基于粒计算的移动电子商务推荐系统研究

发布时间：2018-12-21 20:46

【摘要】：随着移动电子商务兴起,智能终端快速普及和社会网络广泛建立,并伴随着信息化领域的扩展、云计算理论的提出、语义学与本体论的兴起,人们已然进入大数据时代。然而,随着信息量的惊人膨胀,人们必须付出更大的成本才能在大量泛滥的信息中寻找到合适的信息。但是在信息检索、处理以及展示等方面相对于传统PC而言,移动终端有着明显的弱势。如何有效的分析用户需求,使用户不被信息的汪洋大海所淹没,以便捷高效的方式寻找用户的兴趣点,快速满足用户需求已成为移动电子商务研究的热点之一,移动电子商务推荐系统随之产生。与此同时,如何更好地适应移动电子商务所特有的移动性、虚拟性、个性化、极端数据、社会性等新兴特征也成为移动电子商务推荐系统研究的重点内容。作为信息处理的一种新的概念和计算范式,粒计算已经成为学术界近年来兴起的研究热潮。作为一种信息分类工具,粒计算的基本思想符合人们对实际客观世界的认知。通过发现和描述粒与粒之间的特定关系,粒的思想为移动电子商务推荐系统模型复杂数据问题的研究提供一条新的思路和方法。本文以移动电子商务推荐系统模型为研究对象,将粒度分析引入到移动电子商务推荐模型中,针对移动电商特性,借助推荐模型已有研究方法和手段,利用粒度分析中的粒化原则、合成原则、分层原则等,充分借鉴粒度分析中的基于结构化思维的哲学思想、基于结构化问题求解的方法论、基于结构化信息处理的计算模式,将多层次、多视角结构的思想引入到移动电子商务推荐系统模型中,构建一种基于粒计算的个性化推荐系统模型。在理论和方法上为移动电子商务推荐系统模型研究开辟一条新的途径,为解决实际问题提供科学依据。针对基于粒度分析的移动电商推荐的理论模型及方法,本文利用大众点评网成都站餐饮数据对个性化推荐模型进行实验分析,从推荐结果集合和属性粒子等方面分析推荐算法的准确度和多样性。本文研究不仅有望在理论和方法上为移动电子商务推荐系统模型研究难点开辟新的解决路径,而且可以拓展粒计算理论的应用领域,具有重要的理论和应用价值。
[Abstract]:With the rise of mobile e-commerce, the rapid popularization of intelligent terminals and the establishment of social networks, and with the expansion of the field of information, cloud computing theory, semantics and ontology, people have entered the era of big data. However, with the tremendous expansion of information, people have to pay more in order to find the right information in the flood of information. However, compared with traditional PC, mobile terminals have obvious disadvantages in information retrieval, processing and display. How to analyze the user's demand effectively, make the user not be submerged by the sea of information, find the user's interest point in the convenient and efficient way, satisfy the user's demand quickly has become one of the hot spots in the research of the mobile electronic commerce. The mobile e-commerce recommendation system comes into being. At the same time, how to better adapt to the unique mobile e-commerce mobile, virtual, personalized, extreme data, sociality and other emerging features has become the focus of mobile e-commerce recommendation system. As a new concept and computing paradigm of information processing, granular computing has become a hot topic in academic circles in recent years. As a kind of information classification tool, the basic idea of granular computing accords with people's cognition of the actual objective world. By discovering and describing the specific relationship between grains, the idea of grain provides a new idea and method for the study of complex data problems in the model of mobile e-commerce recommendation system. In this paper, the mobile e-commerce recommendation system model is taken as the research object, and the granularity analysis is introduced into the mobile e-commerce recommendation model. According to the characteristics of mobile ecommerce, there are some research methods and means based on the recommendation model. By using the granulation principle, composition principle, stratification principle and so on in granularity analysis, the philosophical thought based on structured thinking, the methodology of structured problem solving and the computing mode of structured information processing are fully used for reference. The idea of multi-level and multi-angle structure is introduced into the mobile e-commerce recommendation system model to construct a personalized recommendation system model based on granular computing. In theory and method, it opens up a new way for the research of mobile E-commerce recommendation system model, and provides scientific basis for solving practical problems. Aiming at the theoretical model and method of mobile e-commerce recommendation based on granularity analysis, this paper makes an experimental analysis on the personalized recommendation model by using the catering data of Chengdu Station of Dianping net. The accuracy and diversity of recommendation algorithm are analyzed from the point of view of recommendation result set and attribute particle. The research in this paper is not only expected to open a new way to solve the difficulties of mobile e-commerce recommendation system model in theory and method, but also to expand the application field of granular computing theory, which has important theoretical and application value.
【学位授予单位】：西南交通大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TP391.3;F724.6

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