Search (5 results, page 1 of 1)

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Abstract

The article describes the project an music information retrieval that has been carried out at the University of Padova, Italy. The research work has been characterized by the synergy of the modular integration of sound techniques of melody processing and of statistical information retrieval. After illustrating the background from which the project has originated, we describe the complete process, from methodology design through evaluation and system implementation. Conclusions, impacts an research in music information retrieval, and future directions are also described.

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Abstract

Although most of the queries submitted to search engines are composed of a few keywords and have a length that ranges from three to six words, more than 15% of the total volume of the queries are verbose, introduce ambiguity and cause topic drifts. We consider verbosity a different property of queries from length since a verbose query is not necessarily long, it might be succinct and a short query might be verbose. This paper proposes a methodology to automatically detect verbose queries and conditionally modify queries. The methodology proposed in this paper exploits state-of-the-art classification algorithms, combines concepts from a large linguistic database and uses a topic gisting algorithm we designed for verbose query modification purposes. Our experimental results have been obtained using the TREC Robust track collection, thirty topics classified by difficulty degree, four queries per topic classified by verbosity and length, and human assessment of query verbosity. Our results suggest that the methodology for query modification conditioned to query verbosity detection and topic gisting is significantly effective and that query modification should be refined when topic difficulty and query verbosity are considered since these two properties interact and query verbosity is not straightforwardly related to query length.

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Abstract

Describes the design and implementation of TACHIR, a tool for the automatic construction of hypertexts for information retrieval. Through the use of an authoring methodology employing a set of well known information retrieval techniques, TACHIR automatically builds up a hypertext from a document collection. The structure of the hypertext reflects a 3 level conceptual model which enables navigation among documents, index terms, and concepts using automatically determined links. The hypertext is implemented using the HTML language. It can be distributed on different sites and different machines over the Internet, and it can be navigated using WWW interfaces

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Abstract

Textbooks are more available in electronic format now than in the past. Because textbooks are typically large, the end user needs effective tools to rapidly access information encapsulated in textbooks stored in digital libraries. Statistical similarity-based links among hypertextbooks are a means to provide those tools. In this paper, the design and the implementation of a tool that generates networks of links within and across hypertextbooks through a completely automatic and unsupervised procedure is described. The design is based an statistical techniques. The overall methodology is presented together with the results of a case study reached through a working prototype that shows that connecting hyper-textbooks is an efficient way to provide an effective retrieval capability.