Exploiting item and user relationships for recommender systems

Zhu Sun*

*Corresponding author for this work

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

4 Citations (Scopus)

Abstract

Recommender systems have become a prevalent tool to cope with the information overload problem. The most well-known recommendation technique is collaborative filtering (CF), whereby a user’s preference can be predicted by her like-minded users. Data sparsity and cold start are two inherent and severe limitations of CF.
Original languageEnglish
Title of host publicationUser modeling, adaptation and personalization
Subtitle of host publication23rd International Conference, UMAP 2015, Proceedings
EditorsFrancesco Ricci, Kalina Bontcheva, Owen Conlan, Séamus Lawless
Place of PublicationCham, Switzerland
PublisherSpringer, Springer Nature
Pages397-402
Number of pages6
ISBN (Electronic)9783319202679
ISBN (Print)9783319202662
DOIs
Publication statusPublished - 2015
Externally publishedYes
Event23rd International Conference on User Modeling, Adaptation and Personalization, UMAP 2015 - Dublin, Ireland
Duration: 29 Jun 20153 Jul 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9146
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference23rd International Conference on User Modeling, Adaptation and Personalization, UMAP 2015
CountryIreland
CityDublin
Period29/06/153/07/15

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