Discussion of XML, information retrieval, precision, and recall focuses on a retrieval technique that adopts the similarity measure of the vector space model, incorporates the document structure, and supports structured queries. Topics include a query model based on tree matching; structured queries and term-based ranking; and term frequency and…

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)

Introduces the concept of relevance as viewed and applied in the context of IR (information retrieval) evaluation by presenting an overview of the multidimensionality and dynamic nature of the concept. Topics include classes and types of relevance; relevance criteria; degrees of relevance; levels of relevance; situational relevance; and…

Discusses information retrieval techniques used on the World Wide Web. Topics include machine learning in information extraction; relevance feedback; information filtering and recommendation; text classification and text clustering; Web mining, based on data mining techniques; hyperlink structure; and Web size. (LRW)

Proposes an effective term suggestion approach to interactive Web searches. Explains a log-based approach to relevant term extraction and term suggestion where relevant terms suggested for a user query are those that co-occur in similar query sessions from search engine logs rather than in the retrieved documents. (Author/LRW)

Presents five user experiments on incorporating behavioral information into the relevance feedback process in information retrieval, concentrating on ranking terms for query expansion and selecting new terms to add to the user's query. Topics include term ranking and user behavior; incorporating user behavior into term ranking; and user behavior…

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…

Proposes a theoretical framework called NLPIR that integrates natural language processing (NLP) into information retrieval (IR) based on the assumption that there exists representation distance between queries and documents. Discusses problems in traditional keyword-based IR, including relevance, and describes some existing NLP techniques.…

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)

Presents the application of a knowledge visualization tool, VxInsight[R], to enable domain analysis for science and technology management. Uses data mining from sources of bibliographic information to define subsets of relevant information and discusses citation mapping, text mapping, and journal mapping. (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)

Reports on an experiment that examined whether thesaurus terms, related to query in a specified semantic way (synonyms, narrower terms, related terms, or broader terms) could be identified as having a more positive impact on retrieval effectiveness when added to a query through automatic query expansion. (Contains 54 references.) (Author/LRW)

Content-based image retrieval is based on the idea of extracting visual features from images and using them to index images in a database. Proposes similarity measures and an indexing algorithm based on information theory that permits an image to be represented as a single number. When used in conjunction with vectors, this method displays…