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Recommendation Based on Users’ Long-Term and Short-Term Interests with Attention
المؤلفون المشاركون
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-13، 13ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-10-17
دولة النشر
مصر
عدد الصفحات
13
التخصصات الرئيسية
الملخص EN
Recommendations based on user behavior sequences are becoming more and more common.
Some studies consider user behavior sequences as interests directly, ignoring the mining and representation of implicit features.
However, user behaviors contain a lot of information, such as consumption habits and dynamic preferences.
In order to better locate user interests, this paper proposes a Bi-GRU neural network with attention to model user’s long-term historical preferences and short-term consumption motivations.
First, a Bi-GRU network is established to solve the long-term dependence problem in sequences, and attention mechanism is introduced to capture user interest changes related to the target item.
Then, user’s short-term interaction trajectory based on self-attention is modeled to distinguish the importance of each potential feature.
Finally, combined with long-term and short-term interests, the next behavior is predicted.
We conducted extensive experiments on Amazon and MovieLens datasets.
The experimental results demonstrate that the proposed model outperforms current state-of-the-art models in Recall and NDCG indicators.
Especially in MovieLens dataset, compared with other RNN-based models, our proposed model improved at least 2.32% at Recall@20, which verifies the effectiveness of modeling long-term and short-term interest of users, respectively.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Tan, Qiaoqiao& Liu, Fang’ai. 2019. Recommendation Based on Users’ Long-Term and Short-Term Interests with Attention. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-13.
https://search.emarefa.net/detail/BIM-1197107
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Tan, Qiaoqiao& Liu, Fang’ai. Recommendation Based on Users’ Long-Term and Short-Term Interests with Attention. Mathematical Problems in Engineering No. 2019 (2019), pp.1-13.
https://search.emarefa.net/detail/BIM-1197107
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Tan, Qiaoqiao& Liu, Fang’ai. Recommendation Based on Users’ Long-Term and Short-Term Interests with Attention. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-13.
https://search.emarefa.net/detail/BIM-1197107
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1197107
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر
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