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Expert Finding by Capturing Organisational Knowledge from Legacy Documents

Expert Finding by Capturing Organisational Knowledge from Legacy Documents
Expert Finding by Capturing Organisational Knowledge from Legacy Documents
Organisations capitalise on their best knowledge through the improvement of shared expertise which leads to a higher level of productivity and competency. The recognition of the need to foster the sharing of expertise has led to the development of expert finder systems that hold pointers to experts who posses specific knowledge in organisations. This paper discusses an approach to locating an expert through the application of information retrieval and analysis processes to an organization’s existing information resources, with specific reference to the engineering design domain. The approach taken was realised through an expert finder system framework. It enables the relationships of heterogeneous information sources with experts to be factored in modelling individuals’ expertise. These valuable relationships are typically ignored by existing expert finder systems, which only focus on how documents relate to their content. The developed framework also provides an architecture that can be easily adapted to different organisational environments. In addition, it also allows users to access the expertise recognition logic, giving them greater trust in the systems implemented using this framework. The framework were applied to real world application and evaluated within a major engineering company.
Expert finder system, knowledge management, capturing knowledge
Sim, Y W
b8eb0767-59b9-4410-bff0-042e8d52dfeb
Crowder, R M
ddeb646d-cc9e-487b-bd84-e1726d3ac023
Wills, G B
3a594558-6921-4e82-8098-38cd8d4e8aa0
Sim, Y W
b8eb0767-59b9-4410-bff0-042e8d52dfeb
Crowder, R M
ddeb646d-cc9e-487b-bd84-e1726d3ac023
Wills, G B
3a594558-6921-4e82-8098-38cd8d4e8aa0

Sim, Y W, Crowder, R M and Wills, G B (2006) Expert Finding by Capturing Organisational Knowledge from Legacy Documents At IEEE International Conference on Computer & Communication Engineering (ICCCE '06), Malaysia. 09 - 11 May 2006.

Record type: Conference or Workshop Item (Paper)

Abstract

Organisations capitalise on their best knowledge through the improvement of shared expertise which leads to a higher level of productivity and competency. The recognition of the need to foster the sharing of expertise has led to the development of expert finder systems that hold pointers to experts who posses specific knowledge in organisations. This paper discusses an approach to locating an expert through the application of information retrieval and analysis processes to an organization’s existing information resources, with specific reference to the engineering design domain. The approach taken was realised through an expert finder system framework. It enables the relationships of heterogeneous information sources with experts to be factored in modelling individuals’ expertise. These valuable relationships are typically ignored by existing expert finder systems, which only focus on how documents relate to their content. The developed framework also provides an architecture that can be easily adapted to different organisational environments. In addition, it also allows users to access the expertise recognition logic, giving them greater trust in the systems implemented using this framework. The framework were applied to real world application and evaluated within a major engineering company.

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More information

Published date: 2006
Additional Information: Event Dates: 9-11 May 2006
Venue - Dates: IEEE International Conference on Computer & Communication Engineering (ICCCE '06), Malaysia, 2006-05-09 - 2006-05-11
Keywords: Expert finder system, knowledge management, capturing knowledge
Organisations: Agents, Interactions & Complexity, Electronic & Software Systems

Identifiers

Local EPrints ID: 262509
URI: http://eprints.soton.ac.uk/id/eprint/262509
PURE UUID: 90c133ff-5851-4883-8296-1e075362f1c5
ORCID for G B Wills: ORCID iD orcid.org/0000-0001-5771-4088

Catalogue record

Date deposited: 05 May 2006
Last modified: 18 Jul 2017 08:50

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