Collaborative information retrieval model based on fuzzy confidence network
Fatiha Naouar, Lobna Hlaoua, Mohamed Nazih Omri · Journal of Intelligent & Fuzzy Systems · 2016
The Web information is too heterogeneous that users have difficulties to retrieve their needed information: text, image or video. Indeed, the collaborative work presents one solution proposed to solve this problem. Collaborative retrieval enables the retrieval histories’ sharing between users havin g the same profile across multiple tools such as annotations. However the user has always problems in choosing the terms to form his query. This paper has proposed collaborative Information Retrieval Model based on Fuzzy Confidence Network. Our approach allows the detection of relevant annotations to a given evidence source. These annotations are next filtered to determine which are relevant to consider them as a new source of information that describes the document used to improve collaborative retrieval performance. We then measure the semantic relationships between terms which will be translated by the propagation of confidence. Experiments were conducted on different queries, showing very encouraging results that could reach an improvement rate.