Handling uncertainty in semantic information retrieval process Chkiwa Mounira 1 , Jedidi Anis 1 and Faiez Gargouri 1 1 Multimedia, InfoRmation systems and Advanced Computing Laboratory Sfax University, Tunisia m.chkiwa@gmail.com, jedidianis@gmail.com, faiez.gargouri@isimsf.rnu.tn Abstract. This position paper proposes a collaboration method between Seman- tic Web and Fuzzy Logic aiming to handle uncertainty in the information re- trieval process in order to cover more relevant items in result of search process. The collaboration method employs OWL ontology in query enhancement, RDF in annotation process and fuzzy rules in ranking enhancement. 1 Introduction In the information retrieval process, there are returned documents which are relevant to the query but they focus in addition of query main interest on others additional topics. To deal with this imprecision we propose to valorize in the ranking process relevant documents which deal mainly with query themes. Another source of impreci- sion in the search process is the user queries; we propose to enhance it in order to come near the intention of the user. This paper is organized as follows: in the next section we present our proposition to enhance the query background expression then we explain how Semantic Web and Fuzzy Logic collaborate to enhance ranking process. In Section 3, we present some related works and Section 4 concludes the paper. 2 Handling uncertainty by semantic/fuzzy collaboration 2.1 The semantic/fuzzy query enhancement A main cause of uncertainty in the information retrieval process comes from the us- er’s queries. In order to return more relevant results, the information retrieval system has to indentify the user’s intention behind the query. To do it, we propose to enhance user queries by adding semantically related terms. In this purpose, we use the Web Ontology Language OWL and then we employ some fuzzy rules in order to weight up the query terms importance. In Figure 1, we present our semantic/fuzzy query en- hancement.