International Conference on Mobile Computing, Applications, and Services

Mobile Computing, Applications, and Services pp 301-308

Using Interaction Signals for Job Recommendations

  • Benjamin Kille
  • Fabian Abel
  • Balázs Hidasi
  • Sahin Albayrak
Conference paper

DOI: 10.1007/978-3-319-29003-4_17

Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 162)
Cite this paper as:
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. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 162. Springer, Cham

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.

Keywords

Job recommendation Interactions Reciprocity Survey Ratings 

Copyright information

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

Authors and Affiliations

  • Benjamin Kille
    • 1
  • 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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