Comparing and evaluating information retrieval algorithms for news recommendation

Toine Bogers; Antal Van Den Bosch

doi:10.1145/1297231.1297256

Comparing and evaluating information retrieval algorithms for news recommendation

Toine Bogers, Antal Van Den Bosch

Publikation: Konference artikel i Proceeding eller bog/rapport kapitel › Konferencebidrag i proceedings › Forskning › peer review

Abstract

In this paper, we argue that the performance of content-based news recommender systems has been hampered by using relatively old and simple matching algorithms. Using more current probabilistic retrieval algorithms results in significant performance boosts. We test our ideas on a test collection that we have made publicly available. We perform both binary and graded evaluation of our algorithms and argue for the need for more graded evaluation of content-based recommender systems.

Originalsprog	Engelsk
Titel	RecSys'07 : Proceedings of the 2007 ACM Conference on Recommender Systems
Antal sider	4
Publikationsdato	1 dec. 2007
Sider	141-144
ISBN (Trykt)	9781595937308
DOI	https://doi.org/10.1145/1297231.1297256
Status	Udgivet - 1 dec. 2007
Udgivet eksternt	Ja
Begivenhed	RecSys'07: 2007 1st ACM Conference on Recommender Systems - Minneapolis, MN, USA Varighed: 19 okt. 2007 → 20 okt. 2007

Konference

Konference	RecSys'07: 2007 1st ACM Conference on Recommender Systems
Land/Område	USA
By	Minneapolis, MN
Periode	19/10/2007 → 20/10/2007
Sponsor

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10.1145/1297231.1297256

Citationsformater

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title = "Comparing and evaluating information retrieval algorithms for news recommendation",

abstract = "In this paper, we argue that the performance of content-based news recommender systems has been hampered by using relatively old and simple matching algorithms. Using more current probabilistic retrieval algorithms results in significant performance boosts. We test our ideas on a test collection that we have made publicly available. We perform both binary and graded evaluation of our algorithms and argue for the need for more graded evaluation of content-based recommender systems.",

keywords = "Content-based recommender systems, Probabilistic retrieval algorithms, Performance evaluation, Graded evaluation, Information retrieval",

author = "Toine Bogers and {Van Den Bosch}, Antal",

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AU - Van Den Bosch, Antal

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AB - In this paper, we argue that the performance of content-based news recommender systems has been hampered by using relatively old and simple matching algorithms. Using more current probabilistic retrieval algorithms results in significant performance boosts. We test our ideas on a test collection that we have made publicly available. We perform both binary and graded evaluation of our algorithms and argue for the need for more graded evaluation of content-based recommender systems.

KW - Content-based recommender systems

KW - Probabilistic retrieval algorithms

KW - Performance evaluation

KW - Graded evaluation

KW - Information retrieval

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M3 - Article in proceedings

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BT - RecSys'07

T2 - RecSys'07: 2007 1st ACM Conference on Recommender Systems

Y2 - 19 October 2007 through 20 October 2007

ER -

Comparing and evaluating information retrieval algorithms for news recommendation

Abstract

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