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Contribution Details

Type Conference or Workshop Paper
Scope Discipline-based scholarship
Published in Proceedings Yes
Title Blockbusters and Wallflowers: Speeding up Diverse and Accurate Recommendations with Random Walks
Organization Unit
  • Fabian Christoffel
  • Bibek Paudel
  • Chris Newell
  • Abraham Bernstein
  • Jennifer Golbeck
  • Giovanni Semeraro
Presentation Type paper
Item Subtype Original Work
Refereed Yes
Status Published in final form
  • English
Event Title 9th ACM Conference on Recommender Systems RecSys 2015
Event Type conference
Event Location Vienna
Event Start Date September 16 - 2015
Event End Date September 20 - 2015
Place of Publication New York, NY, USA
Publisher ACM Press
Abstract Text User satisfaction is often dependent on providing accurate and diverse recommendations. In this paper, we explore algorithms that exploit random walks as a sampling technique to obtain diverse recommendations without compromising on efficiency and accuracy. Specifically, we present a novel graph vertex ranking recommendation algorithm called RP3β that re-ranks items based on 3-hop random walk transition probabilities. We show empirically, that RP3β provides accu- rate recommendations with high long-tail item frequency at the top of the recommendation list. We also present approx- imate versions of RP3β and the two most accurate previously published vertex ranking algorithms based on random walk transition probabilities and show that these approximations converge with increasing number of samples.
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Digital Object Identifier 10.1145/2792838.2800180
Other Identification Number merlin-id:12211
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