This two-part article combines a comprehensive account of a probabilistic model of retrieval with new systematic experiments on TREC (Text Retrieval Conferences) Program material. Part 1 covers the foundations and the model development for document collection and relevance data, along with the test apparatus. Data and results tables for both parts…

A comprehensive account of a probabilistic model of retrieval with new systematic experiments on TREC (Text Retrieval Conferences) Program material. Part 2 covers the further development of the model, with testing, and briefly considers other environment conditions and tasks, model training, concluding with comparisons with other approaches and an…

Evaluates the performance of different methods of data compression coding in several situations. Huffman's code, arithmetic coding, fixed codes, fast approximations to arithmetic coding, and splay coding are discussed in terms of their speed, memory requirements, and proximity to optimal performance. Recommendations for the best methods of…

Describes a series of user studies used to advance understanding of how people use electronic tables (E-tables) and inform the development of a Web-based statistical table browser for use by non-specialists. Results of needs assessment, prototype development, and user studies provide a foundation for understanding E-tables in general and guiding…

Presents a technique for dividing text into field-coherent passages based upon extracting field-associated words or phrases from the text by determining how topics grow, shrink and shift from sentence to sentence. Proposes measures of topic continuity and transition and suggests how those may be used to find the passage boundaries. (Author/LRW)

Describes an approximate document ranking process that uses a compact array of in-memory, low-precision approximations for document length. Combined with another rule for reducing the memory required by partial similarity accumulators, the approximation heuristic allows the ranking of large document collections using less than one byte of memory…

Discusses a list of characteristics (dimensions) that are crucial for data model quality. Fourteen quality dimensions are singled out and organized in six categories: content, scope, level of detail, composition, consistency, and reaction to change. Two types of correlations among dimensions called "reinforcements" and…

Presents a compilation of definitions of information and other related terms including data, knowledge, impact, and development to organize and interrelate them. The goal is to provide members of the information science profession with a common basis for referring to key concepts. (Author/LRW)

Discussion of the vagueness of queries and uncertainty of knowledge when searching in information retrieval systems focuses on searching proper names and using similarity measures, including phonetic similarity, typing errors, and plain string similarity. It is shown experimentally that all three approaches lead to significantly higher retrieval…

Discusses hierarchic document clustering in information retrieval and its potential improved effectiveness over inverted file search (IFS). Describes experiments conducted to determine whether hierarchic clustering can increase the retrieval effectiveness compared to both static clustering and of conventional IFS when it is applied to search…

Discusses information retrieval system design that supports various information-seeking strategies. Describes a study that investigated the relationship between users' information-seeking goals and their information-seeking behavior to specify hierarchical levels of user goals, and discusses results that focus on patterns of interactive intentions…

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.…

Proposes a new method of text classification using stochastic decision lists, ordered sequences of IF-THEN-ELSE rules. The method can be viewed as a rule-based method for text classification having advantages of readability and refinability of acquired knowledge. Advantages of rule-based methods over non-rule-based ones are empirically verified.…

Discussion of image database systems focuses on semantic queries and shows how an image is abstracted into a hierarchy of entity names and features; how relations are established between entities visible in the image; and how a "fuzzy" matching technique is used to compare semantic queries to image abstractions. (Author/LRW)

Describes experiments in the retrieval of spoken documents in multimedia systems. Problems in spoken document retrieval are discussed, and a voice mail application is explained that combines state-of-the-art speech recognition with established document retrieval technologies to provide an effective and efficient retrieval tool. (Author/LRW)