Recommenders Benchmark Framework

Aviram Dayan; Guy Katz; Karl Heinz Lüke; Lior Rokach; Bracha Shapira; Roland Schwaiger; Aykan Aydin; Radmila Fishel; Nassem Biadsy

Recommenders Benchmark Framework

Aviram Dayan, Guy Katz, Karl Heinz Lüke, Lior Rokach, Bracha Shapira, Roland Schwaiger, Aykan Aydin, Radmila Fishel, Nassem Biadsy

Department of Software and Information Systems Engineering

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

Abstract

Recommender Systems are software tools and techniques providing suggestions for items to be of use to a user. Recommender systems have proven to be a valuable means for online users to cope with the virtual information overload and have become one of the most powerful and popular tools in electronic commerce. Correspondingly, various techniques for recommendation generation have been proposed during the last decade. In this paper we present a new benchmark framework. It allows researchers or practitioners to quickly try out and compare different recommendation methods on new data sets. Extending the framework is easy thanks to a simple and well-defined Application Programming Interface (API). It contains a plug-in mechanism allowing others to develop their own algorithms and incorporate them in the framework. An interactive graphical user interface is provided for setting new benchmarks, integrate new plug-ins with the framework, setting up configurations and exploring benchmark results.

Original language	English
Title of host publication	11th International Conference on Innovative Internet Community Services, I2CS 2011 - Proceedings
Editors	Gerald Eichler, Axel Kupper, Volkmar Schau, Hacene Fouchal, Herwig Unger
Publisher	Gesellschaft fur Informatik (GI)
Pages	115-126
Number of pages	12
ISBN (Electronic)	9783885792802
State	Published - 1 Jan 2011
Event	11th International Conference on Innovative Internet Community Services, I2CS 2011 - Berlin, Germany Duration: 15 Jun 2011 → 17 Jun 2011

Publication series

Name	Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)
Volume	P-186
ISSN (Print)	1617-5468

Conference

Conference	11th International Conference on Innovative Internet Community Services, I2CS 2011
Country/Territory	Germany
City	Berlin
Period	15/06/11 → 17/06/11

Keywords

Data Visualization
E-commerce
Information Retrieval
Machine Learning Software
Recommender Systems

ASJC Scopus subject areas

Computer Science Applications

Cite this

Dayan, A., Katz, G., Lüke, K. H., Rokach, L., Shapira, B., Schwaiger, R., Aydin, A., Fishel, R., & Biadsy, N. (2011). Recommenders Benchmark Framework. In G. Eichler, A. Kupper, V. Schau, H. Fouchal, & H. Unger (Eds.), 11th International Conference on Innovative Internet Community Services, I2CS 2011 - Proceedings (pp. 115-126). (Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI); Vol. P-186). Gesellschaft fur Informatik (GI).

Dayan, Aviram ; Katz, Guy ; Lüke, Karl Heinz et al. / Recommenders Benchmark Framework. 11th International Conference on Innovative Internet Community Services, I2CS 2011 - Proceedings. editor / Gerald Eichler ; Axel Kupper ; Volkmar Schau ; Hacene Fouchal ; Herwig Unger. Gesellschaft fur Informatik (GI), 2011. pp. 115-126 (Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)).

@inproceedings{7ddff00c4e3c442984480b28c71e86bb,

title = "Recommenders Benchmark Framework",

abstract = "Recommender Systems are software tools and techniques providing suggestions for items to be of use to a user. Recommender systems have proven to be a valuable means for online users to cope with the virtual information overload and have become one of the most powerful and popular tools in electronic commerce. Correspondingly, various techniques for recommendation generation have been proposed during the last decade. In this paper we present a new benchmark framework. It allows researchers or practitioners to quickly try out and compare different recommendation methods on new data sets. Extending the framework is easy thanks to a simple and well-defined Application Programming Interface (API). It contains a plug-in mechanism allowing others to develop their own algorithms and incorporate them in the framework. An interactive graphical user interface is provided for setting new benchmarks, integrate new plug-ins with the framework, setting up configurations and exploring benchmark results.",

keywords = "Data Visualization, E-commerce, Information Retrieval, Machine Learning Software, Recommender Systems",

author = "Aviram Dayan and Guy Katz and L{\"u}ke, {Karl Heinz} and Lior Rokach and Bracha Shapira and Roland Schwaiger and Aykan Aydin and Radmila Fishel and Nassem Biadsy",

note = "Publisher Copyright: {\textcopyright} 2011 Gesellschaft fur Informatik (GI). All rights reserved.; 11th International Conference on Innovative Internet Community Services, I2CS 2011 ; Conference date: 15-06-2011 Through 17-06-2011",

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language = "English",

series = "Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)",

publisher = "Gesellschaft fur Informatik (GI)",

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}

Dayan, A, Katz, G, Lüke, KH, Rokach, L , Shapira, B, Schwaiger, R, Aydin, A, Fishel, R & Biadsy, N 2011, Recommenders Benchmark Framework. in G Eichler, A Kupper, V Schau, H Fouchal & H Unger (eds), 11th International Conference on Innovative Internet Community Services, I2CS 2011 - Proceedings. Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI), vol. P-186, Gesellschaft fur Informatik (GI), pp. 115-126, 11th International Conference on Innovative Internet Community Services, I2CS 2011, Berlin, Germany, 15/06/11.

Recommenders Benchmark Framework. / Dayan, Aviram; Katz, Guy; Lüke, Karl Heinz et al.
11th International Conference on Innovative Internet Community Services, I2CS 2011 - Proceedings. ed. / Gerald Eichler; Axel Kupper; Volkmar Schau; Hacene Fouchal; Herwig Unger. Gesellschaft fur Informatik (GI), 2011. p. 115-126 (Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI); Vol. P-186).

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

TY - GEN

T1 - Recommenders Benchmark Framework

AU - Dayan, Aviram

AU - Katz, Guy

AU - Lüke, Karl Heinz

AU - Rokach, Lior

AU - Shapira, Bracha

AU - Schwaiger, Roland

AU - Aydin, Aykan

AU - Fishel, Radmila

AU - Biadsy, Nassem

PY - 2011/1/1

Y1 - 2011/1/1

N2 - Recommender Systems are software tools and techniques providing suggestions for items to be of use to a user. Recommender systems have proven to be a valuable means for online users to cope with the virtual information overload and have become one of the most powerful and popular tools in electronic commerce. Correspondingly, various techniques for recommendation generation have been proposed during the last decade. In this paper we present a new benchmark framework. It allows researchers or practitioners to quickly try out and compare different recommendation methods on new data sets. Extending the framework is easy thanks to a simple and well-defined Application Programming Interface (API). It contains a plug-in mechanism allowing others to develop their own algorithms and incorporate them in the framework. An interactive graphical user interface is provided for setting new benchmarks, integrate new plug-ins with the framework, setting up configurations and exploring benchmark results.

AB - Recommender Systems are software tools and techniques providing suggestions for items to be of use to a user. Recommender systems have proven to be a valuable means for online users to cope with the virtual information overload and have become one of the most powerful and popular tools in electronic commerce. Correspondingly, various techniques for recommendation generation have been proposed during the last decade. In this paper we present a new benchmark framework. It allows researchers or practitioners to quickly try out and compare different recommendation methods on new data sets. Extending the framework is easy thanks to a simple and well-defined Application Programming Interface (API). It contains a plug-in mechanism allowing others to develop their own algorithms and incorporate them in the framework. An interactive graphical user interface is provided for setting new benchmarks, integrate new plug-ins with the framework, setting up configurations and exploring benchmark results.

KW - Data Visualization

KW - E-commerce

KW - Information Retrieval

KW - Machine Learning Software

KW - Recommender Systems

UR - http://www.scopus.com/inward/record.url?scp=85134434435&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:85134434435

T3 - Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)

SP - 115

EP - 126

BT - 11th International Conference on Innovative Internet Community Services, I2CS 2011 - Proceedings

A2 - Eichler, Gerald

A2 - Kupper, Axel

A2 - Schau, Volkmar

A2 - Fouchal, Hacene

A2 - Unger, Herwig

PB - Gesellschaft fur Informatik (GI)

T2 - 11th International Conference on Innovative Internet Community Services, I2CS 2011

Y2 - 15 June 2011 through 17 June 2011

ER -

Dayan A, Katz G, Lüke KH, Rokach L , Shapira B, Schwaiger R et al. Recommenders Benchmark Framework. In Eichler G, Kupper A, Schau V, Fouchal H, Unger H, editors, 11th International Conference on Innovative Internet Community Services, I2CS 2011 - Proceedings. Gesellschaft fur Informatik (GI). 2011. p. 115-126. (Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)).

Recommenders Benchmark Framework

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

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