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Data & Knowledge Engineering
Volume 59, Issue 1, October 2006, Pages 1-24
 
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doi:10.1016/j.datak.2005.06.005    How to Cite or Link Using DOI (Opens New Window)
Copyright © 2005 Elsevier B.V. All rights reserved.

Merging news reports that describe events

Anthony HunterCorresponding Author Contact Information, a, E-mail The Corresponding Author and Rupert Summertona

aDepartment of Computer Science, University College London, Gower Street, London WC1E 6BT, UK

Received 25 February 2005; 
accepted 29 June 2005. 
Available online 27 July 2005.

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Abstract

Many kinds of news report provide information about events. For example, business news reports in the area of mergers and acquisitions, provide information about events such as “company X making a bid for company Y”, or “takeover of company Y by company X being rejected by the anti-trust authorities”. Furthermore, news reports do not normally exist in isolation. There is an underlying narrative which concerns a number of entities related in some way over a period of time. In many domains, stories will follow a stereotypical sequence. For example, a particular takeover may involve a bid being made, a rejection by the target board, a rise in the bid value by the potential buyer, a recommendation of acceptance by the target board, acceptance by the shareholders, and finally successful completion of the takeover. In order to merge heterogeneous news reports that describe events, we need to identify and reason about the events being described prior to merging them. In this paper, we investigate this problem with a focus on structured news reports. Each structured news report (SNR) is an XML document, where the textentries are restricted to individual words or simple phrases, such as names and domain-specific terminology, and numbers and units. We assume SNRs do not require natural language processing. As each SNR is isomorphic to a term in logic, we use a logic-based approach to extract relevant information about the events being described in the reports to be merged. We then provide a new version of the event calculus to assimilate the information from the various reports, to obtain the most up-to-date and complete picture of the events being described. Finally, from this assimilated information, we generate an SNR as the output.

Keywords: Information integration; Knowledge fusion; Event calculus; Structured news reports

Article Outline

1. Introduction
2. Assumptions about the domain for event-based merging
3. Input for event-based merging
4. Basic definitions for the object-level and meta-level
5. Inferences about events from input
6. Transition axioms
7. Event calculus
8. Output of event-based merging
9. Implementing event-based merging
10. Discussion
Acknowledgements
Appendix A. Appendix
References
Vitae


 
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