A distributed hybrid recommendation framework to address the new-user cold-start problem

Jenq Haur Wang; Yi Hao Chen

doi:10.1109/UIC-ATC-ScalCom-CBDCom-IoP.2015.307

A distributed hybrid recommendation framework to address the new-user cold-start problem

Jenq Haur Wang
, Yi Hao Chen

Department of Computer Science and Information Engineering

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

9 Scopus citations

Abstract

With the development of electronic commerce, recommender system is becoming an important research topic. Existing methods of recommender systems such as collaborative filtering and content analysis are suitable for different cases. Not every recommender system is capable of handling all kinds of situations. In this paper, we bring forward a distributed hybrid recommendation framework to address the new-user cold-start problem based on user classification. First, current user characteristics, user context and operating records are used to classify the user type. Then, suitable recommendation algorithms are dynamically selected based on the current user type, and executed in parallel. Finally, the recommendation results are merged into a consolidated list. In the experiment on movie ratings dataset Movie Lens, the proposed framework can enhance the accuracy of recommendation system. Also, a 100% coverage can be achieved in the case of new users. This shows the potential of the proposed framework in addressing new-user cold-start problem.

Original language	English
Title of host publication	Proceedings - 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing, 2015 IEEE 12th International Conference on Advanced and Trusted Computing, 2015 IEEE 15th International Conference on Scalable Computing and Communications, 2015 IEEE International Conference on Cloud and Big Data Computing, 2015 IEEE International Conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015
Editors	Jianhua Ma, Ali Li, Huansheng Ning, Laurence T. Yang
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1686-1691
Number of pages	6
ISBN (Electronic)	9781467372114
DOIs	https://doi.org/10.1109/UIC-ATC-ScalCom-CBDCom-IoP.2015.307
State	Published - 20 Jul 2016
Event	Proceedings - 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing, 2015 IEEE 12th International Conference on Advanced and Trusted Computing, 2015 IEEE 15th International Conference on Scalable Computing and Communications, 2015 IEEE International Conference on Cloud and Big Data Computing, 2015 IEEE International Conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015 - Beijing, China Duration: 10 Aug 2015 → 14 Aug 2015

Publication series

Name

Proceedings - 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing, 2015 IEEE 12th International Conference on Advanced and Trusted Computing, 2015 IEEE 15th International Conference on Scalable Computing and Communications, 2015 IEEE International Conference on Cloud and Big Data Computing, 2015 IEEE International Conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015

Conference

Conference	Proceedings - 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing, 2015 IEEE 12th International Conference on Advanced and Trusted Computing, 2015 IEEE 15th International Conference on Scalable Computing and Communications, 2015 IEEE International Conference on Cloud and Big Data Computing, 2015 IEEE International Conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015
Country/Territory	China
City	Beijing
Period	10/08/15 → 14/08/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Keywords

New-user cold-start problem
Recommender systems
User classification

Access to Document

10.1109/UIC-ATC-ScalCom-CBDCom-IoP.2015.307

Cite this

Wang, J. H., & Chen, Y. H. (2016). A distributed hybrid recommendation framework to address the new-user cold-start problem. In J. Ma, A. Li, H. Ning, & L. T. Yang (Eds.), Proceedings - 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing, 2015 IEEE 12th International Conference on Advanced and Trusted Computing, 2015 IEEE 15th International Conference on Scalable Computing and Communications, 2015 IEEE International Conference on Cloud and Big Data Computing, 2015 IEEE International Conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015 (pp. 1686-1691). Article 7518488 (Proceedings - 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing, 2015 IEEE 12th International Conference on Advanced and Trusted Computing, 2015 IEEE 15th International Conference on Scalable Computing and Communications, 2015 IEEE International Conference on Cloud and Big Data Computing, 2015 IEEE International Conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/UIC-ATC-ScalCom-CBDCom-IoP.2015.307

Wang, Jenq Haur ; Chen, Yi Hao. / A distributed hybrid recommendation framework to address the new-user cold-start problem. Proceedings - 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing, 2015 IEEE 12th International Conference on Advanced and Trusted Computing, 2015 IEEE 15th International Conference on Scalable Computing and Communications, 2015 IEEE International Conference on Cloud and Big Data Computing, 2015 IEEE International Conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015. editor / Jianhua Ma ; Ali Li ; Huansheng Ning ; Laurence T. Yang. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 1686-1691 (Proceedings - 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing, 2015 IEEE 12th International Conference on Advanced and Trusted Computing, 2015 IEEE 15th International Conference on Scalable Computing and Communications, 2015 IEEE International Conference on Cloud and Big Data Computing, 2015 IEEE International Conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015).

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abstract = "With the development of electronic commerce, recommender system is becoming an important research topic. Existing methods of recommender systems such as collaborative filtering and content analysis are suitable for different cases. Not every recommender system is capable of handling all kinds of situations. In this paper, we bring forward a distributed hybrid recommendation framework to address the new-user cold-start problem based on user classification. First, current user characteristics, user context and operating records are used to classify the user type. Then, suitable recommendation algorithms are dynamically selected based on the current user type, and executed in parallel. Finally, the recommendation results are merged into a consolidated list. In the experiment on movie ratings dataset Movie Lens, the proposed framework can enhance the accuracy of recommendation system. Also, a 100\% coverage can be achieved in the case of new users. This shows the potential of the proposed framework in addressing new-user cold-start problem.",

keywords = "New-user cold-start problem, Recommender systems, User classification",

author = "Wang, \{Jenq Haur\} and Chen, \{Yi Hao\}",

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booktitle = "Proceedings - 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing, 2015 IEEE 12th International Conference on Advanced and Trusted Computing, 2015 IEEE 15th International Conference on Scalable Computing and Communications, 2015 IEEE International Conference on Cloud and Big Data Computing, 2015 IEEE International Conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015",

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Wang, JH & Chen, YH 2016, A distributed hybrid recommendation framework to address the new-user cold-start problem. in J Ma, A Li, H Ning & LT Yang (eds), Proceedings - 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing, 2015 IEEE 12th International Conference on Advanced and Trusted Computing, 2015 IEEE 15th International Conference on Scalable Computing and Communications, 2015 IEEE International Conference on Cloud and Big Data Computing, 2015 IEEE International Conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015., 7518488, Proceedings - 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing, 2015 IEEE 12th International Conference on Advanced and Trusted Computing, 2015 IEEE 15th International Conference on Scalable Computing and Communications, 2015 IEEE International Conference on Cloud and Big Data Computing, 2015 IEEE International Conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015, Institute of Electrical and Electronics Engineers Inc., pp. 1686-1691, Proceedings - 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing, 2015 IEEE 12th International Conference on Advanced and Trusted Computing, 2015 IEEE 15th International Conference on Scalable Computing and Communications, 2015 IEEE International Conference on Cloud and Big Data Computing, 2015 IEEE International Conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015, Beijing, China, 10/08/15. https://doi.org/10.1109/UIC-ATC-ScalCom-CBDCom-IoP.2015.307

A distributed hybrid recommendation framework to address the new-user cold-start problem. / Wang, Jenq Haur; Chen, Yi Hao.
Proceedings - 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing, 2015 IEEE 12th International Conference on Advanced and Trusted Computing, 2015 IEEE 15th International Conference on Scalable Computing and Communications, 2015 IEEE International Conference on Cloud and Big Data Computing, 2015 IEEE International Conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015. ed. / Jianhua Ma; Ali Li; Huansheng Ning; Laurence T. Yang. Institute of Electrical and Electronics Engineers Inc., 2016. p. 1686-1691 7518488 (Proceedings - 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing, 2015 IEEE 12th International Conference on Advanced and Trusted Computing, 2015 IEEE 15th International Conference on Scalable Computing and Communications, 2015 IEEE International Conference on Cloud and Big Data Computing, 2015 IEEE International Conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015).

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

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AB - With the development of electronic commerce, recommender system is becoming an important research topic. Existing methods of recommender systems such as collaborative filtering and content analysis are suitable for different cases. Not every recommender system is capable of handling all kinds of situations. In this paper, we bring forward a distributed hybrid recommendation framework to address the new-user cold-start problem based on user classification. First, current user characteristics, user context and operating records are used to classify the user type. Then, suitable recommendation algorithms are dynamically selected based on the current user type, and executed in parallel. Finally, the recommendation results are merged into a consolidated list. In the experiment on movie ratings dataset Movie Lens, the proposed framework can enhance the accuracy of recommendation system. Also, a 100% coverage can be achieved in the case of new users. This shows the potential of the proposed framework in addressing new-user cold-start problem.

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Wang JH, Chen YH. A distributed hybrid recommendation framework to address the new-user cold-start problem. In Ma J, Li A, Ning H, Yang LT, editors, Proceedings - 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing, 2015 IEEE 12th International Conference on Advanced and Trusted Computing, 2015 IEEE 15th International Conference on Scalable Computing and Communications, 2015 IEEE International Conference on Cloud and Big Data Computing, 2015 IEEE International Conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015. Institute of Electrical and Electronics Engineers Inc. 2016. p. 1686-1691. 7518488. (Proceedings - 2015 IEEE 12th International Conference on Ubiquitous Intelligence and Computing, 2015 IEEE 12th International Conference on Advanced and Trusted Computing, 2015 IEEE 15th International Conference on Scalable Computing and Communications, 2015 IEEE International Conference on Cloud and Big Data Computing, 2015 IEEE International Conference on Internet of People and Associated Symposia/Workshops, UIC-ATC-ScalCom-CBDCom-IoP 2015). doi: 10.1109/UIC-ATC-ScalCom-CBDCom-IoP.2015.307

A distributed hybrid recommendation framework to address the new-user cold-start problem

Abstract

Publication series

Conference

Bibliographical note

Keywords

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