Report on RecSys 2014 Workshop on New Trends in Content-Based Recommender Systems (CBRecSys 2014)

Toine Bogers, Marijn Koolen, Ivan Cantádor

Publikation: Bidrag til tidsskriftKonferenceartikel i tidsskriftForskningpeer review

191 Downloads (Pure)

Resumé

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 aimed to address this by providing a dedicated venue for papers dedicated to all aspects of content-based recommender systems.
OriginalsprogEngelsk
TidsskriftSIGIR Forum
Vol/bind49
Udgave nummer1
Sider (fra-til)20-26
Antal sider7
ISSN0163-5840
StatusUdgivet - jun. 2015
BegivenhedRecSys 2014: 8th ACM Conference on Recommender Systems - Foster City, CA, USA
Varighed: 6 okt. 201410 okt. 2014

Konference

KonferenceRecSys 2014
LandUSA
ByFoster City, CA
Periode06/10/201410/10/2014

Fingerprint

Collaborative filtering
Recommender systems
Metadata
Websites

Citer dette

@inproceedings{3eb489a03fd74767be67fab69c510e06,
title = "Report on RecSys 2014 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 aimed to address this by providing a dedicated venue for papers dedicated to all aspects of content-based recommender systems.",
keywords = "content-based recommendation, recommender systems",
author = "Toine Bogers and Marijn Koolen and Ivan Cant{\'a}dor",
year = "2015",
month = "6",
language = "English",
volume = "49",
pages = "20--26",
journal = "SIGIR Forum",
issn = "0163-5840",
publisher = "Association for Computing Machinery",
number = "1",

}

Report on RecSys 2014 Workshop on New Trends in Content-Based Recommender Systems (CBRecSys 2014). / Bogers, Toine; Koolen, Marijn; Cantádor, Ivan.

I: SIGIR Forum, Bind 49, Nr. 1, 06.2015, s. 20-26.

Publikation: Bidrag til tidsskriftKonferenceartikel i tidsskriftForskningpeer review

TY - GEN

T1 - Report on RecSys 2014 Workshop on New Trends in Content-Based Recommender Systems (CBRecSys 2014)

AU - Bogers, Toine

AU - Koolen, Marijn

AU - Cantádor, Ivan

PY - 2015/6

Y1 - 2015/6

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 aimed to address this by providing a dedicated venue for papers dedicated to all aspects of content-based recommender systems.

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 aimed to address this by providing a dedicated venue for papers dedicated to all aspects of content-based recommender systems.

KW - content-based recommendation

KW - recommender systems

M3 - Conference article in Journal

VL - 49

SP - 20

EP - 26

JO - SIGIR Forum

JF - SIGIR Forum

SN - 0163-5840

IS - 1

ER -