Proactive: Comprehensive Access to Job Information

Danielle Lee and Peter Brusilovsky
Volume: 8, No: 4, Page: 721 ~ 738, Year: 2012
10.3745/JIPS.2012.8.4.721
Keywords: Job recommendation, explicit preference, implicit preference, personalized information retrieval
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Abstract
The Internet has become an increasingly important source for finding the right employees, so more and more companies post their job openings on the Web. The large amount and dynamic nature of career recruiting information causes information overload problems for job seekers. To assist Internet users in searching for the right job, a range of research and commercial systems were developed over the past 10 years. Surprisingly, the majority of existing job search systems support just one, rarely two ways of information access. In contrast, our work focused on exploring a value of comprehensive access to job information in a single system (i.e., a system which supports multiple ways). We designed Proactive, a recommendation system providing comprehensive and personalized information access. To assist the varied needs of users, Proactive has four information retrieval methods – a navigable list of jobs, keyword-based search, implicit preference-based recommendations, and explicit preference-based recommendations. This paper introduces the Proactive and reports the results of a study focusing on the experimental evaluation of these methods. The goal of the study was to assess whether all of the methods are necessary for users to find relevant jobs and to what extent different methods can meet different users’ information requirements.

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Cite this article
IEEE Style
Danielle Lee and Peter Brusilovsky, "Proactive: Comprehensive Access to Job Information," Journal of Information Processing Systems, vol. 8, no. 4, pp. 721~738, 2012. DOI: 10.3745/JIPS.2012.8.4.721.

ACM Style
Danielle Lee and Peter Brusilovsky, "Proactive: Comprehensive Access to Job Information," Journal of Information Processing Systems, 8, 4, (2012), 721~738. DOI: 10.3745/JIPS.2012.8.4.721.