractable probabilistic modeling of Boolean operators. In Proceedings of the 20th ACM SIGIR Conference on Research and Development in Information Retrieval, pages 119–128. Haines, D. (1996). Adaptive query modification in a probabilistic information retrieval model. PhD thesis, Computer Science Department, University of Massachusetts.

If the research is successful, robust improvement to previous retrieval practice is realized and a better understanding of what is needed for effective retrieval performance results. Even in the absence of improved retrieval performance, new insight is often gained into the nature of the IR problem. Much of the progress of information retrieval is due to research of this nature. The a priori modeling approach adopts a more theoretical, formal line of attack. In this case, the researcher attempts to formalize her intuitions in the form of a priori assumptions, and a theory, typically a probabilistic theory, of information retrieval is developed.

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Advances in Information Retrieval: Recent Research from the Center for Intelligent Information Retrieval by W. Bruce Croft (auth.), W. Bruce Croft (eds.)

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