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Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (11): 28-36    DOI: 10.11925/infotech.2096-3467.2018.0832
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Recommendation Algorithm for Post-Context Filtering Based on TF-IDF: Case Study of Catering O2O
Yin Cong1, Zhang Liyi2()
1Intellectual Property School, Chongqing University of Technology, Chongqing 400054, China
2School of Information Management, Wuhan University, Wuhan 430072, China
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[Objective] This paper carries out an in-depth study on context-integrated and personalized recommendation, aiming to address the issue of information overload. [Methods] We proposed a new contextual preference prediction model based on TF-IDF algorithm for post-context filtering, as well as the contextual association probability and universal importance. Then, we adjusted the initial scores of traditional recommendation with the help of item category preferences to generate the final list. [Results] We conducted an empirical study on catering industry and found that the proposed algorithm yielded better results. [Limitations] The accuracy of the context association needs to be improved. [Conclusions] Context information plays an important role in user behavior and decision making. More research is needed to improve the personalized recommendation based on context modeling.

Key wordsContext Information      Contextual Post-Filtering Recommendation      TF-IDF      Contextual Preference      Item Category Preference     
Received: 26 July 2018      Published: 11 December 2018
ZTFLH:  G202  

Cite this article:

Yin Cong,Zhang Liyi. Recommendation Algorithm for Post-Context Filtering Based on TF-IDF: Case Study of Catering O2O. Data Analysis and Knowledge Discovery, 2018, 2(11): 28-36.

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对比项目 传统电子商务环境 O2O环境
数据特性 以用户-项目二维数据为主, 较少考虑用户所处的情境信息;
不受空间限制, 数据为全域数据。
用户-情境-项目多维数据; 地域性极强, 推荐中涉及的数据为本地化数据。
用户偏好 依据浏览行为和购买记录等信息, 忽视情境挖掘用户偏好。 根据用户在不同情境下的偏好, 结合当前情境分析用户当前偏好。
信息匹配 基于“消费者的需求在一定时期稳定不变”这一假设进行信息
数据稀疏性 数据稀疏性较为严重。 传统推荐稀疏性问题依然存在, 随着维度扩大, 数据稀疏更为严重。
推荐实时性 无需考虑用户情境, 推荐的实时性要求相对较低。 用户需求具有情境敏感性, 需根据用户所处情境变化进行实时推荐。
情境维度 情境实例
位置 武昌、洪山、青山、汉阳、江岸、江汉、硚口
作息 工作日、休息日、节假日
天气 阴、晴、雨、雪、多云
同伴 独自一人、朋友、伴侣、家人
情绪 积极、消极、中性
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