Exploiting item and user relationships for recommender systems

Zhu Sun

doi:10.1007/978-3-319-20267-9_37

Exploiting item and user relationships for recommender systems

Zhu Sun^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-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 language	English
Title of host publication	User modeling, adaptation and personalization
Subtitle of host publication	23rd International Conference, UMAP 2015, Proceedings
Editors	Francesco Ricci, Kalina Bontcheva, Owen Conlan, Séamus Lawless
Place of Publication	Cham, Switzerland
Publisher	Springer, Springer Nature
Pages	397-402
Number of pages	6
ISBN (Electronic)	9783319202679
ISBN (Print)	9783319202662
DOIs	https://doi.org/10.1007/978-3-319-20267-9_37
Publication status	Published - 2015
Externally published	Yes
Event	23rd International Conference on User Modeling, Adaptation and Personalization, UMAP 2015 - Dublin, Ireland Duration: 29 Jun 2015 → 3 Jul 2015

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9146
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	23rd International Conference on User Modeling, Adaptation and Personalization, UMAP 2015
Country/Territory	Ireland
City	Dublin
Period	29/06/15 → 3/07/15

Access to Document

10.1007/978-3-319-20267-9_37

Cite this

Sun, Z. (2015). Exploiting item and user relationships for recommender systems. In F. Ricci, K. Bontcheva, O. Conlan, & S. Lawless (Eds.), User modeling, adaptation and personalization: 23rd International Conference, UMAP 2015, Proceedings (pp. 397-402). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9146). Springer, Springer Nature. https://doi.org/10.1007/978-3-319-20267-9_37

Sun, Zhu. / Exploiting item and user relationships for recommender systems. User modeling, adaptation and personalization: 23rd International Conference, UMAP 2015, Proceedings. editor / Francesco Ricci ; Kalina Bontcheva ; Owen Conlan ; Séamus Lawless. Cham, Switzerland : Springer, Springer Nature, 2015. pp. 397-402 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Exploiting item and user relationships for recommender systems",

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{\textquoteright}s preference can be predicted by her like-minded users. Data sparsity and cold start are two inherent and severe limitations of CF.",

author = "Zhu Sun",

year = "2015",

doi = "10.1007/978-3-319-20267-9_37",

language = "English",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer, Springer Nature",

pages = "397--402",

editor = "Francesco Ricci and Kalina Bontcheva and Owen Conlan and S{\'e}amus Lawless",

booktitle = "User modeling, adaptation and personalization",

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note = "23rd International Conference on User Modeling, Adaptation and Personalization, UMAP 2015 ; Conference date: 29-06-2015 Through 03-07-2015",

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Sun, Z 2015, Exploiting item and user relationships for recommender systems. in F Ricci, K Bontcheva, O Conlan & S Lawless (eds), User modeling, adaptation and personalization: 23rd International Conference, UMAP 2015, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9146, Springer, Springer Nature, Cham, Switzerland, pp. 397-402, 23rd International Conference on User Modeling, Adaptation and Personalization, UMAP 2015, Dublin, Ireland, 29/06/15. https://doi.org/10.1007/978-3-319-20267-9_37

Exploiting item and user relationships for recommender systems. / Sun, Zhu.

User modeling, adaptation and personalization: 23rd International Conference, UMAP 2015, Proceedings. ed. / Francesco Ricci; Kalina Bontcheva; Owen Conlan; Séamus Lawless. Cham, Switzerland : Springer, Springer Nature, 2015. p. 397-402 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9146).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

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AU - Sun, Zhu

PY - 2015

Y1 - 2015

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AB - 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.

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DO - 10.1007/978-3-319-20267-9_37

M3 - Conference proceeding contribution

AN - SCOPUS:84937433224

SN - 9783319202662

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 397

EP - 402

BT - User modeling, adaptation and personalization

A2 - Ricci, Francesco

A2 - Bontcheva, Kalina

A2 - Conlan, Owen

A2 - Lawless, Séamus

PB - Springer, Springer Nature

CY - Cham, Switzerland

T2 - 23rd International Conference on User Modeling, Adaptation and Personalization, UMAP 2015

Y2 - 29 June 2015 through 3 July 2015

ER -

Sun Z. Exploiting item and user relationships for recommender systems. In Ricci F, Bontcheva K, Conlan O, Lawless S, editors, User modeling, adaptation and personalization: 23rd International Conference, UMAP 2015, Proceedings. Cham, Switzerland: Springer, Springer Nature. 2015. p. 397-402. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-20267-9_37

Exploiting item and user relationships for recommender systems

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