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Natural language processing for expertise modelling in e-mail communication

Natural language processing for expertise modelling in e-mail communication
Natural language processing for expertise modelling in e-mail communication
One way to find information that may be required, is to approach a person who is believed to possess it or to identify a person who knows where to look for it. Technical support, which automatically compiles individual expertise and makes this accessible, may be centred on an expert finder system. A central component of such a system is a user profile, which describes user expertise level in discussed subjects. Previous works have made attempts to weight user expertise by using content-based methods, which associate the expertise level with the analysis of keyword usage, irrespective of any semantic meanings conveyed. This paper explores the idea of using a natural language processing technique to understand given information from both a structural and semantic perspective in building user profiles. With its improved interpretation capability compared to prior works, it aims to enhance the performance accuracy in ranking the order of names of experts, returned by a system against a help-seeking query. To demonstrate its efficiency, e-mail communication is chosen as an application domain, since its closeness to a spoken dialog, makes it possible to focus on the linguistic attributes of user information in the process of expertise modelling. Experimental results from a case study show a 23% higher performance on average over 77% of the queries tested with the approach presented here.
3540440259
2412
161-161
Springer
Kim, Sanghee
9e0e5909-9fbe-4c37-9606-2fdea35eac12
Hall, Wendy
11f7f8db-854c-4481-b1ae-721a51d8790c
Keane, Andy
26d7fa33-5415-4910-89d8-fb3620413def
Kim, Sanghee
9e0e5909-9fbe-4c37-9606-2fdea35eac12
Hall, Wendy
11f7f8db-854c-4481-b1ae-721a51d8790c
Keane, Andy
26d7fa33-5415-4910-89d8-fb3620413def

Kim, Sanghee, Hall, Wendy and Keane, Andy (2002) Natural language processing for expertise modelling in e-mail communication. In Intelligent Data Engineering and Automated Learning - IDEAL 2002: Third International Conference, Manchester, UK, August 12-14,2002. Proceedings. Springer. p. 161.

Record type: Conference or Workshop Item (Paper)

Abstract

One way to find information that may be required, is to approach a person who is believed to possess it or to identify a person who knows where to look for it. Technical support, which automatically compiles individual expertise and makes this accessible, may be centred on an expert finder system. A central component of such a system is a user profile, which describes user expertise level in discussed subjects. Previous works have made attempts to weight user expertise by using content-based methods, which associate the expertise level with the analysis of keyword usage, irrespective of any semantic meanings conveyed. This paper explores the idea of using a natural language processing technique to understand given information from both a structural and semantic perspective in building user profiles. With its improved interpretation capability compared to prior works, it aims to enhance the performance accuracy in ranking the order of names of experts, returned by a system against a help-seeking query. To demonstrate its efficiency, e-mail communication is chosen as an application domain, since its closeness to a spoken dialog, makes it possible to focus on the linguistic attributes of user information in the process of expertise modelling. Experimental results from a case study show a 23% higher performance on average over 77% of the queries tested with the approach presented here.

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More information

Published date: 2002
Additional Information: ISSN: 0302-9743
Venue - Dates: Intelligent Data Engineering and Automated Learning - IDEAL 2002: Third International Conference, 2002-08-12 - 2002-08-14

Identifiers

Local EPrints ID: 22395
URI: https://eprints.soton.ac.uk/id/eprint/22395
ISBN: 3540440259
PURE UUID: 9f0cf1ba-a687-4730-abf0-270608b3e92a
ORCID for Wendy Hall: ORCID iD orcid.org/0000-0003-4327-7811

Catalogue record

Date deposited: 31 Mar 2006
Last modified: 06 Jun 2018 13:19

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Contributors

Author: Sanghee Kim
Author: Wendy Hall ORCID iD
Author: Andy Keane

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