There has been a great deal of interest within the Information Retrieval community in evaluating the use of linguistic knowledge to improve the indexing and searching of textual databases. Such systems must often employ a lexicon to store information about the words and phrases comprising the application's domain. Unlike a static lexicon, a dynamic lexicon raises practical concerns about the coordination between the state of the lexicon and IR indexing schemes based on lexical knowledge. Additionally, it introduces a host of database management issues, many of which are similar to those found in the text databases as well. In this paper, we explore a range of system design and performance issues that arise when integrating a dynamic lexicon with a dynamic full-text information retrieval system. We observe that the principle of functional isolation argues against the use of language-dependent information in article indexes and favors the use of query-time strategies for applying lexical knowledge. We propose and evaluate a system architecture which embodies this principle. We also show how a storage and retrieval infrastructure based on Burkowski's [BURKOWSKI92] “containment model” abstraction can be employed to implement both the text retrieval and lexicon facilities required in an integrated system.

In this paper, we present an approach to the incorporation of object versioning into a distributed full-text information retrieval system. We propose an implementation based on “partially versioned” index sets, arguing that its space overhead and query-time performance make it suitable for full-text IR, with its heavy dependence on inverted indexing. We develop algorithms for computing both historical queries and time range queries and show how these algorithms can be applied to a number of problems in distributed information management, such as data replication, caching, transactional consistency, and hybrid media repositories.

AI-STARSis a lexicon-assisted full-text Information Retrieval system, designed for use in a dynamic corporate environment.In this paper, we explore how the requirements of such an environment have influenced many key aspects of the design and implementation of the AI-STARS system.We promote the use of "views" to create logical partitions in large, heterogeneous databases, and argue that storing not only article instances, but also class defhitions, stored queries, display templates and linguistic data in a single object repository has consequences that can be exploited for schema and lexicon evolution, security and subject filtering, information navigation, and data distribution.structured information objects.Next we consi&r querying on semi-stmctured objects and show how the notion of storing queries can & exploited to support multiple logical "views" of large databases.We then describe how our lexical and linguistic knowledge can take advantage of the object-oriented infrastmcture as well, arguing that a uniform representation of heterogeneous objects simplifies the tasks of data security, p~tioning, and distribution.We conclude with a dkcussion of implementation status and issues, related research, and user interface implications.

This paper describes the design of a direct manipulation user interface for Boolean information retrieval. Intended to overcome the difficulties of manipulating explicit Boolean queries as well as the “black box” drawbacks of so-called natural language query systems, the interface presents a two-dimensional graphical representation of a user's natural language query which not only exposes heuristic query transformations performed by the system, but also supports query reformulation by the user via direct manipulation of the representation. The paper illustrates the operation of the interface as implemented in the AI-STARS full-text information retrieval system.