CBRecSys 2016. New Trends on Content-Based Recommender Systems: Proceedings of the 3rd Workshop on New Trends on Content-Based Recommender Systems co-located with 10th ACM Conference on Recommender Systems (RecSys 2016)

Toine Bogers (Redaktør), Pasquale Lops (Redaktør), Marijn Koolen (Redaktør), Cataldo Musto (Redaktør), Giovanni Semeraro (Redaktør)

Publikation: Bog/antologi/afhandling/rapportAntologiForskningpeer review

388 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 2016 workshop provides a dedicated venue for papers dedicated to all aspects of content-based recommendation.
OriginalsprogEngelsk
ForlagCEUR Workshop Proceedings
Antal sider50
StatusUdgivet - 1 sep. 2016
BegivenhedRecSys 2016: 10th ACM Conference on Recommender Systems - Boston, MA, USA
Varighed: 15 sep. 201619 sep. 2016
https://recsys.acm.org/recsys16/
NavnCEUR Workshop Proceedings
Vol/bind1673
ISSN1613-0073

Konference

KonferenceRecSys 2016
LandUSA
ByBoston, MA
Periode15/09/201619/09/2016
Internetadresse

Fingerprint

Collaborative filtering
Recommender systems
Metadata
Websites

Citer dette

Bogers, Toine (Redaktør) ; Lops, Pasquale (Redaktør) ; Koolen, Marijn (Redaktør) ; Musto, Cataldo (Redaktør) ; Semeraro, Giovanni (Redaktør). / CBRecSys 2016. New Trends on Content-Based Recommender Systems : Proceedings of the 3rd Workshop on New Trends on Content-Based Recommender Systems co-located with 10th ACM Conference on Recommender Systems (RecSys 2016). CEUR Workshop Proceedings, 2016. 50 s. (CEUR Workshop Proceedings, Bind 1673).
@book{4a66324239be4536862095555701bd27,
title = "CBRecSys 2016. New Trends on Content-Based Recommender Systems: Proceedings of the 3rd Workshop on New Trends on Content-Based Recommender Systems co-located with 10th ACM Conference on Recommender Systems (RecSys 2016)",
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 2016 workshop provides a dedicated venue for papers dedicated to all aspects of content-based recommendation.",
keywords = "recommender systems, content-based recommendation, text reviews, user-generated content, implicit feedback, semantics, context",
editor = "Toine Bogers and Pasquale Lops and Marijn Koolen and Cataldo Musto and Giovanni Semeraro",
year = "2016",
month = "9",
day = "1",
language = "English",
series = "CEUR Workshop Proceedings",
publisher = "CEUR Workshop Proceedings",

}

CBRecSys 2016. New Trends on Content-Based Recommender Systems : Proceedings of the 3rd Workshop on New Trends on Content-Based Recommender Systems co-located with 10th ACM Conference on Recommender Systems (RecSys 2016). / Bogers, Toine (Redaktør); Lops, Pasquale (Redaktør); Koolen, Marijn (Redaktør); Musto, Cataldo (Redaktør); Semeraro, Giovanni (Redaktør).

CEUR Workshop Proceedings, 2016. 50 s. (CEUR Workshop Proceedings, Bind 1673).

Publikation: Bog/antologi/afhandling/rapportAntologiForskningpeer review

TY - BOOK

T1 - CBRecSys 2016. New Trends on Content-Based Recommender Systems

T2 - Proceedings of the 3rd Workshop on New Trends on Content-Based Recommender Systems co-located with 10th ACM Conference on Recommender Systems (RecSys 2016)

A2 - Bogers, Toine

A2 - Lops, Pasquale

A2 - Koolen, Marijn

A2 - Musto, Cataldo

A2 - Semeraro, Giovanni

PY - 2016/9/1

Y1 - 2016/9/1

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 2016 workshop provides 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 2016 workshop provides a dedicated venue for papers dedicated to all aspects of content-based recommendation.

KW - recommender systems

KW - content-based recommendation

KW - text reviews

KW - user-generated content

KW - implicit feedback

KW - semantics

KW - context

M3 - Anthology

T3 - CEUR Workshop Proceedings

BT - CBRecSys 2016. New Trends on Content-Based Recommender Systems

PB - CEUR Workshop Proceedings

ER -