Third workshop on recommendation in complex scenarios (ComplexreC 2019)

Marijn Koolen; Bamshad Mobasher; Toine Bogers; Alexander Tuzhilin

doi:10.1145/3298689.3346948

Third workshop on recommendation in complex scenarios (ComplexreC 2019)

Marijn Koolen, Bamshad Mobasher, Toine Bogers, Alexander Tuzhilin

HUC - Digital Infrastructure

Research output: Contribution to conference › Paper › Scientific › peer-review

Abstract

Over the past decade, recommendation algorithms for ratings prediction and item ranking have steadily matured. However, these state-of-the-art algorithms are typically applied in relatively straightforward and static scenarios: given information about a user's past item preferences in isolation, can we predict whether they will like a new item or rank all unseen items based on predicted interest? In reality, recommendation is often a more complex problem: the evaluation of a list of recommended items never takes place in a vacuum, and it is often a single step in the user's more complex background task or need. The goal of the ComplexRec 2019 workshop is to offer an interactive venue for discussing approaches to recommendation in complex scenarios that have no simple one-size-fits-all solution.

Original language	English
Pages	550
Number of pages	2
DOIs	https://doi.org/10.1145/3298689.3346948
Publication status	Published - 2019

Keywords

Complex recommendation

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10.1145/3298689.3346948

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title = "Third workshop on recommendation in complex scenarios (ComplexreC 2019)",

abstract = "Over the past decade, recommendation algorithms for ratings prediction and item ranking have steadily matured. However, these state-of-the-art algorithms are typically applied in relatively straightforward and static scenarios: given information about a user's past item preferences in isolation, can we predict whether they will like a new item or rank all unseen items based on predicted interest? In reality, recommendation is often a more complex problem: the evaluation of a list of recommended items never takes place in a vacuum, and it is often a single step in the user's more complex background task or need. The goal of the ComplexRec 2019 workshop is to offer an interactive venue for discussing approaches to recommendation in complex scenarios that have no simple one-size-fits-all solution.",

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author = "Marijn Koolen and Bamshad Mobasher and Toine Bogers and Alexander Tuzhilin",

year = "2019",

doi = "10.1145/3298689.3346948",

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T1 - Third workshop on recommendation in complex scenarios (ComplexreC 2019)

AU - Koolen, Marijn

AU - Mobasher, Bamshad

AU - Bogers, Toine

AU - Tuzhilin, Alexander

PY - 2019

Y1 - 2019

N2 - Over the past decade, recommendation algorithms for ratings prediction and item ranking have steadily matured. However, these state-of-the-art algorithms are typically applied in relatively straightforward and static scenarios: given information about a user's past item preferences in isolation, can we predict whether they will like a new item or rank all unseen items based on predicted interest? In reality, recommendation is often a more complex problem: the evaluation of a list of recommended items never takes place in a vacuum, and it is often a single step in the user's more complex background task or need. The goal of the ComplexRec 2019 workshop is to offer an interactive venue for discussing approaches to recommendation in complex scenarios that have no simple one-size-fits-all solution.

AB - Over the past decade, recommendation algorithms for ratings prediction and item ranking have steadily matured. However, these state-of-the-art algorithms are typically applied in relatively straightforward and static scenarios: given information about a user's past item preferences in isolation, can we predict whether they will like a new item or rank all unseen items based on predicted interest? In reality, recommendation is often a more complex problem: the evaluation of a list of recommended items never takes place in a vacuum, and it is often a single step in the user's more complex background task or need. The goal of the ComplexRec 2019 workshop is to offer an interactive venue for discussing approaches to recommendation in complex scenarios that have no simple one-size-fits-all solution.

KW - Complex recommendation

UR - http://www.mendeley.com/research/third-workshop-recommendation-complex-scenarios-complexrec-2019-1

U2 - 10.1145/3298689.3346948

DO - 10.1145/3298689.3346948

M3 - Paper

SP - 550

ER -

Third workshop on recommendation in complex scenarios (ComplexreC 2019)

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Keywords

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