Describes a test collection that was developed as a multi-purpose testbed for experiments on the Web in distributed information retrieval, hyperlink algorithms, and conventional ad hoc retrieval. Discusses inter-server connectivity, integrity of server holdings, inclusion of documents related to a wide spread of likely queries, and distribution of…

Discusses the role of search engines in Web usability and analyzes and evaluates the retrieval effectiveness of various indexing and searching strategies on a new Web text collection. Highlights include preprocessing techniques that might improve retrieval effectiveness; and hyperlinks as useful sources of evidence in improving retrieval…

Proposes a fuzzy multiset model for information clustering with application to information retrieval on the World Wide Web. Highlights include search engines; term clustering; document clustering; algorithms for calculating cluster centers; theoretical properties concerning clustering algorithms; and examples to show how the algorithms work.…

Reviews Web-search tools available to librarians. Discusses the Clever project, (part of the Computer Science Principles and Methodologies Department at the IBM Almaden Research Center, Silicon Valley, California), an algorithm that finds authoritative sources on the Web; Google technology, based on links between Web pages; Ask Jeeves, a…

Describes SWEAR (Systematic Weighting and Ranking), a powers-of-two algorithm that can be used for searching the World Wide Web or any large database that automatically creates discrete, well-defined result sets and displays them in decreasing order of likely relevance. Also discusses fuzzy sets. (Author/LRW)

Discusses the use of link structure analysis in World Wide Web information retrieval and in retrieval and ranking algorithms of search engines. Presents two techniques which bias co-citation based link analyses towards favorable Web pages and away from undesired pages, and are then integrated into existing link-analyzing algorithms. (Author/LRW)

Discusses the collection fusion problem of image databases, concerned with retrieving relevant images by content based retrieval from image databases distributed on the Web. Focuses on a metaserver which selects image databases supporting similarity measures and proposes a new algorithm which exploits a probabilistic technique using Bayesian…

Presents an overview of machine learning research and reviews methods used for evaluating machine learning systems. Ways that machine-learning algorithms were used in traditional information retrieval systems in the "pre-Web" era are described, and the field of Web mining and how machine learning has been used in different Web mining…

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)

Describes WebACE, the architecture of a client-side agent that explores and classifies Web documents in clusters automatically and discusses the details of the algorithms within its key components. Highlights principal direction divisive partitioning (PDDP), a scalable hierarchical clustering algorithm; compares it to other clustering methods; and…

Presents a World Wide Web page model that reacts to pre-defined events and performs actions like "prefetching" automatically. Discusses the active index, conceptual page model; design of the client system, status of the current implementation, prefetching algorithm, an experiment of the algorithm, experimental results of the active index…

This study tested two Web personal spiders (i.e., agents that take users' requests and perform real-time customized searches) based on best first-search and genetic-algorithm techniques. Both results were comparable and complementary, although the genetic algorithm obtained higher recall value. The Java-based interface was found to be necessary…