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2015 IEEE 12th International Conference on e-Business Engineering最新文献

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Personalized Recommendation of E-Commerce Website Category Hierarchy Based on Web Usage Mining and Multidimensional Scaling 基于Web使用挖掘和多维尺度的电子商务网站类别层次个性化推荐
Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.23
Peng Wu, Jiamin Wang, Daqing He
The purpose of this paper is to study personalized needs of e-commerce website category hierarchy based on users' mental models by means of Multidimensional Scaling and Web Usage Mining. The users' browsing category paths in an e-commerce website is extracted based on the Web Usage Mining, and the Multidimensional Scaling was used to probe the structure and composition of the users' mental models of website category hierarchy based on their browsing category paths, at last, users' personalized needs can be identified. Three million web log data records were collected for experimental study. The experimental results show the proposed method is efficient to discover users' personalized needs of expected category hierarchy based on large scale web log data automatically and efficiently.
本文采用多维尺度和Web使用挖掘的方法,研究基于用户心智模型的电子商务网站品类层次的个性化需求。基于Web Usage Mining提取了某电子商务网站用户的浏览品类路径,并利用多维尺度法根据用户浏览品类路径探索用户的网站品类层次心理模型的结构和组成,最终识别出用户的个性化需求。收集了300万条网络日志数据记录进行实验研究。实验结果表明,该方法能够有效地自动发现基于大规模web日志数据的用户个性化需求。
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引用次数: 1
Review Sentiment Analysis Based on Deep Learning 基于深度学习的评论情感分析
Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.24
Zhongkai Hu, Jianqing Hu, Weifeng Ding, Xiaolin Zheng
With rapid development of E-commerce platforms, automated review sentiment analysis for commodities becomes a research focus, with main purpose to extract potential information within reviews for decision making of consumers. Traditional methods have made some progress on document level sentiment analysis, but with tremendous increasing of data scale, how to process high dimension of data fast and effectively becomes the largest limitation. In this paper, we import deep neural network which is appropriate for high dimension data analysis, and propose a framework of sentiment analysis based on deep learning. Experiments on different data scale and different domains show that the proposed method can solve high dimensional problem with good performance.
随着电子商务平台的快速发展,商品评论情感自动分析成为一个研究热点,其主要目的是提取评论中潜在的信息,供消费者决策。传统方法在文档级情感分析方面取得了一定的进展,但随着数据规模的急剧增加,如何快速有效地处理高维数据成为最大的限制。本文引入适合于高维数据分析的深度神经网络,提出了一种基于深度学习的情感分析框架。在不同数据规模和不同领域的实验表明,该方法能够有效地解决高维问题。
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引用次数: 38
Study on the Model and Algorithm of Internet Trusted Identity Authentication System 互联网可信身份认证系统模型与算法研究
Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.76
Yao-Ching Liu, Y. Chai, Yi Liu
In the current Internet environment, security incidents occur frequently and the potential safety problems are highlighted. In this case, we propose "Internet trusted identity authentication system". The system changes the previous conventional mode of identity authentication, changes the mode of username/password to the relationship bound between net ID and password rule and replaces the traditional dead-password mode with the mode of dynamic password and password rule. At the same time, we should establish the repository of trusted identity to store and manage the net ID and password rule. With the tools of USBKEY, SMS and digital certificates, the system can achieve the function of implementing the real-name network in the Internet, making remembering passwords more convenience, simplifying users' operations online and strengthening the security of personal identification information online, which can improve the safety, reliability and efficiency of the Internet, on the premise that it won't change the Internet functions or the operation habits.
在当前的互联网环境下,安全事件频发,安全隐患凸显。在这种情况下,我们提出了“互联网可信身份认证系统”。该系统改变了以往传统的身份认证模式,将用户名/密码模式改为网号与密码规则的关系绑定模式,将传统的死密码模式改为动态密码和密码规则模式。同时,建立可信身份库,对网络ID和密码规则进行存储和管理。本系统通过USBKEY、SMS、数字证书等工具,在不改变互联网功能和使用习惯的前提下,实现互联网实名制,方便用户记密码,简化用户网上操作,加强网上个人身份信息的安全性,提高互联网的安全性、可靠性和效率。
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引用次数: 0
Schooladvise: Designing a Reputation System for Educational Services through Service Design and Business Modeling 学校咨询:通过服务设计和商业模型设计教育服务的声誉系统
Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.52
Sara Capecchi, Mauro Giraudo, Claudia Negro, P. Pisano
In this paper we analyse the use of an extension of tools for service design and business conceptual modelling toward reputation system design for the realisation of Schooladvise a platform for educational services reputation management. The work described in the present paper originates from the intuition that business process modelling, service design and reputation system modelling share many needs, aims and problems: to represent a variety of entities involved in the related domains, to improve services/business in order to meet the users need, moreover they all involve stakeholders with very different background and skills, a problem known as socio-technical mismatch. The objective and the contribution of the analysis presented in this paper is to gather feedback on the proposed modelling language from the end-users (requirements engineers and domain experts) while applying it to a complex case study.
在本文中,我们分析了服务设计工具的扩展和商业概念建模在声誉系统设计中的应用,以实现Schooladvise教育服务声誉管理平台。本文中描述的工作源于这样一种直觉,即业务流程建模、服务设计和声誉系统建模共享许多需求、目标和问题:代表相关领域中涉及的各种实体,改进服务/业务以满足用户需求,此外,它们都涉及具有非常不同背景和技能的利益相关者,这是一个被称为社会技术不匹配的问题。本文中提出的分析的目标和贡献是从最终用户(需求工程师和领域专家)那里收集关于所建议的建模语言的反馈,同时将其应用于复杂的案例研究。
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引用次数: 0
Relative Patterns Discovery toward Big Data Analytics 面向大数据分析的相对模式发现
Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.74
Hao-Ting Pai, Fan Wu, P. Hsueh, Grace Lin, Ya-Hui Chan
Recently, enterprises and governments invested aggressively in big data analytics because it is truly representative of popular opinion based on millions of people. Despite bringing new opportunities, big data encounters the challenges such as extremely large number of observations (e.g., Millions of transactions), high dimensionality (e.g., Thousands of items), and immediate response. Taking big data into consideration, the conventional association analysis is frustrated by the extraction of patterns information. Specifically, the computational complexity of frequent item sets mining increases exponentially by the number of items, which has been proven to be an NP-Complete problem. Although many studies used a pruning-patterns strategy to reduce the complexity, it probably distorts the shape of data and incurs inaccurate result. In this paper, we introduce relative patterns discovery (named RPD) that explores the same patterns between each two observations. To show that RPD is a pragmatic solution toward big data analytics, we design a scalable outlier detection method (named SOD) based on the concept of RPD. Particularly, SOD can score the anomaly without enumerate all the relative patterns. The empirical investigations, conducted with various real-world datasets, demonstrate that SOD performs well even in the environment of large number of observations and high dimensionality.
最近,企业和政府大举投资于大数据分析,因为它真正代表了基于数百万人的民意。大数据在带来新机遇的同时,也面临着观测量大(如数百万笔交易)、维度高(如数千件物品)、反应迅速等挑战。在大数据环境下,传统的关联分析方法在模式信息的提取上存在不足。具体而言,频繁项集挖掘的计算复杂度随项目数量呈指数增长,已被证明是一个np完全问题。尽管许多研究使用了修剪模式策略来降低复杂性,但它可能会扭曲数据的形状并导致不准确的结果。在本文中,我们引入了相对模式发现(称为RPD),它在每两个观测之间探索相同的模式。为了证明RPD是一种实用的大数据分析解决方案,我们基于RPD的概念设计了一种可扩展的离群值检测方法(SOD)。特别地,SOD可以在不列举所有相关模式的情况下对异常进行评分。利用各种真实数据集进行的实证研究表明,即使在大量观测和高维度的环境中,SOD也表现良好。
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引用次数: 1
A Four-Layer Flexible Spatial Data Framework towards IoT Application 面向物联网应用的四层灵活空间数据框架
Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.64
Shuai Luan, Hongming Cai, Fenglin Bu, Lihong Jiang
Huge amounts of spatial documents have been generated every day in IoT (internet of things) applications. Both spatial and textual or other information of complicated structure should be taken into account when providing services. Therefore, it is crucial to store and process these data efficiently in IoT applications. In this paper, we propose a flexible four-layer framework for spatial data towards IoT applications, which decouples the spatial and content information and organizes the whole space with a pyramid structure. The four layers of the framework are geography node, application node, logical node and storage node that are related with the accurate spatial information, content information with rich semantic, flexible space organization and efficient storage with hybrid database respectively. Among them, logical node is the center which associates the other nodes, and provides an efficient query processing method using the pyramid structure. We apply the four-layer framework in the Smarter City Charging Pile System and construct the four kinds of nodes to realize the function that recommends the best matching charging piles for electric vehicle drivers taking both distance and pile state into consideration. The compare discussion shows that our framework has high flexibility, supports rich semantic and is more acceptable in practical IoT applications.
在物联网应用中,每天都会生成大量的空间文档。在提供服务时,既要考虑空间信息,也要考虑文本或其他结构复杂的信息。因此,在物联网应用中有效地存储和处理这些数据至关重要。本文针对物联网应用,提出了一个灵活的四层空间数据框架,将空间信息和内容信息解耦,并以金字塔结构组织整个空间。该框架的四层分别是与准确的空间信息、语义丰富的内容信息、灵活的空间组织和高效的混合数据库存储相关的地理节点、应用节点、逻辑节点和存储节点。其中,逻辑节点是关联其他节点的中心,利用金字塔结构提供了一种高效的查询处理方法。我们将四层框架应用到智慧城市充电桩系统中,构建四种节点,实现同时考虑距离和桩状态为电动汽车驾驶员推荐最佳匹配充电桩的功能。对比讨论表明,我们的框架具有较高的灵活性,支持丰富的语义,在实际物联网应用中更容易被接受。
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引用次数: 2
Quantitative E-Business System Design Method 定量电子商务系统设计方法
Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.80
Lixin Zhou
This paper presents a quantitative e-business system design method. At first we put forward the requirements for e-business quantitatively. Then we put forward a quantitative e-business design model for e-business system. In this paper we try to find digital values in the process of software architecture design. Our target is to design software architectures more objectively, which makes the software architectural design process become an effective quantitative process. Finally, we present an example for e-business system in this paper.
本文提出了一种定量电子商务系统的设计方法。首先定量地提出了电子商务的要求。然后提出了电子商务系统的定量电子商务设计模型。本文试图在软件架构设计过程中寻找数字价值。我们的目标是更加客观地设计软件架构,使软件架构设计过程成为一个有效的量化过程。最后,本文给出了一个电子商务系统的实例。
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引用次数: 3
The Hedonic Method towards Higher-Level Compilation of Online CPI 面向网络CPI高层次编制的享乐主义方法
Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.37
Yadong Huang, Y. Chai, Yi Liu, H. Chu
Traditionally, direct weighting method is adopted in the calculation of price index in a region. Under the online shopping environment, there are significant differences in consumer spending in different E-commerce enterprises, because the business scope, the main commodities, and the target consumers vary a lot in different enterprises. If the direct weighting method is adopted, the price index of an E-commerce enterprise with lower price increase of all commodities may be higher than the one with higher price increase. The solution is there should be diverse weights of commodities in different enterprises. This paper proposes the Hedonic method towards higher-level compilation of online CPI: elementary price index is regarded as a function of enterprise property and commodity property, and price index by category is calculated using least square method. In addition, the linear form and exponential form of Hedonic method are provided. At last, the Hedonic method is tested by calculating the chain and fixed base price index with real data, and the result shows that not only the testing results but also the price index of the linear form and the exponential form are very similar.
传统上,区域价格指数的计算采用直接加权法。在网络购物环境下,不同电子商务企业的消费者支出存在显著差异,这是因为不同企业的经营范围、主要商品、目标消费者都有很大差异。如果采用直接加权法,则所有商品价格涨幅较低的电子商务企业的价格指数可能高于价格涨幅较高的电子商务企业。解决的办法是不同的企业应该有不同的商品权重。本文提出了在线CPI更高层次编制的Hedonic方法:将初级价格指数作为企业属性和商品属性的函数,采用最小二乘法计算分类价格指数。并给出了Hedonic方法的线性形式和指数形式。最后,用实际数据对Hedonic方法进行了链和定基价格指数的计算,结果表明,不仅测试结果,线性形式和指数形式的价格指数也非常相似。
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引用次数: 0
A novel method to measure graph similarity 一种测量图相似度的新方法
Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.38
Xu Wang, Jihong Ouyang
A novel method to measure the graph similarity is proposed, where the labels, in-degrees, and out-degrees of the vertices in the graph are comprehensively considered in order to conquer the high complexity and information loss in the measurement process. In this proposal, the graph is decomposed into a generalized tree and its similarity can be measured by computing the cost of the node sequence triples in the generalized tree. The proposed method decreases the computational complexity to O(n2) in comparison with the other available graph similarity methods. An example is provided to illustrate that the method is feasible and effective.
提出了一种新的图相似度度量方法,该方法综合考虑了图中顶点的标签、入度和出度,克服了测量过程中的高复杂性和信息丢失问题。该方法将图分解为一棵广义树,通过计算广义树中节点序列三元组的代价来衡量其相似度。与其他可用的图相似度方法相比,该方法将计算复杂度降低到O(n2)。算例说明了该方法的可行性和有效性。
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引用次数: 0
A Multi-viewed Document Representation for Semantic Document Exchange 语义文档交换的多视图文档表示
Pub Date : 2015-10-23 DOI: 10.1109/ICEBE.2015.34
Shuo Yang, J. Guo
Exact document interpretation is very important to semantic document exchange. An essential issue for document interpretation is to maintain semantic consistency of the exchanged documents between any two autonomous business communities, where the document sender and receiver have no misunderstanding in using the exchanged documents. Existing approaches to resolving this issue adopt document standards or apply business ontologies. While these approaches are effective in certain degree, the issue of limited flexibility and evolvement in using standards and the lack of accuracy in using ontologies to mediate document elements must be explored and resolved. This paper proposes a multi-viewed tabular document (Tabdoc) approach to achieving consistent document interpretation between document writers and readers. In this approach, any document is a table, which is seen as a tree to represent document structure. Concepts, layout and grammatical relations of a same document are separated from the document structure and form different views in Tabdoc model.
准确的文档解释对语义文档交换非常重要。文档解释的一个基本问题是在任何两个自治的业务社区之间保持交换文档的语义一致性,在这种情况下,文档发送方和接收方在使用交换文档时不会产生误解。解决此问题的现有方法采用文档标准或应用业务本体。虽然这些方法在一定程度上是有效的,但必须探索和解决使用标准的灵活性和演变有限以及使用本体调解文档元素缺乏准确性的问题。本文提出了一种多视图表格文档(Tabdoc)方法,以实现文档编写者和读者之间一致的文档解释。在这种方法中,任何文档都是一个表,它被视为表示文档结构的树。在Tabdoc模型中,同一文档的概念、布局和语法关系从文档结构中分离出来,形成不同的视图。
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引用次数: 2
期刊
2015 IEEE 12th International Conference on e-Business Engineering
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