Possibility and necessity measures for relevance assessment

The major question raised in information retrieval on semi-structured documents relates to the manner of effectively handling the structure and the contents of the document for better answering the user's needs. These needs can be formulated by queries composed of only key words or key words and structural constraints. In this paper, we are interested in Information Retrieval in semi-structured document like XML. For these purposes, we present a model for the semi-structured information retrieval, based on the possibilistic networks. The document - elements and elements - terms relations are modelled by measures of possibility and necessity. In this model, the user's query starts a process of propagation to recover documents or portions of documents necessarily or at least possibly relevant. An example of such a research is proposed in order to illustrate the presented approach.

[1]  L. Zadeh.  Fuzzy sets as a basis for a theory of possibility , 1999 .

[2]  Norbert Fuhr.  Language Models and Uncertain Inference in Information Retrieval , 2001 .

[3]  Stephen E. Robertson,et al.  Some simple effective approximations to the 2-Poisson model for probabilistic weighted retrieval , 1994, SIGIR '94.

[4]  Mounia Lalmas,et al.  Dempster-Shafer's theory of evidence applied to structured documents: modelling uncertainty , 1997, SIGIR '97.

[5]  Mohand Boughanem,et al.  A Model for Information Retrieval Based on Possibilistic Networks , 2005, SPIRE.

[6]  Karen Sauvagnat.  Mod`ele flexible pour la Recherche d'Information dans des corpus de documents semi-structur´es , 2005 .

[7]  Mounia Lalmas,et al.  Advances in XML Information Retrieval: Third International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2004, Dagstuhl Castle, ... 2004 (Lecture Notes in Computer Science) , 2005 .

[8]  Norbert Fuhr,et al.  Applying the Divergence from Randomness Approach for Content-Only Search in XML Documents , 2004, ECIR.

[9]  Gerard Salton,et al.  The SMART Retrieval System—Experiments in Automatic Document Processing , 1971 .

[10]  Didier Dubois,et al.  Possibilistic logic bases and possibilistic graphs , 1999, UAI.

[11]  Gabriella Kazai,et al.  The Accessibility Dimension for Structured Document Retrieval , 2002, ECIR.

[12]  M. de Rijke,et al.  An Element-based Approach to XML Retrieval , 2004 .

[13]  Maarten de Rijke,et al.  XML retrieval: what to retrieve? , 2003, SIGIR '03.

[14]  Benjamin Piwowarski,et al.  Bayesian Networks and INEX , 2002, INEX Workshop.

[15]  Gerard Salton,et al.  Research and Development in Information Retrieval , 1982, Lecture Notes in Computer Science.

[16]  Norbert Fuhr,et al.  Content-oriented XML retrieval with HyRex , 2002, INEX Workshop.

[17]  Christian Borgelt,et al.  Possibilistic Graphical Models , 2000, Computational Intelligence in Data Mining.

[18]  Paul Ogilvie,et al.  Using Language Models for Flat Text Queries in XML Retrieval , 2003 .