Presents a new method to improve the performance of query processing in a spatial database. Experiments demonstrated that performance of database systems can be improved because both the number of objects accessed and number of objects requiring detailed inspection are much less than those in the previous approach. (AEF)

Describes the design of an information retrieval system that permits the personalization of a search by developing a user profile in order to reduce noise and increase the number of relevant items retrieved. The preorientation system is explained and an example using full-text natural language processing tools is presented. (Author/LRW)

Describes the University of California at Berkeley's participation in the TREC (Text Retrieval Conference) interactive track experiments. Highlights include results of searches on two systems, Cheshire II and ZPRISE; system design goals and implementation; precision and recall results; search questions by topic and system; and results of…

Demonstrates that if the similarity function of a retrieval system leads to a (pseudo-) metric, the retrieval, similarity and Everett-Cater metric topology coincide and are different from the discrete topology; this is the case if documents are represented by lists, using the Jaccard similarity measure. The corresponding metric is the…

This study uses the human approach to examine the sources and effectiveness of search terms selected during 40 mediated interactive database searches and focuses on determining the retrieval effectiveness of search terms identified by users and intermediaries from retrieved items during term relevance feedback. (Author/JKP)

Describes SALOMON (Summary and Analysis of Legal texts for Managing Online Needs), a system which automatically summarizes Belgian criminal cases to improve access to court decisions. Highlights include a text grammar represented as a semantic network; automatic abstracting; knowledge acquisition and representation; parsing; evaluation, including…

Discusses intelligent filtering systems and describes work in the INFOS (Intelligent News Filtering Organizational System) project designed to automatically categorize data as relevant or irrelevant based on user interests. The filtering is performed by combining keyword-based hill climbing, knowledge-based conceptual representation via WordNet,…