Discussion of information retrieval focuses on the use of binary trees and how to compact it to use less memory and take less time. Explains retrieval algorithms and describes data structure and hierarchical structure. (LRW)

Discussion of word stemming for text processing and information retrieval focuses on an algorithm for generating stemmers from text stemmer specification files. Highlights include the use of finite state machines for stemming; stemmer specification file format; stemmer generation and driver algorithms; and stemmer timing comparisons. (Author/LRW)

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…

Discussion of the classification of documents from bibliographic databases focuses on a method of vectorizing reference documents from LISA (Library and Information Science Abstracts) which permits their topological organization using Kohonen's algorithm. Analyzes possibilities of this type of neural network with respect to the development of…

Presents a faster method for determining hierarchical relationships in information retrieval by using trie structures instead of a linear storage of a concept code. Highlights include case structures, a knowledge representation for natural-language understanding with semantic constraints; a compression algorithm of tries; and evaluation.…

Discussion of text compression focuses on a method to reduce the amount of storage needed to represent a Markov model with an extended alphabet, by applying a clustering scheme that brings together similar states. Highlights include probability vectors; algorithms; implementation details; and experimental data with natural languages. (Author/LRW)

Presents a multilevel model of the information filtering process that permits document classification. Evaluates a document classification approach based on a supervised learning algorithm, measures the accuracy of the algorithm in a neural network that was trained to classify medical documents on cell biology, and discusses filtering…

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 local similarity pattern (LSP) as a new method for computing digital image similarity. Topics include optimizing similarity computation based on genetic algorithm; relevance feedback; and an evaluation of LSP on five databases that showed an increase in retrieval precision over other methods for computing image similarity. (Author/LRW)

Considers the need for keyphrase-extraction techniques in intelligent Chinese information retrieval and presents a PAT-tree-based adaptive approach, developed from the PATRICIA Algorithm (Practical Algorithm to Retrieve Information Coded in Alphanumeric). Discusses Internet utilization, automatic term suggestion, domain-specific lexicon…

Presents a document-clustering algorithm that uses a term frequency vector for each document in a Japanese collection to produce a hierarchy in the form of a document classification tree. Introduces an application of this algorithm to a Japanese-to-English translation-aid system. (Author/LRW)

Proposes a novel approach to automatically retrieve keywords and then uses genetic algorithms to adapt the keyword weights. Discusses Chinese text retrieval, term frequency rating formulas, vector space models, bigrams, the PAT-tree structure for information retrieval, query vectors, and relevance feedback. (Author/LRW)

Discussion of query processing focuses on techniques developed by LEXIS-NEXIS for identifying key concepts, selecting synonyms and related terms, and detecting phrases that can be combined to increase recall and precision. Describes experiments in the ad hoc track of the sixth TREC (Text Retrieval Conference), including the use of ranking…

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.…

Presents a technique for developing a knowledge-base of information to use in an expert system. Proposed approach employs a popular machine-learning algorithm along with a method for forming a finite number of features or conjuncts of at most n primitive attributes. Illustrates this procedure by examining qualitative information represented in a…