The Design and Realization of Personalized E-commerce Recommendation System

According to demand and function of the e-commerce recommendation system demand, this paper analyze and design e-commerce and personalized recommendation, design and complete different system functions in different system level; then design in detail system process from the front and back office systems, and in detail descript the key data in the database and several tables. Finally, the paper respectively tests several main modules of onstage system and the backstage system. The paper designed electronic commerce recommendation based on personalized recommendation system, it can complete the basic function of the electronic commerce system, also can be personalized commodity recommendation for different users, the user data information and the user＇ s shopping records.

An E-Commerce Recommender System Based on Content-Based Filtering

Content-based filtering E-commerce recommender system was discussed fully in this paper. Users＇ unique features can be explored by means of vector space model firstly. Then based on the qualitative value of products informa tion, the recommender lists were obtained. Since the system can adapt to the users＇ feedback automatically, its performance were enhanced comprehensively. Finally the evaluation of the system and the experimental results were presented.

The Mobile Personalized Recommendation Model Containing Implicit Intention

Because mobile e-commerce is limited by the mobile terminal,network environment and other factors,accurate personalized recommendations become more and more important.We establish a large data intelligence platform,aiming at the characteristics of mobile e-commerce;we put forward a personalized recommendation model with implicit intention further.Firstly,create an intelligence unit with the virtual individual association set,virtual demand association set and virtual behavior associated set;Secondly,calculate the complex buying behavior prediction engine;Finally,give the predictive value of complex buying behavior.This method takes full account of factors such as hidden wishes perturbations that affect the predict of complex buying behavior,which to some extent solve a long-span composite purchasing behavior prediction.It shows that this method improves the purchasing behavior prediction accuracy effectively through experiments.

Study on the Recommended Model Based on Personal Information System

This paper classifies the scenario elements which affect the real-time information needs of mobile commerce users, and proposes a nomination model that integrates the user’s personalized context elements. In this model, the top K scenarios that have the greatest impact on each user’s instant information demands are calculated from the user’s current scenario and historical data, thereby constructing a user personalized situation and improving it as an input condition that existing scenario-based multi-dimensional information recommendation algorithm is used for project nomination. Result/Conclusion: The improved algorithm and other three algorithms were compared by Movie lens and MBook Crossing dataset. The experimental results show that the model has higher prediction accuracy and can effectively improve user satisfaction and more effectively and solve personalized nomination issues in a mobile commerce environment.

Privacy disclosure in Chinese social networking sites:An investigation of Renren users

Purpose:This study was conducted to investigate the current situation of privacy disclosure(in the Chinese social networking sites.Design/methodology/approach:Data analysis was based on profiles of 240 college students on Renren.com,a popular college-oriented social networking site in China.Users’ privacy disclosure behaviors were studied and gender difference was analyzed particularly.Correlation analysis was conducted to examine the relationships among evaluation indicators involving user name,image,page visibility,message board visibility,completeness of education information and provision of personal information.Findings:A large amount of personal information was disclosed via social networking sites in China.Greater percentage of male users than female users disclosed their personal information.Furthermore,significantly positive relationships were found among page visibility,message board visibility,completeness of education information and provision of personal information.Research limitations:Subjects were collected from only one social networking website.Meanwhile,our survey involves subjective judgments of user name reliability,category of profile images and completeness of information.Practical implications:This study will be of benefit for college administrators,teachers and librarians to design courses for college students on how to use social networking sites safely.Originality /value:This empirical study is one of the first studies to reveal the current situation of privacy disclosure in the Chinese social networking sites and will help the research community gain a deeper understanding of privacy disclosure in the Chinese social networking sites.

开放性人格与大学生社交网站使用的关系:感知媒介丰富性的中介作用与自我监控的调节作用

本研究基于媒介丰富性理论,考察了开放性人格与大学生社交网站使用的关系及其内在机制。对563名大学生进行问卷调查,结果显示:(1)开放性人格显著正向预测主动社交网站使用、负向预测被动社交网站使用。(2)感知媒介丰富性在开放性人格与主动社交网站使用之间发挥中介作用。(3)自我监控既可以调节开放性人格与被动社交网站使用之间的关系,也可以调节“开放性人格→感知媒介丰富性→主动社交网站使用”这一中介效应的后半段。研究从人格和媒介视角出发,厘清了高开放性大学生从社交网站使用中获益的具体方式、内在机制与边界条件,兼具理论和实践意义。

Evolutionary Game Analysis on E-Commerce Personalization and Privacy Protection

Personalized products and services in e-commerce bring consumers many new experiences, but also trigger a series of information security issues. Considering the bounded rationality of the game participants, in this paper, we propose an evolutionary game model of privacy protection between firms and consumers based on e-commerce personalization. Evolutionary stable strategies（ESSs） are obtained from the equilibrium points according to the model analysis, and then simulation experiments are launched to validate the decision-making results and the influencing mechanism of various factors. The results show that the model can eventually evolve toward a win-win situation by wisely varying its various factors, such as ratios of initial strategies, cost of privacy protection, commodity prices, and other related factors. Further, we find that reducing the possibility of the privacy breach under the premise of privacy protection can help promote the e-commerce personalization.

论刑事侦查中地理围栏技术应用的改进

地理围栏技术的应用已十分常见,其在我国的刑事侦查中有三种样态:未知犯罪嫌疑人时的筛选确定、已知犯罪嫌疑人时获取犯罪嫌疑人更多个人信息及涉案证据的相互印证。这一过程中侦查机关获取个人信息所受限制较少且过度分析了个人信息,加重了对个人隐私权利的侵犯程度。其侦查逻辑本身还具有认知进程单向性的特点,容易殃及无辜。应当限缩适用范围,明确排除第一种样态的适用,除有益于隐私保障外还能防止产生技术依赖;在承认公共场所隐私利益的前提下,披露围栏设备的安装位置、限缩其安装区域;再设置内容详细的围栏数据搜查证、要求侦查机关履行告知义务、并辅以密钥技术手段保障处理个人信息的正当性。

GLOBAL ANALYSIS TO A KIND OF COMPETITION MODEL OF E-COMMERCE SITES

In this paper, we present a competition modei of e-commerce sites with the property of 'better for better'. Then we qualitatively analyze the special case of two dimensions. So we prove that there does not exist limit cycle, in the first quadrant of the phase plane and all trajectories tend to some singular points.

计量驻点机构建设及个性化现场计量服务研究

近年来,随着我国工业化进程的发展和产业升级,运输成本、人力成本不断地攀升,标准器等资源整合的影响较大,传统的现场计量服务受到了挑战。在传统现场计量服务的基础上,提出了设立驻点分支计量机构的观点,阐述了如何完善驻点分支机构的管理制度,强化驻点分支机构的人才队伍建设等新举措;并视不同客户的特点,制定个性化现场服务策略,为更好地服务客户打下坚实的基础,有一定的参考价值。

社交网络用户个人信息安全隐私保护行为影响因素研究

[目的/意义]本研究目的是以社交网络用户为研究对象,通过提出假设、构建理论模型和收集实际数据验证模型来对社交网络用户个人信息安全隐私保护行为的影响因素进行探究。[方法/过程]本研究基于保护动机理论和隐私关注构建影响因素模型,并通过问卷调查获取数据,运用结构方程方法对模型的适用性进行检验。[结果/结论]反应效能、自我效能、反应成本、感知威胁和隐私关注对用户个人信息安全隐私保护意愿具有显著的直接影响,其中反应成本起到消极作用,上述5个变量通过中介变量保护意愿间接影响用户的保护行为。

上海某地铁站黑碳浓度水平及个体暴露特征

基于对职业环境空气污染物的个体暴露风险关注,在上海某地铁站进行了ρ(黑碳)的连续定点(新风井和车辆控制室)监测;同时对地铁工作人员进行个体黑碳暴露采样,并与定点监测的ρ(黑碳)比较,探讨个体采样在黑碳暴露研究中的作用.结果表明:某地铁站新风井处ρ(黑碳)与ρ(NO2)呈显著相关(R=0.75,P<0.05),而与ρ(PM10)无显著相关性(R=0.43,P>0.1);由ρ(黑碳)日变化及其在工作日和休息日的差异可知,地铁站内ρ(黑碳)可能与室外机动车尾气排放相关;与定点监测结果不同,个体黑碳暴露浓度波动范围大,出现了未在定点监测中观测到的极高值,并且个体黑碳暴露浓度的四分位差值(IQR)是定点监测结果的2倍;尽管车控室内平均个体黑碳暴露浓度较低,但由于个体72%的工作时间是在车控室内度过的,因此车控室的个体黑碳暴露剂量比非车控室环境高.

感知有用性、信任与社交网站用户的个人信息披露意愿

感知有用性、信任是影响社交网站用户个人信息披露意愿的重要因素,对三者内在关系的探讨有助于更好地理解个体信息行为。选取新浪和腾讯微博、人人网以及QQ空间等社交网站的用户作为研究对象,通过网络问卷调查收集数据,并且利用结构方程模型(SEM)分析三者的作用路径。研究结果表明,社交网站用户的感知有用性和信任都对个人信息披露意愿产生了正向影响,不过信任的影响更为明显,并且信任在感知有用性和个人信息披露意愿之间发挥了部分中介的作用。

基于数据挖掘的个性化学习导航系统的设计与实现

介绍了在远程教育系统中引入自适应机制，针对远程教育系统的学习者的学习特点，提供不同的学习资源，即个性化学习导航系统。个性化的基础是对用户的已有数据进行数据挖掘，分析出用户的知识架构。根据已有的全局知识空间，与用户知识架构作补操作，向用户提供其应学习的资源。

Web3.0与个性化信息服务

论文在对Web3.0的含义进行阐述的基础上,分析了Web3.0的四个特征,着重介绍它对个性化信息服务的影响,介绍了Web3.0目前面临的问题,并对其未来进行了展望。

移动社交网站中的信息过载与个性化推荐机制研究

为避免信息过载的危害,移动社交网站应向用户推荐更符合用户个性化需求的信息。通过对移动社交网站的信息过载现状进行研究,系统分析了信息过载产生的原因和可能造成的危害,在研究个性化推荐机制对信息过载具有防控作用的基础上,构建了面向移动社交网站的个性化推荐机制的宏观架构,并进一步探讨了该机制关键模块的功能和关键步骤的技术实现问题。

一个基于Rough集的用户兴趣访问模式的发现算法

个性化网站是当今商务网站智能化的一个发展方向 ,其特点就是迎合每个用户的浏览兴趣并且不断调整自己来适应用户浏览兴趣的变化 .研究的是如何发现用户访问过程中所关注的兴趣内容 ,从而为网站的个性化推荐服务 .首先对网站的内容抽取出概念 ,生成概念树 ,在此基础上提出了一个基于 Rough集的用户兴趣访问模式的发现算法 。

基于Web使用挖掘技术的个性化教育网站构筑

本文介绍了个性化网络教育的特点。对在Web服务器端和客户端进行学生浏览路径模式采集的各种方法进行了分析,探讨了如何将Web使用挖掘技术应用到个性化网络教育,最后介绍了由我们开发的个性化教育网站。

网络用户个人信息的敏感度研究

采用问卷调查的方式对中国网络用户个人信息的敏感度进行了研究。结果表明,调查中21项信息的敏感度存在差异,据此可将网络用户个人信息分为非常敏感、敏感、比较敏感和不敏感四类;网络情境对大多数个人信息的敏感度产生了显著影响;不同性别、年龄和学历的网络用户对个人信息的敏感度认识存在差异。

村落遗产地品牌个性对游客忠诚的影响——游客自我一致和村落遗产地品牌关系质量的中介作用

村落遗产地旅游品牌研究还处于浅层次发展阶段,本文以世界文化遗产开平碉楼与村落为例,依据自我调节态度理论的"评价→情感响应→行为意向"自我调节过程,构建出村落遗产地品牌个性、游客自我一致、村落遗产地品牌关系质量与游客忠诚关系模型,并运用Mplus7.0软件进行结构方程模型分析。研究结果显示:(1)村落遗产地品牌个性包含高雅、乐观、质朴、实惠和智慧5个维度,其中,质朴是村落遗产地品牌个性的独特维度,游客总体感知最高。(2)游客品牌满意和游客品牌依恋在游客自我一致与游客忠诚关系间起完全中介作用。(3)村落遗产地品牌个性能够通过游客自我一致和村落遗产地品牌关系质量链式中介间接作用于游客忠诚,但对游客品牌依恋和游客忠诚的直接效应不显著。研究结果为村落遗产地旅游品牌化管理提供了理论参考与借鉴。