In this paper we present the concept of Federated Information Sharing Communities (FISC), which leverages organisational and social relationships with document content to provide community-centred information sharing and communication environments. Prominence is given to capabilities that go beyond the generic retrieval of documents to include the ability to retrieve people, their interests and inter-relationships. We focus on providing social awareness "in the large" to help users understand the members within community and the relationships between them. Within the FISC framework, we provide viewpoint retrieval to enable a user to construct member-specific view(s) of the community, based on their various topic interests. As proof of concept, we present the first FISC prototype based on the twenty-five year SIGIR collection and examples of operational results.

In this paper we describe the concept of Federated Information Sharing Communities (FISC), and associated architecture, which provide a way for organisations, distributed workgroups and individuals to build up a federated community based on their common interests over the World Wide Web. To support communities, we develop capabilities that go beyond the generic retrieval of documents to include the ability to retrieve people, their interests and inter-relationships. We focus on providing social awareness "in the large" to help users understand the members within a community and the relationships between them. Within the FISC framework, we provide viewpoint retrieval to enable a user to construct visual contextual views of the community from the perspective of any community member. To evaluate these ideas we develop test beds to compare individual component technologies such as user and group profile construction and similarity matching, and we develop prototypes to explore the broader architecture and usage issues.

Current e-Book browsers provide minimal support for comprehending the organization, narrative structure, and themes, of large complex books. In order to build an understanding of such books, readers should be provided with user interfaces that present, and relate, the organizational, narrative and thematic structures. We propose adapting information retrieval techniques for the purpose of discovering these structures, and sketch three distinctive visualizations for presenting these structures to the e-Book reader. These visualizations are presented within an initial design for an e-Book browser.

Abstract Clear and precise queries are a necessity when searching very large document collections, especially when query‐based retrieval is the only means of exploration. We propose system‐mediated information access as a solution for users' well‐documented inability to formulate good queries. Our approach is based on two main assumptions: first, on the ability of document clustering to reveal the topical, semantic structure of a problem domain represented by a specialized “source collection,” and, second, on the capacity of statistical language models to convey content. Taking the role of the human mediator or intermediary searcher, a mediation system interacts with the user and supports her exploration of a relatively small source collection, chosen to be representative for the problem domain. Based on the user's selection of relevant “exemplary” documents and clusters from this source collection, the system builds a language model of her information need. This model is subsequently used to derive “mediated queries,” which are expected to convey precisely and comprehensively the user's information need, and can be submitted by the user to search any large and heterogeneous “target collections.” We present results of experiments that simulated various mediation strategies and compared the effect on mediation effectiveness of a variety of parameters, such as the similarity measure, the weighting scheme, and the clustering method. They provide both upperbounds of performance that can potentially be reached by real end users and a comparison between the effectiveness of these strategies. The experimental evidence suggests that information retrieval mediated through a clustered specialized collection has potential to improve effectiveness significantly.

This paper introduces a novel switching method which can be used to combine two or more PPM models. The work derives from our earlier work on modelling English and text mining, and the approach takes advantage of both to help improve the compression performance significantly. The performance of the combination of models is at least as good as (and in many cases significantly better than) the best performed of the individual models. The paper reviews PPM-based text mining as it underpins the approach taken by the algorithm. It describes how PPM models are combined by applying a novel variation of the Viterbi algorithm. Results are then presented, followed by a discussion of related work, with conclusions.

No abstract available.

Epic is an image retrieval system that implements a novel spatial-querying mechanism.A usercentred, task-oriented, comparative evaluation of Epic was undertaken in which two versions of the system--one set up to enable spatial queries only, the other allowing textual queries only-were compared.Use was made of the two systems by design professionals in simulated work task situations, and quantitative and qualitative data collected as indicators of the levels of users' satisfaction.Re sults demonstrated that users often had a 'mental image' of a potentially satisfying picture in mind, that they were happy to express this need in visual terms, and that in doing so they preferred to have access to Epic's spatialquerying facility.Success in obtaining statistically significant results appears to support validation of the novel methodological framework adopted.

No abstract available.

A user-interface architecture, called FireWorks, is described.stractions are required for implementing a range of effective environments for information seeking.

This paper describes ECLAIR, an extensible object-oriented class library, which can be used to construct information retrieval systems and applications. ECLAIR is implemented in C++ and uses an object-oriented database management system for persistent object storage. The library provides data structures and operations necessary to allow the efficient indexing, storage and retrieval of data items based on their text content using automatic indexing and best-match retrieval techniques. By exploiting the object-oriented paradigm, we have been able to develop a library which is usable by any application requiring information retrieval functionality, and further, is extensible such that many of the functions provided by the library can be changed as required by an application. Additionally, applications can exploit the features of the underlying object-oriented database management system, which include support for persistence of data (objects), modelling complex objects, concurrent access to data, and reliable processing of data in the presence of system failures. In the paper we consider how to deliver information retrieval functionality to the developers of application systems and we evaluate current approaches. The design and implementation of ECLAIR is described in detail. A number of experiments applying ECLAIR are reported.