: Full-text retrieval systems typically use either a bitmap or an inverted file to identify which documents contain which words, so that the documents containing any combination of words can be quickly located. Bitmaps of word occurrences are large, but are usually sparse, and thus are amenable to a variety of compression techniques. Here we consider techniques in which the encoding of each bitvector within the bitmap is parameterised, so that a different code can be used for each bitvector. Our experimental results show that the new methods yield better compression than previous techniques. Categories and Subject Descriptors: E.4 [Coding and Information Theory]: Data compaction and compression; H.3.2 [Information Storage]: File organisation . Keywords: Full-text retrieval, data compression, document database, Huffman coding, geometric distribution, inverted file. 1 Introduction Full-text retrieval systems are used for storing and accessing document collections such as newspaper a...

Structure definitions of documents have been used successfully for inputting and formatting in text processing systems. This report considers transformations between different representations of structured documents and studies possibilities to extend the use of structure definitions to document transformations and to discover algorithmic methods for carrying out transformations. Documents are presented as parse trees for context-free grammars and transformations are made from parse tree to parse tree. First, the report describes differences of manuscript styles required by various scientific journals and presents a declarative classification for structure differences between two parse trees. Second, a set of tree transformation methods are described and their suitability for transformations between documents having a structure difference in each defined class is analyzed. For each class several methods may or must be used and only certain kinds of differences can be managed automatica...

Clustering is used in information retrieval systems to enhance the efficiency and effectiveness of the retrieval process. Clustering is achieved by partitioning the documents in a collection into classes such that documents that are associated with each other are assigned to the same cluster. This association is generally determined by examining the index term representation of documents or by capturing user feedback on queries to the system. In cluster-oriented systems, the retrieval process can be enhanced by employing characterization of clusters. In this paper, we present the techniques to develop clusters and cluster characterizations by employing user viewpoint. The user viewpoint is elicited through a structured interview based on a knowledge acquisition technique, namely personal construct theory. It is demonstrated that the application of personal construct theory results in a cluster representation that can be used during query as well as to assign new documents to the approp...

This paper describes our experience in using a multimedia project management and software engineering environment, Decision-based Hyper-multimedia CASE (DHC), to support the Low-Visibility Landing and Surface Operations (LVLASO) project at the NASA Langley Research Center. 1 The purpose of the LVLASO project is to allow pilots to land and taxi airplanes when visibility is impeded due to adverse weather conditions. NASA is supporting this effort by developing new cockpit systems concepts for use on the flight deck. We are utilizing DHC to capture the decisions and documents generated during this project's life cycle. DHC supports a new Decision-based Systems Development paradigm, which allows the organization of the project by the decisions which shape the end-products and associated documents. This paper describes our current understanding of using a hyperlinked multimedia project space in developing large, group collaborative projects. 1 Low Visibility Landing and Surface Operations...