Workshop on New Trends in Content-based Recommender Systems (CBRecSys 2014)

Toine Bogers; Marijn Koolen; Ivan Cantádor

doi:10.1145/2645710.2645784

Workshop on New Trends in Content-based Recommender Systems (CBRecSys 2014)

Toine Bogers, Marijn Koolen, Ivan Cantádor

Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review

Abstract

While content-based recommendation has been applied successfully in many different domains, it has not seen the same level of attention as collaborative filtering techniques have. However, there are many recommendation domains and applications where content and metadata play a key role, either in addition to or instead of ratings and implicit usage data. For some domains, such as movies, the relationship between content and usage data has seen thorough investigation already, but for many other domains, such as books, news, scientific articles, and Web pages we still do not know if and how these data sources should be combined to provided the best recommendation performance. The CBRecSys 2014 workshop aims to address this by providing a dedicated venue for papers dedicated to all aspects of content-based recommendation.

Original language	English
Title of host publication	RecSys ‘14: Proceedings of the 2014 ACM Conference on Recommender Systems
Number of pages	2
Publisher	Association for Computing Machinery
Publication date	6 Oct 2014
Pages	379-380
ISBN (Print)	978-1-4503-2668-1
DOIs	https://doi.org/10.1145/2645710.2645784
Publication status	Published - 6 Oct 2014
Externally published	Yes
Event	ACM Conference in Recommender Systems - Foster City, United States Duration: 6 Oct 2014 → 10 Oct 2014

Conference

Conference	ACM Conference in Recommender Systems
Country/Territory	United States
City	Foster City
Period	06/10/2014 → 10/10/2014

Keywords

Content-Based Recommendation
Collaborative Filtering
Metadata
Recommendation Domains
CBRecSys 2014 Workshop

Access to Document

10.1145/2645710.2645784

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http://dl.acm.org/citation.cfm?id=2645710.2645784

Cite this

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title = "Workshop on New Trends in Content-based Recommender Systems (CBRecSys 2014)",

abstract = "While content-based recommendation has been applied successfully in many different domains, it has not seen the same level of attention as collaborative filtering techniques have. However, there are many recommendation domains and applications where content and metadata play a key role, either in addition to or instead of ratings and implicit usage data. For some domains, such as movies, the relationship between content and usage data has seen thorough investigation already, but for many other domains, such as books, news, scientific articles, and Web pages we still do not know if and how these data sources should be combined to provided the best recommendation performance. The CBRecSys 2014 workshop aims to address this by providing a dedicated venue for papers dedicated to all aspects of content-based recommendation.",

keywords = "Content-Based Recommendation, Collaborative Filtering, Metadata, Recommendation Domains, CBRecSys 2014 Workshop, Content-Based Recommendation, Collaborative Filtering, Metadata, Recommendation Domains, CBRecSys 2014 Workshop",

author = "Toine Bogers and Marijn Koolen and Ivan Cant{\'a}dor",

year = "2014",

month = oct,

day = "6",

doi = "10.1145/2645710.2645784",

language = "English",

isbn = "978-1-4503-2668-1",

pages = "379--380",

booktitle = "RecSys {\textquoteleft}14: Proceedings of the 2014 ACM Conference on Recommender Systems",

publisher = "Association for Computing Machinery",

address = "United States",

note = "ACM Conference in Recommender Systems, RecSys ; Conference date: 06-10-2014 Through 10-10-2014",

}

Workshop on New Trends in Content-based Recommender Systems (CBRecSys 2014). / Bogers, Toine; Koolen, Marijn; Cantádor, Ivan.
RecSys ‘14: Proceedings of the 2014 ACM Conference on Recommender Systems. Association for Computing Machinery, 2014. p. 379-380.

Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review

TY - GEN

T1 - Workshop on New Trends in Content-based Recommender Systems (CBRecSys 2014)

AU - Bogers, Toine

AU - Koolen, Marijn

AU - Cantádor, Ivan

PY - 2014/10/6

Y1 - 2014/10/6

N2 - While content-based recommendation has been applied successfully in many different domains, it has not seen the same level of attention as collaborative filtering techniques have. However, there are many recommendation domains and applications where content and metadata play a key role, either in addition to or instead of ratings and implicit usage data. For some domains, such as movies, the relationship between content and usage data has seen thorough investigation already, but for many other domains, such as books, news, scientific articles, and Web pages we still do not know if and how these data sources should be combined to provided the best recommendation performance. The CBRecSys 2014 workshop aims to address this by providing a dedicated venue for papers dedicated to all aspects of content-based recommendation.

AB - While content-based recommendation has been applied successfully in many different domains, it has not seen the same level of attention as collaborative filtering techniques have. However, there are many recommendation domains and applications where content and metadata play a key role, either in addition to or instead of ratings and implicit usage data. For some domains, such as movies, the relationship between content and usage data has seen thorough investigation already, but for many other domains, such as books, news, scientific articles, and Web pages we still do not know if and how these data sources should be combined to provided the best recommendation performance. The CBRecSys 2014 workshop aims to address this by providing a dedicated venue for papers dedicated to all aspects of content-based recommendation.

KW - Content-Based Recommendation

KW - Collaborative Filtering

KW - Metadata

KW - Recommendation Domains

KW - CBRecSys 2014 Workshop

KW - Content-Based Recommendation

KW - Collaborative Filtering

KW - Metadata

KW - Recommendation Domains

KW - CBRecSys 2014 Workshop

U2 - 10.1145/2645710.2645784

DO - 10.1145/2645710.2645784

M3 - Article in proceedings

SN - 978-1-4503-2668-1

SP - 379

EP - 380

BT - RecSys ‘14: Proceedings of the 2014 ACM Conference on Recommender Systems

PB - Association for Computing Machinery

T2 - ACM Conference in Recommender Systems

Y2 - 6 October 2014 through 10 October 2014

ER -

Workshop on New Trends in Content-based Recommender Systems (CBRecSys 2014)

Abstract

Conference

Keywords

Access to Document

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Cite this