Experimental assessment of the TARGET adaptive ontology-based Web search framework

Finding relevant information on the Web can be a complex task for most of the users. Although Web search applications are improving, they still need to be more intelligent to adapt to the search domain targeted by users, the evolution of this domain and users' characteristics. In this paper, we present an experimental assessment of the TARGET framework for improving the relevance of the documents when users are searching the Web by using adaptive ontologies. This is done first by introducing the TARGET approach. We will briefly present the used ontologies and their ability to adapt to domain evolution. Then, We detail the TARGET tool used in our experimentations. This includes its architecture, its ability to carry out the ontology adaptation process as well as the way it searches the Web and ranks the returned results. Finally, we discuss the results obtained using the tool through the presentation of our case study devoted to the retrieval of scientific articles.

• Type: Journal
• Year: 2010
• Where: NOTERE
• Authors: Nicolas Guelfi, Cédric Pruski, Chantal Reynaud
• Keywords: Distributed And Parallel Computing, Neural Networks, NOTERE 2010, Ontology Adaptation Process, TARGET Approach, Web Search Applications