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- PublicationPassive Profiling and Collaborative RecommendationOnline recruitment services have rapidly become one of the most popular types of application on the World-Wide Web. The award-winning JobFinder site ( www.jobfinder.ie) is good example. It allows users to browse and search a large database of current jobs from a variety of employment sectors. However, like many similar Internet applications JobFinder has a number of shortcomings, due mainly to its reliance on traditional database technology and client-pull information access models, which place the burden of navigation and search on the user. To address these shortcomings the CASPER (Case-based Agency: Skill Profiling & Electronic Recruitment) project seeks to investigate the role of Artificial Intelligence techniques such as Automated Collaborative Filtering (ACF) and Case-Based Reasoning (CBR) as a means of providing a more proactive, personalised and intelligent model of information access.
- PublicationPersonalised Retrieval for Online Recruitment ServicesInternet search technology is largely based on exact-match retrieval. Such systems rely on the user to provide an adequate description of their requirements. However, most users submit poorly specified queries, leading to imprecise search results. Furthermore, there is no facility for personalising searches to reflect implicit likes and dislikes of users. We describe two complementary solutions to these problems as implemented in CASPER, an intelligent online recruitment service. We describe an approach to personalised similarity-based retrieval, and a queryless collaborative filtering recommendation technique.
- PublicationA large scale study of European mobile search behaviourRecent evidence suggests that mobile search is becoming an increasingly important way for mobile users to gain access to online information, especially as off-portal content continues to grow rapidly. In this paper we study the characteristics of mobile search by analysing approximately 6 million individual search requests generated by over 260,000 individual mobile searchers over a 7- day period during 2006. We analyse the patterns of queries used by mobile searchers and focus on key characteristics such as the clickthru rates of mobile searches in order to understand, for the first time, just how well mobile search engines are responding to user queries. Moreover, we compare our results to a number of recent mobile studies and highlight some of the key differences between mobile search and traditional Web search behaviours.
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