Proposes a new approach for classifying text documents into two disjoint classes. Highlights include a brief overview of document clustering; a data mining approach called the One Clause at a Time (OCAT) algorithm which is based on mathematical logic; vector space model (VSM); and comparing the OCAT to the VSM. (Author/LRW)

Explains the use of genetic algorithms to combine results from multiple query evaluations to improve relevance in information retrieval. Discusses niching techniques, relevance feedback techniques, and evolution heuristics, and compares retrieval results obtained by both genetic multiple query evaluation and classical single query evaluation…

Describes the design of optimal tree-structured vector quantizers that minimize the expected distortion subject to cost functions related to storage cost, encoding rate, or quantization time. Since the optimal design problem is intractable in most cases, the performance of a general design heuristic based on successive partitioning is analyzed.…

Discussion of information retrieval, query optimization techniques, and relevance feedback focuses on genetic algorithms, which are derived from artificial intelligence techniques. Describes an evaluation of different genetic algorithms using a residual collection method and compares results with the Ide dec-hi method (Salton and Buckley, 1990…

Presents two new algorithms for performing arithmetic coding without employing multiplication and discusses their implementation requirements. The first algorithm, suitable for an alphabet of arbitrary size, reduces the worst case excess length to under 0.8%. The second algorithm, suitable only for alphabets of less than 12 symbols, allows even…

Presents an inference algorithm that produces a weighted finite automata (WFA), in particular, the grayness functions of graytone images. Image-data compression results based on the new inference algorithm produces a WFA with a relatively small number of edges. Image-data compression results alone and in combination with wavelets are discussed.…

In information retrieval (IR), the aim of genetic algorithms (GA) is to help a system to find, in a huge documents collection, a good reply to a query expressed by the user. Analysis of phenomena seen during the implementation of a GA for IR has led to a new crossover operation, which is introduced and compared to other learning methods.…

Presents a probabilistic technique to retrieve passages from texts having a large size or heterogeneous semantic content. Results of experiments comparing the probabilistic technique to one based on a text segmentation algorithm revealed that the passage size affects passage retrieval performance; text organization and query generality may have an…

Analyzes the properties of genetic sequences that cause the failure of classical algorithms used for data compression. A lossless algorithm, which compresses the information contained in DNA and RNA sequences by detecting regularities such as palindromes, is presented. This algorithm combines substitutional and statistical methods and appears to…