xCLiMF: Optimizing expected reciprocal rank for data with multiple levels of relevance

Y Shi; A Karatzoglou; L Baltrunas; MA Larson; A Hanjalic

xCLiMF: Optimizing expected reciprocal rank for data with multiple levels of relevance

Y Shi, A Karatzoglou, L Baltrunas, MA Larson, A Hanjalic

Multimedia Computing

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

49 Citations (Scopus)

Original language	English
Title of host publication	Proceedings of the 7th ACM conference on Recommender systems (RecSys '13)
Editors	SN
Place of Publication	NY, NY, USA
Publisher	Association for Computing Machinery (ACM)
Pages	431-434
Number of pages	4
ISBN (Print)	978-1-4503-2409-0
Publication status	Published - 2013
Event	7th ACM Conference on Recommender Systems, RecSys 2013 - Hong Kong, China Duration: 12 Oct 2013 → 16 Oct 2013

Publication series

Name
Publisher	ACM

Conference

Conference	7th ACM Conference on Recommender Systems, RecSys 2013
Country/Territory	China
City	Hong Kong
Period	12/10/13 → 16/10/13

Keywords

conference contrib. refereed
Conf.proc. > 3 pag

Cite this

@inproceedings{3b6bfe26883e40e6aa65b97037a67d94,

title = "xCLiMF: Optimizing expected reciprocal rank for data with multiple levels of relevance",

keywords = "conference contrib. refereed, Conf.proc. > 3 pag",

author = "Y Shi and A Karatzoglou and L Baltrunas and MA Larson and A Hanjalic",

year = "2013",

language = "English",

isbn = "978-1-4503-2409-0",

publisher = "Association for Computing Machinery (ACM)",

pages = "431--434",

editor = "SN",

booktitle = "Proceedings of the 7th ACM conference on Recommender systems (RecSys '13)",

address = "United States",

note = "7th ACM Conference on Recommender Systems, RecSys 2013 ; Conference date: 12-10-2013 Through 16-10-2013",

}

Shi, Y, Karatzoglou, A, Baltrunas, L, Larson, MA & Hanjalic, A 2013, xCLiMF: Optimizing expected reciprocal rank for data with multiple levels of relevance. in SN (ed.), Proceedings of the 7th ACM conference on Recommender systems (RecSys '13). Association for Computing Machinery (ACM), NY, NY, USA, pp. 431-434, 7th ACM Conference on Recommender Systems, RecSys 2013, Hong Kong, China, 12/10/13.

xCLiMF: Optimizing expected reciprocal rank for data with multiple levels of relevance. / Shi, Y; Karatzoglou, A; Baltrunas, L et al.
Proceedings of the 7th ACM conference on Recommender systems (RecSys '13). ed. / SN. NY, NY, USA: Association for Computing Machinery (ACM), 2013. p. 431-434.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

TY - GEN

T1 - xCLiMF: Optimizing expected reciprocal rank for data with multiple levels of relevance

AU - Shi, Y

AU - Karatzoglou, A

AU - Baltrunas, L

AU - Larson, MA

AU - Hanjalic, A

PY - 2013

Y1 - 2013

KW - conference contrib. refereed

KW - Conf.proc. > 3 pag

UR - http://dl.acm.org/ft_gateway.cfm?id=2507227&ftid=1405040&dwn=1&CFID=267049508&CFTOKEN=75777149

M3 - Conference contribution

SN - 978-1-4503-2409-0

SP - 431

EP - 434

BT - Proceedings of the 7th ACM conference on Recommender systems (RecSys '13)

A2 - SN, null

PB - Association for Computing Machinery (ACM)

CY - NY, NY, USA

T2 - 7th ACM Conference on Recommender Systems, RecSys 2013

Y2 - 12 October 2013 through 16 October 2013

ER -

xCLiMF: Optimizing expected reciprocal rank for data with multiple levels of relevance

Publication series

Conference

Keywords

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Cite this