Play it again, sam! recommending familiar music in fresh ways

Giovanni Gabbolini; Derek Bridge

doi:10.1145/3460231.3478866

Play it again, sam! recommending familiar music in fresh ways

Giovanni Gabbolini
, Derek Bridge

University College Cork

Research output: Chapter in Book/Report/Conference proceedings › Chapter › peer-review

Abstract

In the music domain, repeated consumption is not uncommon. In this work, we explore how to recommend familiar music in fresh ways. Specifically, we design algorithms that can produce 'tours' through a small personal collection of songs. The tours are decorated with segues, which are textual connections between consecutive songs, chosen for their interestingness. We present three such algorithms, and we outline their strengths and weaknesses based on a comparative offline evaluation. This preliminary algorithmic work is a prelude to upcoming user-centric investigations.

Original language	English
Title of host publication	RecSys 2021 - 15th ACM Conference on Recommender Systems
Publisher	Association for Computing Machinery, Inc
Pages	697-701
Number of pages	5
ISBN (Electronic)	9781450384582
DOIs	https://doi.org/10.1145/3460231.3478866
Publication status	Published - 13 Sep 2021
Event	15th ACM Conference on Recommender Systems, RecSys 2021 - Virtual, Online, Netherlands Duration: 27 Sep 2021 → 1 Oct 2021

Publication series

Name	RecSys 2021 - 15th ACM Conference on Recommender Systems

Conference

Conference	15th ACM Conference on Recommender Systems, RecSys 2021
Country/Territory	Netherlands
City	Virtual, Online
Period	27/09/21 → 1/10/21

Keywords

Recommender systems
Repeated consumption
Segues

Access to Document

10.1145/3460231.3478866

Cite this

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title = "Play it again, sam! recommending familiar music in fresh ways",

abstract = "In the music domain, repeated consumption is not uncommon. In this work, we explore how to recommend familiar music in fresh ways. Specifically, we design algorithms that can produce 'tours' through a small personal collection of songs. The tours are decorated with segues, which are textual connections between consecutive songs, chosen for their interestingness. We present three such algorithms, and we outline their strengths and weaknesses based on a comparative offline evaluation. This preliminary algorithmic work is a prelude to upcoming user-centric investigations.",

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year = "2021",

month = sep,

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doi = "10.1145/3460231.3478866",

language = "English",

series = "RecSys 2021 - 15th ACM Conference on Recommender Systems",

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}

Gabbolini, G & Bridge, D 2021, Play it again, sam! recommending familiar music in fresh ways. in RecSys 2021 - 15th ACM Conference on Recommender Systems. RecSys 2021 - 15th ACM Conference on Recommender Systems, Association for Computing Machinery, Inc, pp. 697-701, 15th ACM Conference on Recommender Systems, RecSys 2021, Virtual, Online, Netherlands, 27/09/21. https://doi.org/10.1145/3460231.3478866

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AB - In the music domain, repeated consumption is not uncommon. In this work, we explore how to recommend familiar music in fresh ways. Specifically, we design algorithms that can produce 'tours' through a small personal collection of songs. The tours are decorated with segues, which are textual connections between consecutive songs, chosen for their interestingness. We present three such algorithms, and we outline their strengths and weaknesses based on a comparative offline evaluation. This preliminary algorithmic work is a prelude to upcoming user-centric investigations.

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KW - Repeated consumption

KW - Segues

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DO - 10.1145/3460231.3478866

M3 - Chapter

AN - SCOPUS:85115619789

T3 - RecSys 2021 - 15th ACM Conference on Recommender Systems

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BT - RecSys 2021 - 15th ACM Conference on Recommender Systems

PB - Association for Computing Machinery, Inc

T2 - 15th ACM Conference on Recommender Systems, RecSys 2021

Y2 - 27 September 2021 through 1 October 2021

ER -

Play it again, sam! recommending familiar music in fresh ways

Abstract

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Keywords

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