Hybrid Recommendation Base on Learning to Rank

Bin Xie; Xinhuai Tang; Feilong Tang

doi:10.1109/IMIS.2015.13

Hybrid Recommendation Base on Learning to Rank

Bin Xie
, Xinhuai Tang
, Feilong Tang

Nanjing University of Science and Technology
Shanghai Jiao Tong University

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

3 引用（Scopus）

摘要

In order to solve the problem of recommender system using in different scenarios and the ranking of recommendation result, we propose a method using learning to rank for hybrid recommendation. It uses boosting merging algorithm as the base model, Lambda MART algorithm for updating. This makes our ranking model can be updated in real time based on user feedback information. By learning different data from different scenarios, the recommender system can be applied to different applications. In the end, we experiment our hybrid recommendation model by ranking evaluation NDCG.

源语言	英语
主期刊名	Proceedings - 2015 9th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2015
编辑	Francesco Palmieri, Leonard Barolli, Helio Dos Santos Silva, Hsing-Chung Chen
出版商	Institute of Electrical and Electronics Engineers Inc.
页	53-57
页数	5
ISBN（电子版）	9781479988730
DOI	https://doi.org/10.1109/IMIS.2015.13
出版状态	已出版 - 30 9月 2015
已对外发布	是
活动	9th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2015 - Blumenau, Santa Catarina, 巴西期限: 8 7月 2015 → 10 7月 2015

出版系列

姓名	Proceedings - 2015 9th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2015

会议

会议	9th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2015
国家/地区	巴西
市	Blumenau, Santa Catarina
时期	8/07/15 → 10/07/15

访问文件

10.1109/IMIS.2015.13

其它文件与链接

链接到 Scopus 的出版物

引用此

Xie, B., Tang, X., & Tang, F. (2015). Hybrid Recommendation Base on Learning to Rank. 在 F. Palmieri, L. Barolli, H. Dos Santos Silva, & H.-C. Chen (编辑), Proceedings - 2015 9th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2015 (页码 53-57). 文章 7284927 (Proceedings - 2015 9th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IMIS.2015.13

Xie, Bin ; Tang, Xinhuai ; Tang, Feilong. / Hybrid Recommendation Base on Learning to Rank. Proceedings - 2015 9th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2015. 编辑 / Francesco Palmieri ; Leonard Barolli ; Helio Dos Santos Silva ; Hsing-Chung Chen. Institute of Electrical and Electronics Engineers Inc., 2015. 页码 53-57 (Proceedings - 2015 9th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2015).

@inproceedings{7677eea40cd443ec957b1abd5d21418d,

title = "Hybrid Recommendation Base on Learning to Rank",

abstract = "In order to solve the problem of recommender system using in different scenarios and the ranking of recommendation result, we propose a method using learning to rank for hybrid recommendation. It uses boosting merging algorithm as the base model, Lambda MART algorithm for updating. This makes our ranking model can be updated in real time based on user feedback information. By learning different data from different scenarios, the recommender system can be applied to different applications. In the end, we experiment our hybrid recommendation model by ranking evaluation NDCG.",

keywords = "Boosting merging algorithm, Hybrid recommendation, Lambda MART algorithm, Learning to Rank, NDCG",

author = "Bin Xie and Xinhuai Tang and Feilong Tang",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 9th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2015 ; Conference date: 08-07-2015 Through 10-07-2015",

year = "2015",

month = sep,

day = "30",

doi = "10.1109/IMIS.2015.13",

language = "英语",

series = "Proceedings - 2015 9th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2015",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "53--57",

editor = "Francesco Palmieri and Leonard Barolli and \{Dos Santos Silva\}, Helio and Hsing-Chung Chen",

booktitle = "Proceedings - 2015 9th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2015",

address = "美国",

}

Xie, B, Tang, X & Tang, F 2015, Hybrid Recommendation Base on Learning to Rank. 在 F Palmieri, L Barolli, H Dos Santos Silva & H-C Chen (编辑), Proceedings - 2015 9th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2015., 7284927, Proceedings - 2015 9th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2015, Institute of Electrical and Electronics Engineers Inc., 页码 53-57, 9th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2015, Blumenau, Santa Catarina, 巴西, 8/07/15. https://doi.org/10.1109/IMIS.2015.13

Hybrid Recommendation Base on Learning to Rank. / Xie, Bin; Tang, Xinhuai; Tang, Feilong.
Proceedings - 2015 9th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2015. 编辑 / Francesco Palmieri; Leonard Barolli; Helio Dos Santos Silva; Hsing-Chung Chen. Institute of Electrical and Electronics Engineers Inc., 2015. 页码 53-57 7284927 (Proceedings - 2015 9th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2015).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - Hybrid Recommendation Base on Learning to Rank

AU - Xie, Bin

AU - Tang, Xinhuai

AU - Tang, Feilong

PY - 2015/9/30

Y1 - 2015/9/30

N2 - In order to solve the problem of recommender system using in different scenarios and the ranking of recommendation result, we propose a method using learning to rank for hybrid recommendation. It uses boosting merging algorithm as the base model, Lambda MART algorithm for updating. This makes our ranking model can be updated in real time based on user feedback information. By learning different data from different scenarios, the recommender system can be applied to different applications. In the end, we experiment our hybrid recommendation model by ranking evaluation NDCG.

AB - In order to solve the problem of recommender system using in different scenarios and the ranking of recommendation result, we propose a method using learning to rank for hybrid recommendation. It uses boosting merging algorithm as the base model, Lambda MART algorithm for updating. This makes our ranking model can be updated in real time based on user feedback information. By learning different data from different scenarios, the recommender system can be applied to different applications. In the end, we experiment our hybrid recommendation model by ranking evaluation NDCG.

KW - Boosting merging algorithm

KW - Hybrid recommendation

KW - Lambda MART algorithm

KW - Learning to Rank

KW - NDCG

UR - https://www.scopus.com/pages/publications/84959299987

U2 - 10.1109/IMIS.2015.13

DO - 10.1109/IMIS.2015.13

M3 - 会议稿件

AN - SCOPUS:84959299987

T3 - Proceedings - 2015 9th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2015

SP - 53

EP - 57

BT - Proceedings - 2015 9th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2015

A2 - Palmieri, Francesco

A2 - Barolli, Leonard

A2 - Dos Santos Silva, Helio

A2 - Chen, Hsing-Chung

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 9th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2015

Y2 - 8 July 2015 through 10 July 2015

ER -

Xie B, Tang X, Tang F. Hybrid Recommendation Base on Learning to Rank. 在 Palmieri F, Barolli L, Dos Santos Silva H, Chen HC, 编辑, Proceedings - 2015 9th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2015. Institute of Electrical and Electronics Engineers Inc. 2015. 页码 53-57. 7284927. (Proceedings - 2015 9th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2015). doi: 10.1109/IMIS.2015.13

Hybrid Recommendation Base on Learning to Rank

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