How to find the nearest by evaluating only few? Clustering techniques used to improve the efficiency of an Information Retrieval sytem based on Distributional Semantics

摘要

The first objective of this contribution is to give a description of our textual information retrieval system based on distributional semantics. The central idea of the approach is to represent the retrievable units and the user queries in a unified way as projections in a vectory space of pertinent terms. The projections are derived from a co-occurrence matrix computed on large reference (textual) corpora collecting the distributional semantic information. A similarity computation based on the cosine measure is then used to characterize the semantic proximity between queries and documents.