Interfaces for eliciting new user preferences in recommender systems

Sean M. McNee, Shyong K. Lam, Joseph A. Konstan, John Riedl

Research output: Contribution to journalConference articlepeer-review

74 Scopus citations

Abstract

Recommender systems build user models to help users find the items they will find most interesting from among many available items. One way to build such a model is to ask the user to rate a selection of items. The choice of items selected affects the quality of the user model generated. In this paper, we explore the effects of letting the user participate in choosing the items that are used to develop the model. We compared three interfaces to elicit information from new users: having the system choose items for users to rate, asking the users to choose items themselves, and a mixed-initiative interface that combines the other two methods. We found that the two pure interfaces both produced accurate user models, but that directly asking users for items to rate increases user loyalty in the system. Ironically, this increased loyalty comes despite a lengthier signup process. The mixed-initiative interface is not a reasonable compromise as it created less accurate user models with no increase in loyalty.

Original languageEnglish (US)
Pages (from-to)178-187
Number of pages10
JournalLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
Volume2702
DOIs
StatePublished - Jan 1 2003
Event9th International Conference, UM 2003 - Johnstown, PA, United States
Duration: Jun 22 2003Jun 26 2003

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