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Abstract: In this paper, we describe EMADS, an extendible multi-agent data mining system. The EMADS vision is that of a community of data mining agents, contributed by many individuals, interacting under decentralised control to address data mining requests. EMADS is seen both as an end user application and a research tool. This paper details the EMADS vision, the associated conceptual framework and the current implementation. Although EMADS may be applied to many data mining tasks; the study described here, for the sake of brevity, concentrates on agent based data classification. A full description of EMADS is presented. [Copyright &y& Elsevier]

Abstract: Some parsers need to be very precise and strict when parsing, yet must allow users to easily adapt or extend the parser to parse new inputs, without requiring that the user have an in-depth knowledge and understanding of the parser’s internal workings. This paper presents a novel parsing architecture, designed for parsing Postfix log files, that aims to make the process of parsing new inputs as simple as possible, enabling users to trivially add new rules (to parse variants of existing inputs) and relatively easily add new actions (to process a previously unknown category of input). The architecture scales linearly or better as the number of rules and size of input increases, making it suitable for parsing large corpora or months of accumulated data. [Copyright &y& Elsevier]

Abstract: Traditionally, interactive natural language systems assume a semantic model in which the entities referred to are in some abstract representation of a real or imagined world. In a system where graphical objects such as diagrams may be on the screen during the language interaction, there is possibility that the user may want to allude to these visual entities. Since graphical objects have their own properties (colour, shape, position on the screen, etc.) but may also represent items in a knowledge base which have other associated properties (price, geographical location, technical specifications, etc.), some systematic way is needed to enable such objects to be referred to in terms of either their screen properties or their associated attributes from the domain under discussion. In this paper, we present a formalisation for these arrangements, and show how our logical definitions can be used to generate constraints suitable for reference resolution within a natural language interpreter. [Copyright &y& Elsevier]