Search (6 results, page 1 of 1)

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Abstract

In most commercial online systems, the retrieval system is based on the Boolean model and its inverted file organization. Since the investment in these systems is so great and changing them could be economically unfeasible, this article suggests a new ranking scheme especially adapted for hypertext environments in order to produce more effective retrieval results and yet maintain the effectiveness of the investment made to date in the Boolean model. To select the retrieved documents, the suggested ranking strategy uses multiple sources of document content evidence. The proposed scheme integrates both the information provided by the index and query terms, and the inherent relationships between documents such as bibliographic references or hypertext links. We will demonstrate that our scheme represents an integration of both subject and citation indexing, and results in a significant imporvement over classical ranking schemes uses in hybrid Boolean systems, while preserving its efficiency. Moreover, through knowing the nearest neighbor and the hypertext links which constitute additional sources of evidence, our strategy will take them into account in order to further improve retrieval effectiveness and to provide 'good' starting points for browsing in a hypertext or hypermedia environement

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Abstract

The emphasis in most hypertext systems is on the navigational methods, rather than on the global document retrieval mechanisms. When a search mechanism is provided, it is often restricted to simple string matching or to the Boolean model (as an alternate method). proposes a retrieval mechanism using Bayesian inference networks. The main contribution of this approach is the automatic construction of this network using the expected mutual information measure to build the inference tree, and using Jaccard's formula to define fixed conditional probability relationships

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Abstract

In most hypertext systems, information retrieval techniques emphasize browsing or navigational methods which are not thorough enough to find all relevant material, especially when the number of nodes and/or links becomes very large. Reviews the main query-based search techniques currently used in hypertext environments. Explains the experimental methodology. Concentrates on the retrieval effectiveness of these retrieval strategies. Considers ways of improving search effectiveness

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Abstract

When searching information in a hypertext is limited to navigation, it is not an easy task, especially when the number of nodes and/or links becomes very large. A query based access mechanism must therefore be provided to complement the navigational tools inherent in hypertext systems. Most mechanisms currently proposed are based on conventional information retrieval models which consider documents as indepent entities, and ignore hypertext links. To promote the use of other information retrieval mechnaisms adapted to hypertext systems, responds to the following questions; how can we integrate information given by hypertext links into an information retrieval scheme; are these hypertext links (and link semantics) clues to the enhancement of retrieval effectiveness; if so, how can we use them. 2 solutions are: using a default weight function based on link tape or assigning the same strength to all link types; or using a specific weight for each particular link, i.e. the level of association or a similarity measure. Proposes an extended vector processing scheme which extracts additional information from hypertext links to enhance retrieval effectiveness. A hypertext based on 2 medium size collections, the CACM and the CISI collection has been built. The hypergraph is composed of explicit links (bibliographic references), computed links based on bibliographic information, or on hypertext links established according to document representatives (nearest neighbour)

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