Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

User model in a box: Cross-system user model transfer for resolving cold start problems

Wongchokprasitti, C and Peltonen, J and Ruotsalo, T and Bandyopadhyay, P and Jacucci, G and Brusilovsky, P (2015) User model in a box: Cross-system user model transfer for resolving cold start problems. In: UNSPECIFIED.

[img] Plain Text (licence)
Available under License : See the attached license file.

Download (1kB)


Recommender systems face difficulty in cold-start scenarios where a new user has provided only few ratings. Improving cold-start performance is of great interest. At the same time, the growing number of adaptive systems makes it ever more likely that a new user in one system has already been a user in another system in related domains. To what extent can a user model built by one adaptive system help address a cold start problem in another system? We compare methods of cross-system user model transfer across two large real-life systems: we transfer user models built for information seeking of scientific articles in the SciNet exploratory search system, operating over tens of millions of articles, to perform cold-start recommendation of scientific talks in the CoMeT talk management system, operating over hundreds of talks. Our user study focuses on transfer of novel explicit open user models curated by the user during information seeking. Results show strong improvement in cold-start talk recommendation by transferring open user models, and also reveal why explicit open models work better in cross-domain context than traditional hidden implicit models.


Social Networking:
Share |


Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
CreatorsEmailPitt UsernameORCID
Wongchokprasitti, Cchw20@pitt.eduCHW20
Peltonen, J
Ruotsalo, T
Bandyopadhyay, P
Jacucci, G
Brusilovsky, Ppeterb@pitt.eduPETERB0000-0002-1902-1464
Date: 1 January 2015
Date Type: Publication
Journal or Publication Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume: 9146
Page Range: 289 - 301
Event Type: Conference
DOI or Unique Handle: 10.1007/978-3-319-20267-9_24
Institution: University of Pittsburgh
Refereed: Yes
ISBN: 9783319202662
ISSN: 0302-9743
Date Deposited: 27 Jul 2015 15:55
Last Modified: 30 Mar 2021 13:56


Monthly Views for the past 3 years

Plum Analytics

Actions (login required)

View Item View Item