Recommender systems and the social web

Amit Tiroshi, Tsvi Kuflik, Judy Kay, Bob Kummerfeld

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In the past, classic recommender systems relied solely on the user models they were able to construct by themselves and suffered from the "cold start" problem. Recent decade advances, among them internet connectivity and data sharing, now enable them to bootstrap their user models from external sources such as user modeling servers or other recommender systems. However, this approach has only been demonstrated by research prototypes. Recent developments have brought a new source for bootstrapping recommender systems: social web services. The variety of social web services, each with its unique user model characteristics, could aid bootstrapping recommender systems in different ways. In this paper we propose a mapping of how each of the classical user modeling approaches can benefit from nowadays active services' user models, and also supply an example of a possible application.

Original languageEnglish
Title of host publicationAdvances in User Modeling - UMAP 2011 Workshops, Revised Selected Papers
Pages60-70
Number of pages11
DOIs
StatePublished - 2012
EventUser Modeling, Adaptation and Personalization Conference, UMAP 2011 - Girona, Spain
Duration: 11 Jul 201115 Jul 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7138 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceUser Modeling, Adaptation and Personalization Conference, UMAP 2011
Country/TerritorySpain
CityGirona
Period11/07/1115/07/11

Keywords

  • Recommender Systems
  • Social Web Services
  • User Modeling

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science (all)

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