Automatic People Tagging for Expertise Profiling in the Enterprise

Abstract

In an enterprise search setting, there is a class of queries for which people, rather than documents, are desirable answers. However, presenting users with just a list of names of knowledgeable employees without any description of their expertise may lead to confusion, lack of trust in search results, and abandonment of the search engine. At the same time, building a concise meaningful description for a person is not a trivial summarization task. In this paper, we propose a solution to this problem by automatically tagging people for the purpose of profiling their expertise areas in the scope of the enterprise where they are employed. We address the novel task of automatic people tagging by using a machine learning algorithm that combines evidence that a certain tag is relevant to a certain employee acquired from different sources in the enterprise. We experiment with the data from a large distributed organization, which also allows us to study sources of expertise evidence that have been previously overlooked, such as personal click-through history. The evaluation of the proposed methods shows that our technique clearly outperforms state of the art approaches.