Recommenders benchmark framework.

Aviram Dayan; Guy Katz; Naseem Biasdi; Lior Rokach; Bracha Shapira; Aykan Aydin; Roland Schwaiger; Radmila Fishel

doi:10.1145/2043932.2044003

Recommenders benchmark framework.

Aviram Dayan, Guy Katz, Naseem Biasdi, Lior Rokach, Bracha Shapira, Aykan Aydin, Roland Schwaiger, Radmila Fishel

The Rachel and Selim Benin School of Engineering and Computer Science

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

3 Scopus citations

Abstract

In this demo we present a recommender benchmark framework that serves as an infrastructure for comparing and examining the performance and feasibility of different recommender algorithms on various datasets with a variety of measures. The extendable infrastructure aims to provide easy plugging of novel recommendation-algorithms, datasets and compare their performance using visual tools and metrics with other algorithms in the benchmark. It also aims at generating a WEKA-type workbench [1] for the recommender systems field to enable usage and application of common recommender systems (RS) algorithms for research and practice. The demo movie is available at: http://www.youtube.com/ watch?v=fsDITf6s0WY.

Original language	English
Title of host publication	Proceedings of the 2011 ACM Conference on Recommender Systems, RecSys 2011
Pages	353-354
Number of pages	2
DOIs	https://doi.org/10.1145/2043932.2044003
State	Published - 2011
Event	5th ACM Conference on Recommender Systems, RecSys 2011 - Chicago, United States Duration: 23 Oct 2011 → 27 Oct 2011 Conference number: 5 https://recsys.acm.org/recsys11/

Publication series

Name	RecSys'11 - Proceedings of the 5th ACM Conference on Recommender Systems

Conference

Conference	5th ACM Conference on Recommender Systems, RecSys 2011
Country/Territory	United States
City	Chicago
Period	23/10/11 → 27/10/11
Internet address	https://recsys.acm.org/recsys11/

Keywords

benchmark
dataset characteristics.
datasets
evaluators
metrics
recommendation engines

Access to Document

10.1145/2043932.2044003License: Unspecified

https://dblp.org/rec/conf/recsys/DayanKBRSASF11.htmlLicense: Unspecified

Cite this

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title = "Recommenders benchmark framework.",

abstract = "In this demo we present a recommender benchmark framework that serves as an infrastructure for comparing and examining the performance and feasibility of different recommender algorithms on various datasets with a variety of measures. The extendable infrastructure aims to provide easy plugging of novel recommendation-algorithms, datasets and compare their performance using visual tools and metrics with other algorithms in the benchmark. It also aims at generating a WEKA-type workbench [1] for the recommender systems field to enable usage and application of common recommender systems (RS) algorithms for research and practice. The demo movie is available at: http://www.youtube.com/ watch?v=fsDITf6s0WY.",

keywords = "benchmark, dataset characteristics., datasets, evaluators, metrics, recommendation engines",

author = "Aviram Dayan and Guy Katz and Naseem Biasdi and Lior Rokach and Bracha Shapira and Aykan Aydin and Roland Schwaiger and Radmila Fishel",

year = "2011",

doi = "10.1145/2043932.2044003",

language = "אנגלית",

isbn = "978-1-4503-0683-6",

series = "RecSys'11 - Proceedings of the 5th ACM Conference on Recommender Systems",

pages = "353--354",

booktitle = "Proceedings of the 2011 ACM Conference on Recommender Systems, RecSys 2011",

note = "5th ACM Conference on Recommender Systems, RecSys 2011 ; Conference date: 23-10-2011 Through 27-10-2011",

url = "https://recsys.acm.org/recsys11/",

}

Dayan, A, Katz, G, Biasdi, N, Rokach, L, Shapira, B, Aydin, A, Schwaiger, R & Fishel, R 2011, Recommenders benchmark framework. in Proceedings of the 2011 ACM Conference on Recommender Systems, RecSys 2011. RecSys'11 - Proceedings of the 5th ACM Conference on Recommender Systems, pp. 353-354, 5th ACM Conference on Recommender Systems, RecSys 2011, Chicago, Illinois, United States, 23/10/11. https://doi.org/10.1145/2043932.2044003

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AU - Katz, Guy

AU - Biasdi, Naseem

AU - Rokach, Lior

AU - Shapira, Bracha

AU - Aydin, Aykan

AU - Schwaiger, Roland

AU - Fishel, Radmila

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KW - benchmark

KW - dataset characteristics.

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KW - metrics

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ER -

Recommenders benchmark framework.

Abstract

Publication series

Conference

Keywords

Access to Document

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