Information retrieval systems typically weight the importance of search terms according to document and collection statistics (such as by using tf \Theta idf scores, where less common terms are given higher weight). We consider here the scenario where a user can express her own subjective weighting of the importance of the terms that form the query on top of the systemgenerated weighting, and show how this should modify the relevance scores of documents. This has been allowed before, but only by ad hoc heuristics. We give the first principled method for taking into account the user's subjective weighting of the importance of query terms. Our method is based on an approach by Fagin and Wimmers, that gives a simple formula derived from any existing "unweighted" ranking function. A naive application of the formula would require issuing as many distinct queries as there are terms in the query (search terms), thus damaging the response time of the retrieval. We explain here how to...

this paper is organized as follows: Section 2 describes KA in general. In Section 3 we describe how KA was used for the topic distillation experiment. Section 4 describes the obtained results. Section 5 concludes

XML documents represent a middle range between unstructured data such as textual documents and fully structured data encoded in databases. Typically, information retrieval techniques are used to support search on the "unstructured" end of this scale, while database techniques are used for the other end. To date, most of the work on XML query and search has stemmed from the structured side and is strongly inspired by database techniques. We describe here an approach that originates from the "unstructured" end and is based on augmentation of information retrieval techniques. It is specifically targeted to support the information needs of end-users, more specifically user friendliness via an intuitive querying mechanism, and ranking of results for approximate needs. We describe our query format and ranking mechanism and demonstrate how it was used to run the INEX topics.

Abstract Although software reuse presents clear advantages for programmer productivity and code reliability, it is not practiced enough. One of the reasons for the only moderate success of reuse is the lack of software libraries that facilitate the actual locating and understanding of reusable components. This paper describes a technology for automatically assembling large software libraries that promote software reuse by helping the user locate the components closest to her/his needs. Software libraries are automatically assembled from a set of unorganized components by using information retrieval techniques. The construction of the library is done in two steps. First, attributes are automatically extracted from natural language documentation by using a new indexing scheme based on the notions of lexical affinities and quantity of information. Then, a hierarchy for browsing is automatically generated using a clustering technique that draws only on the information provided by the attributes. Thanks to the free-text indexing scheme, tools following this approach can accept free-style natural language queries. This technology has been implemented in the system, which has been applied to construct an organized library of utilities. An experiment was conducted in order to evaluate the retrieval effectiveness of as compared to a hypertext library system for 3 on the IBM RISC System/6000 series. We followed the usual evaluation procedure used in information retrieval, based upon recall and precision measures, and determined that our system performs 15 % better on a random test set, while being