Finding and Mapping Expertise Automatically Using Corporate Data
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In an organization, both management as well as new and experienced employees often have a need to get in touch with experts in a variety of situations. The new staff members need to learn how to perform their job, the management need - amongst other things - to man projects and vacancies, and other employees are often dependent on others' expertise to accomplish their tasks. Traditionally this problem has often been approached with computer applications using semi-automatic methods involving self-assessments of expertise stored in databases. These methods prove to be time-consuming, they do not consider the dynamics of expertise and the self-assessed expertise is often difficult to validate. This report presents an overview of issues involved in expertise finding and the development of a simple, yet effective prototype which tries to overcome the mentioned problems by using a fully automatic approach. A study of the Urban Development area at the Municipality of Trondheim is carried out to analyze this organizations' possessed expertise, sought after expertise and to collect necessary information for building the expertise finder prototype. The study found that a lot of expertise evidence is found in the formal correspondence archived in the case handling systems' document repository, and that the structure and content of these documents could fit a fully-automatic Expertise finder well. Four alternative test cases have been evaluated during the testing and evaluation of the prototype. One of these test cases - where expert profiles are modelled on-the-fly based on employees' names occurring in formal documents - is able to compete with- and in some cases outperform evaluation scores presented in related research.