Presents a genetic relevance optimization process performed in an information retrieval system that uses genetic techniques for solving multimodal problems (niching) and query reformulation techniques. Explains that the niching technique allows the process to reach different relevance regions of the document space, and that query reformulations…

Discussion of semantic networks and ranked retrieval focuses on two models, the semantic network model with spreading activation and the vector space model with dot product. Suggests a formal method to analyze the two models in terms of their relative performance in the same universe of objects. (Author/LRW)

Presents a new stemming algorithm based on tree structures that improves relevance in information retrieval by conflation, grouping similar words into a single term. Highlights include the normalization process used in automatic thesaurus construction; theoretical aspects; the normalization algorithm; and experiments with English and Spanish. (LRW)

Presents a preliminary empirical test of a maximum likelihood approach to using relevance data for training information retrieval parameters. Discusses similarities to language models; the unification of document-oriented and query-oriented views; tests on data sets; algorithms and scalability; and the effectiveness of maximum likelihood…

Discusses genetic algorithms in information retrieval, especially for relevance feedback, and evaluates the efficacy of a genetic algorithm with various order-based fitness functions for relevance feedback in a test database. Compares results with the Ide dec-hi method, one of the best traditional methods. (Contains 56 references.) (Author/LRW)

Evaluates the retrieval performance of an algorithm that automatically categorizes medical documents, which consists in assigning an International Code of Disease (ICD) based on well-known information retrieval techniques. Reports on experimental results that tested precision using a database of over 20,000 medical documents. (Author/LRW)

Discusses XML and information retrieval and describes a query language, ELIXIR (expressive and efficient language for XML information retrieval), with a textual similarity operator that can be used for similarity joins. Explains the algorithm for answering ELIXIR queries to generate intermediate relational data. (Author/LRW)

Discussion of finding relevant documents in electronic document collections focuses on an evaluation of the Kea automatic keyphrase extraction algorithm which was developed by members of the New Zealand Digital Library Project. Results are based on evaluations by human assessors of the quality and appropriateness of Kea keyphrases. (Author/LRW)

Discusses vectors used in information retrieval and the algorithms used to manipulate them. Uses the Kohonen neural algorithm and a fuzzification model to perform a fuzzy clustering of document terms to reduce the high dimension and presents results from a test database. (Author/LRW)

Discusses latent semantic indexing (LSI) that would allow search engines to reduce the dimension of the document space by mapping it into a space spanned by conceptual indices. Topics include vector space models; singular value decomposition (SVD); unitary operators; the Haar transform; and new algorithms. (Author/LRW)

Presents the architecture and algorithms behind Matchsimile, an approximate string matching lookup tool designed for extracting person and company names from large texts. Highlights include name formation rules, defining the search problem, system architecture, recognizing pattern words, recognizing whole patterns, and performance. (Author/MES)

Proposes an approach to incorporate term similarity and inverse document frequency into a logical model of information retrieval. Highlights include document representation and matching; incorporating term similarity into the measure of distance; new algorithms for implementation; inverse document frequency; and logical versus classical models of…

Discusses how to improve the quality of Internet search systems and introduces the Ghosts Consensus Method which is free from the drawbacks of digital democracy algorithms and is based on linear programming tasks. Highlights include vector space models; determining relevant documents; and enriching query terms. (LRW)

Reports an approach to automatic thesaurus construction for Chinese documents. Presents an effective Chinese keyword extraction algorithm. Compared to previous studies, this method speeds up the thesaurus generation process drastically. It also achieves a similar percentage level of term relatedness. Includes three tables and four figures.…

Describes EquiX, a search language for XML that combines querying with searching to query the data and the meta-data content of Web pages. Topics include search engines; a data model for XML documents; search query syntax; search query semantics; an algorithm for evaluating a query on a document; and indexing EquiX queries. (LRW)