LSTM-based recommendation approach for interaction records

研究成果: 著書/レポートタイプへの貢献会議での発言

抄録

Interactive platforms such as Spotify and Steam currently play an increasingly important role on the Internet. Users continuously use the content on these platforms. Therefore, the most important data in interactive platforms are interaction records, which contain an enormous amount of information regarding user interests at any given time. However, previous recommendation approaches have been unable to process such records satisfactorily. Therefore, we propose an LSTM-based recommendation approach for interaction records. In our approach, we used a recurrent neural network (RNN) based on LSTM to make recommendations by learning user interests and their changing trend. We propose a pretreatment called serial filling at equal ratio to apply LSTM. Further, we used a dimensionality reduction technique based on matrix factorization to improve the system efficiency. Finally, we evaluated our approach using Steam datasets. As indicated by the results, our approach performs better than other conventional approaches in three aspects: Accuracy, efficiency, and diversity.

元の言語英語
ホスト出版物のタイトルProceedings of the 13th International Conference on Ubiquitous Information Management and Communication, IMCOM 2019
編集者Sukhan Lee, Hyunseung Choo, Roslan Ismail
出版者Springer Verlag
ページ950-962
ページ数13
ISBN(印刷物)9783030190620
DOI
出版物ステータス出版済み - 1 1 2019
イベント13th International Conference on Ubiquitous Information Management and Communication, IMCOM 2019 - Phuket, タイ
継続期間: 1 4 20191 6 2019

出版物シリーズ

名前Advances in Intelligent Systems and Computing
935
ISSN(印刷物)2194-5357

会議

会議13th International Conference on Ubiquitous Information Management and Communication, IMCOM 2019
タイ
Phuket
期間1/4/191/6/19

Fingerprint

Steam
Recurrent neural networks
Factorization
Internet

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science(all)

これを引用

Zhou, Y., & Ushiama, T. (2019). LSTM-based recommendation approach for interaction records. : S. Lee, H. Choo, & R. Ismail (版), Proceedings of the 13th International Conference on Ubiquitous Information Management and Communication, IMCOM 2019 (pp. 950-962). (Advances in Intelligent Systems and Computing; 巻数 935). Springer Verlag. https://doi.org/10.1007/978-3-030-19063-7_74

LSTM-based recommendation approach for interaction records. / Zhou, Yan; Ushiama, Taketoshi.

Proceedings of the 13th International Conference on Ubiquitous Information Management and Communication, IMCOM 2019. 版 / Sukhan Lee; Hyunseung Choo; Roslan Ismail. Springer Verlag, 2019. p. 950-962 (Advances in Intelligent Systems and Computing; 巻 935).

研究成果: 著書/レポートタイプへの貢献会議での発言

Zhou, Y & Ushiama, T 2019, LSTM-based recommendation approach for interaction records. : S Lee, H Choo & R Ismail (版), Proceedings of the 13th International Conference on Ubiquitous Information Management and Communication, IMCOM 2019. Advances in Intelligent Systems and Computing, 巻. 935, Springer Verlag, pp. 950-962, 13th International Conference on Ubiquitous Information Management and Communication, IMCOM 2019, Phuket, タイ, 1/4/19. https://doi.org/10.1007/978-3-030-19063-7_74
Zhou Y, Ushiama T. LSTM-based recommendation approach for interaction records. : Lee S, Choo H, Ismail R, 編集者, Proceedings of the 13th International Conference on Ubiquitous Information Management and Communication, IMCOM 2019. Springer Verlag. 2019. p. 950-962. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-3-030-19063-7_74
Zhou, Yan ; Ushiama, Taketoshi. / LSTM-based recommendation approach for interaction records. Proceedings of the 13th International Conference on Ubiquitous Information Management and Communication, IMCOM 2019. 編集者 / Sukhan Lee ; Hyunseung Choo ; Roslan Ismail. Springer Verlag, 2019. pp. 950-962 (Advances in Intelligent Systems and Computing).
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