Abstract
Job recommender systems depend on accurate feedback to improve their suggestions. Implicit feedback arises in terms of clicks, bookmarks and replies. We present results from a member inquiry conducted on a large-scale job portal. We analyse correlations between ratings and implicit signals to detect situations where members liked their suggestions. Results show that replies and bookmarks reflect preferences much better than clicks.
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Acknowledgement
The research leading to these results has received funding from European Union Seventh Framework Programme (FP7/2007–2013) under Grant Agreement № 610594.
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© 2015 Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Kille, B., Abel, F., Hidasi, B., Albayrak, S. (2015). Using Interaction Signals for Job Recommendations. In: Sigg, S., Nurmi, P., Salim, F. (eds) Mobile Computing, Applications, and Services. MobiCASE 2015. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 162. Springer, Cham. https://doi.org/10.1007/978-3-319-29003-4_17
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DOI: https://doi.org/10.1007/978-3-319-29003-4_17
Publisher Name: Springer, Cham
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