UAM at INEX 2012 relevance feedback track: using a probabilistic method for ranking refinement
Esaú Villatoro-Tello, Christian Sánchez-Sánchez, Héctor Jiménez-Salazar, Wulfrano Arturo Luna-Ramírez, Carlos Rodríguez-Lucatero · 2012
Abstract. This paper describes the system developed by the Language and Reasoning Group of UAM for the Relevance Feedback track of INEX 2012. The presented system focuses on the problem of ranking documents in accordance to their relevance. It is mainly based on the following hy-potheses: (i) current IR machines are able to retrieve relevant documents for most of general queries, but they can not generate a pertinent rank-ing; and (ii) focused relevance feedback could provide more and better elements for the ranking process than isolated query terms. Based on these hypotheses, our participation at INEX 2012 aimed to demonstrate that using some query-related relevance feedback it is possible to improve the final ranking of the retrieved documents. 1