Using Interaction Signals for Job Recommendations

  • Benjamin KilleEmail author
  • Fabian Abel
  • Balázs Hidasi
  • Sahin Albayrak
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 162)


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.


Job recommendation Interactions Reciprocity Survey Ratings 



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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Copyright information

© Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2015

Authors and Affiliations

  • Benjamin Kille
    • 1
    Email author
  • Fabian Abel
    • 2
  • Balázs Hidasi
    • 3
  • Sahin Albayrak
    • 1
  1. 1.Berlin Institute of TechnologyBerlinGermany
  2. 2.XING AGHamburgGermany
  3. 3.Gravity ResearchBudapestHungary

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