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 Hebrew University of Jerusalem, Ben-Gurion University of the Negev

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

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 - 6 Dec 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

All Science Journal Classification (ASJC) codes

Computer Graphics and Computer-Aided Design
Information Systems

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",

month = dec,

day = "6",

doi = "10.1145/2043932.2044003",

language = "الإنجليزيّة",

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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T1 - Recommenders benchmark framework.

AU - Dayan, Aviram

AU - Katz, Guy

AU - Biasdi, Naseem

AU - Rokach, Lior

AU - Shapira, Bracha

AU - Aydin, Aykan

AU - Schwaiger, Roland

AU - Fishel, Radmila

N1 - Conference code: 5

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AB - 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.

KW - benchmark

KW - dataset characteristics.

KW - datasets

KW - evaluators

KW - metrics

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M3 - منشور من مؤتمر

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SN - 9781450306836

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BT - Proceedings of the 2011 ACM Conference on Recommender Systems, RecSys 2011

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ER -

Recommenders benchmark framework.

Abstract

Publication series

Conference

Keywords

All Science Journal Classification (ASJC) codes

Access to Document

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Cite this