A collaborative filtering algorithm based on user activity level

Yongli Cui; Shubin Song; Liang He; Guorong Li

doi:10.1109/BIFE.2012.25

A collaborative filtering algorithm based on user activity level

Yongli Cui
, Shubin Song
, Liang He^*
, Guorong Li

^*Corresponding author for this work

School of Computer Science and Technology

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

3 Scopus citations

Abstract

Collaborative Filtering Algorithm is one of the most successful recommender technologies, and has been widely used in E-commerce. However, traditional Collaborative Filtering often focus on user-item ratings, but ignore the information implicated in user activity which means how and how often a user makes operations in a system, so it misses some important information to improve the prediction quality. To solve this problem, we bring user activity factor into collaborative filtering and propose a new collaborative filtering algorithm based on user activity level (UACF) . Finally, experiments have shown that our new algorithm UACF improves the precision of traditional collaborative filtering.

Original language	English
Title of host publication	Proceedings of the 2012 5th International Conference on Business Intelligence and Financial Engineering, BIFE 2012
Pages	80-83
Number of pages	4
DOIs	https://doi.org/10.1109/BIFE.2012.25
State	Published - 2012
Event	2012 5th International Conference on Business Intelligence and Financial Engineering, BIFE 2012 - Lanzhou, Gansu, China Duration: 18 Aug 2012 → 21 Aug 2012

Publication series

Name	Proceedings of the 2012 5th International Conference on Business Intelligence and Financial Engineering, BIFE 2012

Conference

Conference	2012 5th International Conference on Business Intelligence and Financial Engineering, BIFE 2012
Country/Territory	China
City	Lanzhou, Gansu
Period	18/08/12 → 21/08/12

Keywords

Collaborative filtering
Recommender system
User activity

Access to Document

10.1109/BIFE.2012.25

Cite this

Cui, Y., Song, S., He, L., & Li, G. (2012). A collaborative filtering algorithm based on user activity level. In Proceedings of the 2012 5th International Conference on Business Intelligence and Financial Engineering, BIFE 2012 (pp. 80-83). Article 6305084 (Proceedings of the 2012 5th International Conference on Business Intelligence and Financial Engineering, BIFE 2012). https://doi.org/10.1109/BIFE.2012.25

@inproceedings{1a86106057034a238a20689d54d899d4,

title = "A collaborative filtering algorithm based on user activity level",

abstract = "Collaborative Filtering Algorithm is one of the most successful recommender technologies, and has been widely used in E-commerce. However, traditional Collaborative Filtering often focus on user-item ratings, but ignore the information implicated in user activity which means how and how often a user makes operations in a system, so it misses some important information to improve the prediction quality. To solve this problem, we bring user activity factor into collaborative filtering and propose a new collaborative filtering algorithm based on user activity level (UACF) . Finally, experiments have shown that our new algorithm UACF improves the precision of traditional collaborative filtering.",

keywords = "Collaborative filtering, Recommender system, User activity",

author = "Yongli Cui and Shubin Song and Liang He and Guorong Li",

year = "2012",

doi = "10.1109/BIFE.2012.25",

language = "英语",

isbn = "9780769547503",

series = "Proceedings of the 2012 5th International Conference on Business Intelligence and Financial Engineering, BIFE 2012",

pages = "80--83",

booktitle = "Proceedings of the 2012 5th International Conference on Business Intelligence and Financial Engineering, BIFE 2012",

note = "2012 5th International Conference on Business Intelligence and Financial Engineering, BIFE 2012 ; Conference date: 18-08-2012 Through 21-08-2012",

}

Cui, Y, Song, S, He, L & Li, G 2012, A collaborative filtering algorithm based on user activity level. in Proceedings of the 2012 5th International Conference on Business Intelligence and Financial Engineering, BIFE 2012., 6305084, Proceedings of the 2012 5th International Conference on Business Intelligence and Financial Engineering, BIFE 2012, pp. 80-83, 2012 5th International Conference on Business Intelligence and Financial Engineering, BIFE 2012, Lanzhou, Gansu, China, 18/08/12. https://doi.org/10.1109/BIFE.2012.25

A collaborative filtering algorithm based on user activity level. / Cui, Yongli; Song, Shubin; He, Liang et al.
Proceedings of the 2012 5th International Conference on Business Intelligence and Financial Engineering, BIFE 2012. 2012. p. 80-83 6305084 (Proceedings of the 2012 5th International Conference on Business Intelligence and Financial Engineering, BIFE 2012).

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

TY - GEN

T1 - A collaborative filtering algorithm based on user activity level

AU - Cui, Yongli

AU - Song, Shubin

AU - He, Liang

AU - Li, Guorong

PY - 2012

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N2 - Collaborative Filtering Algorithm is one of the most successful recommender technologies, and has been widely used in E-commerce. However, traditional Collaborative Filtering often focus on user-item ratings, but ignore the information implicated in user activity which means how and how often a user makes operations in a system, so it misses some important information to improve the prediction quality. To solve this problem, we bring user activity factor into collaborative filtering and propose a new collaborative filtering algorithm based on user activity level (UACF) . Finally, experiments have shown that our new algorithm UACF improves the precision of traditional collaborative filtering.

AB - Collaborative Filtering Algorithm is one of the most successful recommender technologies, and has been widely used in E-commerce. However, traditional Collaborative Filtering often focus on user-item ratings, but ignore the information implicated in user activity which means how and how often a user makes operations in a system, so it misses some important information to improve the prediction quality. To solve this problem, we bring user activity factor into collaborative filtering and propose a new collaborative filtering algorithm based on user activity level (UACF) . Finally, experiments have shown that our new algorithm UACF improves the precision of traditional collaborative filtering.

KW - Collaborative filtering

KW - Recommender system

KW - User activity

UR - https://www.scopus.com/pages/publications/84868140985

U2 - 10.1109/BIFE.2012.25

DO - 10.1109/BIFE.2012.25

M3 - 会议稿件

AN - SCOPUS:84868140985

SN - 9780769547503

T3 - Proceedings of the 2012 5th International Conference on Business Intelligence and Financial Engineering, BIFE 2012

SP - 80

EP - 83

BT - Proceedings of the 2012 5th International Conference on Business Intelligence and Financial Engineering, BIFE 2012

T2 - 2012 5th International Conference on Business Intelligence and Financial Engineering, BIFE 2012

Y2 - 18 August 2012 through 21 August 2012

ER -

Cui Y, Song S, He L, Li G. A collaborative filtering algorithm based on user activity level. In Proceedings of the 2012 5th International Conference on Business Intelligence and Financial Engineering, BIFE 2012. 2012. p. 80-83. 6305084. (Proceedings of the 2012 5th International Conference on Business Intelligence and Financial Engineering, BIFE 2012). doi: 10.1109/BIFE.2012.25

A collaborative filtering algorithm based on user activity level

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