Search (8 results, page 1 of 1)

  • × author_ss:"Savoy, J."
  • × theme_ss:"Hypertext"
  1. Savoy, J.: Searching information in legal hypertext systems (1993/94) 0.00 
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    Abstract
    Hypertext may represent a new paradigm capable of exploring legal sources within which links are established according to pertinent relationships found between statute texts and case law. However, to discover relvant information in such a network, a browsing mechanism is not enough when faced with a large column of texts. Describes a new retrieval model where documents are represented according to both their content and relationship with other sources of information
    Type
    a
  2. Savoy, J.: ¬A new probabilistic scheme for information retrieval in hypertext (1995) 0.00 
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    Abstract
    The aim of probabilistic models is to define a retrieval strategy within which documents can be optimally ranked according to their relevance probability with respect to a given request. Presents a study which suggests representing documents not only by index term vendors, as proposed by previous probabilistic models but also by considering relevance hypertext links. To enhance retrieval effectiveness, the learning retrieval scheme should modify the weight assigned to each indexing terms, the importance attached to each search term, and the relationships between documents. Evaluation of the proposed retrieval scheme with a hypertext based on the CACM test collection which includes 3.204 documents and the CISI corpus (1,460 documents), yields interesting results on the retrieval effectiveness of this approach
    Type
    a
  3. Savoy, J.: ¬A learning scheme for information retrieval in hypertext (1994) 0.00 
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    Abstract
    In proposing a searching strategy well suited to the hypertext environment, we have considered four criteria: (1) the retrieval scheme should be integrated into a large hypertext environment; (2) the retrieval process should be operable with an unrestricted text collection; (3) the processing time should be reasonable; and (4) the system should be capable of learning in order to improve its retrieval effectiveness
    Type
    a
  4. Savoy, J.: Bayesian inference networks and spreading activation in hypertext systems (1992) 0.00 
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  5. Savoy, J.; Desbois, D.: Information retrieval in hypertext systems (1991) 0.00 
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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
    Type
    a
  6. Savoy, J.: ¬An extended vector-processing scheme for searching information in hypertext systems (1996) 0.00 
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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)
    Type
    a
  7. Picard, J.; Savoy, J.: Enhancing retrieval with hyperlinks : a general model based on propositional argumentation systems (2003) 0.00 
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    Abstract
    Fast, effective, and adaptable techniques are needed to automatically organize and retrieve information an the ever-increasing World Wide Web. In that respect, different strategies have been suggested to take hypertext links into account. For example, hyperlinks have been used to (1) enhance document representation, (2) improve document ranking by propagating document score, (3) provide an indicator of popularity, and (4) find hubs and authorities for a given topic. Although the TREC experiments have not demonstrated the usefulness of hyperlinks for retrieval, the hypertext structure is nevertheless an essential aspect of the Web, and as such, should not be ignored. The development of abstract models of the IR task was a key factor to the improvement of search engines. However, at this time conceptual tools for modeling the hypertext retrieval task are lacking, making it difficult to compare, improve, and reason an the existing techniques. This article proposes a general model for using hyperlinks based an Probabilistic Argumentation Systems, in which each of the above-mentioned techniques can be stated. This model will allow to discover some inconsistencies in the mentioned techniques, and to take a higher level and systematic approach for using hyperlinks for retrieval.
    Type
    a
  8. Savoy, J.: Effectiveness of information retrieval systems used in a hypertext environment (1993) 0.00 
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