From fusion to re-ranking: a semantic approach

Annalina Caputo, Pierpaolo Basile, Giovanni Semeraro

Abstract: A number of works have shown that the aggregation of several Information Retrieval (IR) systems works better than each system working individually. Nevertheless, early investigation in the context of CLEF Robust-WSD task, in which semantics is involved, showed that aggregation strategies achieve only slight improvements. This paper proposes a re-ranking approach which relies on inter-document similarities. The novelty of our idea is twofold: the output of a semantic based IR system is exploited to re-weigh documents and a new strategy based on Semantic Vectors is used to compute inter-document similarities.