Estimation of Information Sources Pertinence in Mediated Data Integration Systems

Solutions to efficient fuzzy queries processing in decentralized environments were mostly proposed for a relational databases context. Moreover, most of related works process fuzzy queries without considering cooperation between distributed sources. To overcome these drawbacks, we propose a two-step method able to determine as efficiently as possible the set of rewritings that are likely to provide satisfactory answers to a conjunctive fuzzy query submitted to the mediated schema managing distributed and heterogeneous information sources. In the first step, an attempt is made to associate each query rewriting with histograms summarizing the distributions, in the query result, of the attributes to which fuzzy conditions are related. In the second step, histograms associated to large-scale distributed heterogeneous data sources are used to estimate the score of query rewritings. Score associated to each rewriting determines how closely the rewriting matches the user query and whether it is interesting to process this rewriting or not.