基于社会化媒体情境的多维协同智能推荐

doi:10.11772/j.issn.1001-9081.2016.03.740

计算机应用 ›› 2016, Vol. 36 ›› Issue (3): 740-745.DOI: 10.11772/j.issn.1001-9081.2016.03.740

基于社会化媒体情境的多维协同智能推荐

卢志刚, 孙亚丹

上海海事大学经济管理学院, 上海 201306

收稿日期:2015-08-10 修回日期:2015-10-25 出版日期:2016-03-10 发布日期:2016-03-17
通讯作者: 孙亚丹
作者简介:卢志刚(1973-),男,湖北京山人,教授,博士,主要研究方向:供应链管理、商务智能;孙亚丹(1991-),女,山东济宁人,硕士研究生,主要研究方向:电子商务、供应链管理。
基金资助:
上海海事大学校基金资助项目(20130464)。

Multidimensional collaborative intelligence recommendation based on social media context

LU Zhigang, SUN Yadan

School of Economics and Management, Shanghai Maritime University, Shanghai 201306, China

Received:2015-08-10 Revised:2015-10-25 Online:2016-03-10 Published:2016-03-17
Supported by:
This work is partially supported by Fundamental Funds for Shanghai Maritime University (20130464).

摘要/Abstract

摘要： 针对传统协同智能推荐技术的冷启动、数据稀缺性问题,为提高推荐算法的效率和准确性,提出一种基于社会化媒体情境的多维智能推荐算法模型。该模型将目标用户的属性特征、行为特征考虑到社会化媒体情境信息中,并动态实时捕捉用户在不同社会化媒体情境下的偏好倾向,利用联机分析处理(OLAP)技术对多维数据进行处理。该模型将用户间的社会化关系和所处的政治经济环境视为衡量用户相似的重要指标,同时使用皮尔森系数和云模型来计算用户间各特征的相似度,并以此为推荐基础向用户呈现更个性化和定制化的推荐结果。实验结果表明,该模型的推荐结果的平均绝对误差明显小于传统的协同智能推荐和单纯的基于云模型推荐技术。

关键词: 社会化媒体, 情境, 协同推荐, 多维, 云模型

Abstract: In allusion to the problem of cold start technology and data scarcity in the traditional collaborative intelligence recommendation technology, in order to improve the efficiency and accuracy of recommendation algorithm, multidimensional collaborative intelligence recommendation based on social media context was proposed. In this model, the feature attributes and behavioral characteristics of the target users were considered into the information of social media context, users' interests in different social media context were dynamically captured in real-time, and OnLine Analytical Processing (OLAP) technology was used to process multidimensional data. The social relationship between users and the political and economic environment were regarded as an important indicator, then, the similarity between users were calculated using Pearson coefficient and cloud model, to get personalized and customized recommendation results. The experimental results show that the average absolute error of the model is significantly less than traditional collaborative intelligent recommendation and simple recommendation technology based on cloud model.

Key words: social media, context, collaborative recommendation, multidimensional, cloud model

中图分类号:

TP393.0

卢志刚, 孙亚丹. 基于社会化媒体情境的多维协同智能推荐[J]. 计算机应用, 2016, 36(3): 740-745.

LU Zhigang, SUN Yadan. Multidimensional collaborative intelligence recommendation based on social media context[J]. Journal of Computer Applications, 2016, 36(3): 740-745.

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基于社会化媒体情境的多维协同智能推荐

Multidimensional collaborative intelligence recommendation based on social media context

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