Measuring spontaneous devaluations in user preferences

Komal Kapoor, Nisheeth Srivastava, Jaideep Srivastava, Paul Schrater

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

Spontaneous devaluation in preferences is ubiquitous, where yesterday's hit is today's affiction. Despite technological advances facilitating access to a wide range of media com- modities, finding engaging content is a major enterprise with few principled solutions. Systems tracking spontaneous devaluation in user preferences can allow prediction of the on-set of boredom in users potentially catering to their changed needs. In this work, we study the music listening histories of Last.fm users focusing on the changes in their preferences based on their choices for different artists at different points in time. A hazard function, commonly used in statistics for survival analysis, is used to capture the rate at which a user returns to an artist as a function of exposure to the artist. The analysis provides the first evidence of sponta- neous devaluation in preferences of music listeners. Better understanding of the temporal dynamics of this phenomenon can inform solutions to the similarity-diversity dilemma of recommender systems.

Original languageEnglish (US)
Title of host publicationKDD 2013 - 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
EditorsRajesh Parekh, Jingrui He, Dhillon S. Inderjit, Paul Bradley, Yehuda Koren, Rayid Ghani, Ted E. Senator, Robert L. Grossman, Ramasamy Uthurusamy
PublisherAssociation for Computing Machinery
Pages1061-1069
Number of pages9
ISBN (Electronic)9781450321747
DOIs
StatePublished - Aug 11 2013
Event19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2013 - Chicago, United States
Duration: Aug 11 2013Aug 14 2013

Publication series

NameProceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
VolumePart F128815

Other

Other19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2013
CountryUnited States
CityChicago
Period8/11/138/14/13

Keywords

  • Dynamic preferences
  • Recommender systems
  • Temporalmod- els
  • User behavior modeling

Fingerprint Dive into the research topics of 'Measuring spontaneous devaluations in user preferences'. Together they form a unique fingerprint.

Cite this