Presents a relevance-feedback strategy that improves the effectiveness of information-retrieval systems based on back-propagation of the relevance of retrieved documents using an algorithm developed in a neural approach. Describes a neural information-retrieval model and reports results obtained with the algorithm in three different environments.…

Describes a detailed algorithm for fast text compression. Related to the PPM (prediction by partial matching) method, it simplifies the modeling phase by eliminating the escape mechanism and speeds up coding by using a combination of quasi-arithmetic coding and Rice coding. Details of the use of quasi-arithmetic code tables are given, and their…

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…

Discussion of evaluation methodology in information retrieval focuses on the average precision over a set of fixed recall values in an effort to evaluate the retrieval effectiveness of a search algorithm. Highlights include a review of traditional evaluation methodology with examples; and a statistical inference methodology called bootstrap.…

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…