Fuzzy Term Proximity With Boolean Queries at 2006 TREC Terabyte Task

We report here the results of fuzzy term proximity method applied to Terabyte Task. Fuzzy proxmity main feature is based on the idea that the closer the query terms are in a document, the more relevant this document is. With this principle, we have a high precision method so we complete by these obtained with Zettair search engine default method (dirichlet). Our model is able to deal with Boolean queries, but contrary to the traditional extensions of the basic Boolean IR model, it does not explicitly use a proximity operator because it can not be generalized to nodes. The fuzzy term proximity is controlled with an influence function. Given a query term and a document, the influence function associates to each position in the text a value dependant of the distance of the nearest occurence of this query term. To model proximity, this function is decreasing with distance. Different forms of function can be used: triangular, gaussian etc. For practical reasons only functions with finite support were used. The support of the function is limited by a constant called k. The fuzzy term proximity functions are associated to every leaves of the query tree. Then fuzzy proximities are computed for every nodes with a post-order tree traversal. Given the fuzzy proximities of the sons of a node, its fuzzy proximity is computed, like in the fuzzy IR models, with a mimimum (resp. maximum) combination for conjunctives (resp. disjunctives) nodes. Finally, a fuzzy query proximity value is obtained for each position in this document at the root of the query tree. The score of this document is the integration of the function obtained at the tree root. For the experiments, we modify Lucy (version 0.5.2) to implement our matching function. Two query sets are used for our runs. One set is manually built with the title words (and sometimes some description words). Each of these words is OR’ed with its derivatives like plurals for instance. Then the OR nodes obtained are AND’ed at the tree root. An other automatic query sets is built with an AND of automatically extracted terms from the title field. These two query sets are submitted to our system with two values of k: 50 and 200. The two corresponding query sets with flat queries are also submitted to zettair search engine.