| 基于梯度提升决策树的情境感知推荐模型 |
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| 引用本文： | 郭静娟.基于梯度提升决策树的情境感知推荐模型[J].情报探索,2020(4):58-63. |
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| 作者姓名： | 郭静娟 |
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| 作者单位： | 华南理工大学经济与贸易学院 广东广州 511400 |
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| 摘 要： | 目的/意义]旨在深入研究情境信息对用户偏好的影响,提高情境感知推荐的准确性。方法/过程]提出了基于梯度提升决策树的情境感知推荐模型,根据梯度提升决策树计算情境属性权重,将其与传统协同过滤算法相融合,生成情境感知推荐结果。结果/结论]该模型可以识别影响用户偏好的重要情景属性,为用户提供个性化推荐服务。
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| 关 键 词： | 梯度提升 决策树 情境感知 推荐模型 本体 |
Context-aware Recommendation Model Based on Gradient Boosting Decision Tree |
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| Guo Jingjuan.Context-aware Recommendation Model Based on Gradient Boosting Decision Tree[J].Information Research,2020(4):58-63. |
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| Authors: | Guo Jingjuan |
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| Institution: | (Department of Economics&Trade South China University of Technology,Guangzhou Guangdong 511400) |
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| Abstract: | Purpose/significance]The paper intends to explore the impact of context information on users’preferences and improve the accuracy of context-aware recommendations.Method/process]The paper established a context-aware recommendation model based on gradient boosting decision tree calculated context attribute weights based on the gradient boosting decision tree algorithm combined them with traditional collaborative filtering algorithms and got context-aware recommendation results.Result/conclusion]The model can identify the significant situation attributes that may offect the user perference and provides personalized recommendation service. |
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| Keywords: | gradient boosting decision tree context-aware recommendation model ontology |
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