Possibilistic Model for Relevance Feedback in Collaborative Information Retrieval
Fatiha Naouar, Lobna Hlaoua, Mohamed Nazih Omri
International Journal of Web Applications, Vol. 4, No. 2, 2012.
DOI: 
Link: http://dline.info/ijwa/fulltext/v4n2/3.pdf
Abstract:
Web information is too heterogeneous that users have difficulties to retrieve their needed information: text, image orvideo. In this context, the collaborative work presents one solution proposed to solve this problem. Collaborative retrieval enables the retrieval historiesâ€™ sharing between users having the same profile across multiple tools such as annotations. We propose in this paper to improve collaborative retrieval performance, considering the annotations as a new source of information describing documents. In our contribution, we propose to apply the relevance feedback to extend the userâ€™s query. So we use a possibilistic approach to extract the relevant terms from annotations given in semi-structured documents returned by collaborative retrieval systems.