Browsing by Author "Bal, Kamal"

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    Content-Oriented XML Retrieval with partial aggregation of relevance factors
    (CERIST, 2009-12) Bal, Kamal; Nouali, Omar
    In this paper, we are interested in content oriented XML information retrieval whose aim is to retrieve not a list of relevant documents, but only fragments of document (XML element) relevant to the user information need. Retrieved XML elements must not only contain relevant information but also be at good level of granularity. Retrieved elements must cover as well as the information need and be focused on this need (does not speak other non relevant topics). The majority of approaches developed in this context consider some relevance factors and aggregate theme globally to have a unique value called rsv (retrieval status value) for each element. We present in this paper an approach of XML retrieval where factor’s aggregation is done not on relevance factor’s values level but on relevance factor’s preference relations which models each factor.
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    Deal with multiplicity and diversity of relevance factors in XML retrieval
    (2010-07-05) Bal, Kamal; Nouali, Omar
    In this paper, we are interested in content oriented XML information retrieval whose aim is to retrieve not a list of relevant documents, but only fragments of document (XML element) relevant to the user information need. Retrieved XML elements must not only contain relevant information but also be at good level of granularity. The coexistence of content and structural information in XML documents makes that multiple and diverse relevance sources condition the selection and the rank of relevant XML element. It is admitted that the consideration of several relevance sources will surely improve quality of results. However, actual XML retrieval approaches consider just some relevance sources and neglect others due to relevance sources heterogeneity. In this paper, we try to identify and classify theses relevance sources and to propose a way to exploit multiple and diverse relevance sources in retrieval process.
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    Deal with multiplicity and diversity of relevance factors in XML retrieval
    (CERIST, 2010) Bal, Kamal; Nouali, Omar
    In this paper, we are interested in content oriented XML information retrieval whose aim is to retrieve not a list of relevant documents, but only fragments of document (XML element) relevant to the user information need. Retrieved XML elements must not only contain relevant information but also be at good level of granularity. The coexistence of content and structural information in XML documents makes that multiple and diverse relevance sources condition the selection and the rank of relevant XML element. It is admitted that the consideration of several relevance sources will surely improve quality of results. However, actual XML retrieval approaches consider just some relevance sources and neglect others due to relevance sources heterogeneity. In this paper, we try to identify and classify theses relevance sources and to propose a way to exploit multiple and diverse relevance sources in retrieval process.
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    Learning to Rank in XML Information Retrieval: Which Feature Improve the Best?
    (IEEE, 2012-08-23) Chaa, Messaoud; Nouali, Omar; Bal, Kamal
    The augmented adoption of XML as the standard format for representing a document structure requires the development of tools to retrieve and rank effectively elements of the XML documents. It’s known that in information retrieval, considering multiple sources of relevance improves information retrieval. In this work some relevance features are defined and used in a learning to rank approach for XML information retrieval. Our aim is to combine theses features to derive good ranking function and show the impact of each feature in the relevance of XML element. Experiments on a large collection from the XML Information Retrieval evaluation campaign (INEX) showed good performance of the approach.