Rodrigo Gonçalves
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Abstract
Understanding people’s expertise is not a trivial task since it is time-consuming when manually executed. Automated approaches have become a topic of research in recent years in various scientific fields, such as information retrieval, databases, and machine learning. This article carries out a survey on automated expertise retrieval, i.e., finding data linked to a person that describes the person’s expertise, which allows tasks such as profiling or finding people with a certain expertise. A faceted taxonomy is introduced that covers many of the existing approaches and classifies them on the basis of features chosen from studying the state-of-the-art. A list of open issues, with suggestions for future research topics, is introduced as well. It is hoped that our taxonomy and review of related works on expertise retrieval will be useful when analyzing different proposals and will allow a better understanding of existing work and a systematic classification of future work on the topic.
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Index Terms
- Automated Expertise Retrieval: A Taxonomy-Based Survey and Open Issues
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