Organizing Multiple Data Sources for Developing Intelligent e-Business Portals

Enterprise applications usually involve huge, complex, and persistent data to work on, together with business rules and processes. In order to represent, integrate, and use the information coming from the huge, distributed, multiple sources, we present a conceptual model with dynamic multi-level workflows corresponding to a mining-grid centric multi-layer grid architecture, for multi-aspect analysis in building an e-business portal on the Wisdom Web. We show that this integrated model will help to dynamically organize status-based business processes that govern enterprise application integration. We also present two case studies to demonstrate the effectiveness of the proposed model in the real world. The first case study is about how to organize and mine multiple data sources for behavior-based online customer segmentation, which is the first crucial step of personalization and one-to-one marketing. The second case study is about how to evaluate and monitor data quality, which in return can optimize the knowledge discovery process for intelligent decision making. The proposed methodology attempts to orchestrate various mining agents on the mining-grid for integrating data and knowledge in a unified portal developed by a service-oriented architecture.     

基于服务协作中间件的动态流程模型

新兴的面向服务体系结构正在加速软件的发展和变化,无法适应动态环境的应用将逐渐失去作用,尤其对那些面临着需求频繁变更的业务流程管理系统而言更是如此.为了响应这种现实需求,基于Web服务和业务流程管理技术,提出了服务协作中间件(service cooperation middleware,简称SCM)模型,探讨了其内部机理与协作流程元模型的形式化.通过引入模型转换,扩充流程状态空间,定义了动态流程模型,动态流程的结构重构和行为自适应可以借助SCM的反射能力得以实现.针对SCM模型,设计了流程虚拟机(prrocess virtual machine,简称PVM),流程在运行时由PVM控制执行.借助于模型驱动机制,业务流程可从设计到运行不断地进行模型变换.由此建立的业务流程能够更灵活、更广泛地适用于各种开放环境,提升企业分布计算.     

Understanding corporate data models

Corporate data models are widely used to support data management within organisations. However, both IS professionals and business users find them difficult to understand. This paper describes a methodology for designing and representing corporate data models that uses explanation and visualisation mechanisms to improve understanding, and reports a case study of the use of the methodology in the development of a data warehouse. The methodology was shown to be effective in that a high quality corporate data model was designed and then understood and utilised by all the participants. The model was used as an active, hypertext interface to the first prototype of the data warehouse. The case study findings indicated that: scenarios are useful for eliciting information requirements and explaining abstract concepts in the model to business users; graphical icons and subject area partitions are effective means of visualising the model and lead to improved understanding of the model by business users; and design rationale is an effective means of explaining the evolution of concepts in the model for specialist data modellers.     

面向服务的企业架构*

定义了面向服务的企业架构、业务过程和活动类型,分析了企业架构内涵的演化、概念框架和服务视角,并在传统企业建模、IT规划和企业架构的基础上提出了面向服务企业架构及其规划过程,为分析面向服务环境下企业的业务、IT及其一致性提供了公共的理解和交流基础,有助于企业实时监控IT架构运营状况,进而预测、评估和优化企业业务过程性能,实现企业间的业务过程协作建模与执行.     

A novel rule-centric object oriented approach for document generation

Complex business models in large-scale enterprises deal with voluminous knowledge based on which most decisive official and technical documents are generated. Nowadays, template processors are available for generating such documents. However, the existing template processors are either labor intensive or complicated to suit well-established business model and knowledge repositories in a heterogeneous environment. Hence, a novel generalized adaptable and flexible template processor that utilizes the existing resources without modifying the business model is proposed. The tacit business intelligence defined as rules, knowledge repositories and document structure are the nodal agents of this approach. Further, an XML based Object Query Definition Markup Language for rule definition is newly suggested. The rules are reorganized into hierarchical DAG structured rules using a transformation algorithm and traversed using hybrid traversal. The required output document is represented through a template. Object wrappers act as the communicating agent between diversified datasets and the templates. The proposed architecture is modeled and implemented using set theory. It is experimented in a web-based distributed environment using JAVA and tested using a real world dataset of a large-scale engineering enterprise. The results demonstrate its adaptability and extensibility to any multi-organizational structure.     

A soft knowledge modeling approach for geographically dispersed financial organizations

Fund management is a major function for most financial sector enterprises with geographically dispersed activities. The risk associated to such managerial decisions affects directly the continuity, profitability and reputation of the enterprise. This paper presents a knowledge modeling methodology tool to act as a decision support mechanism for geographically dispersed financial enterprises. The underlying research addresses the problem of financial information capture and representation by utilizing the soft computing characteristics of Fuzzy Cognitive Maps (FCMs). By using FCMs, the proposed mechanism generates a hierarchical and dynamic network of interconnected financial knowledge concepts, simulates the operational efficiency of distributed organizational models with imprecise relationships and quantifies the impact of geographically dispersed activities to the overall business performance. Generic adaptive maps offer an alternative approach to financial management based on strategic level knowledge modeling and integrate hierarchical FCMs into the decision making model of typical financial sector enterprises. Finally, this paper discusses experiments with the proposed mechanism and comments on its usability.     

一种将业务规则与BPEL有效集成的方法

业务规则是定义和约束企业业务结构与业务行为的规定或规范，是企业业务运作和管理决策所依赖的重要资源。当前，面向服务的计算变得越来越流行，Web services已经成为集成互联网上分布和异构应用程序的通用技术。使用Web服务合成语言BPEL可以将不同服务提供者提供的服务整合成新的服务。然而，这种基于流程的合成语言缺乏在合成过程中使用由不同的业务规则引擎管理的业务规则的能力。因此提出了一种将业务规则与BPEL集成的方法。     

Enterprise Modeling and Decision-Support for Automating the Business Rules Lifecycle

Business rules represent policies, procedures and constraints regarding how an enterprise conducts its business. To get the full benefits of modeling business rules requires an approach to managing them through their full lifecycle, from acquisition through deployment and evolution. The research reported in this paper is aimed at determining what infrastructure capabilities are needed to provide this lifecycle support. The solution embodies a modeling framework that captures the structure of the enterprise, in terms of which the business rules can be expressed, and decision-support capabilities for reasoning about and deriving business rules. The paper demonstrates the possibility of automatic support of the business rules lifecycle by automatically generating business rules from the captured information, along with data representing domain assumptions in a case study (the London Ambulance System). A system was implemented to illustrate the methodology and to demonstrate the feasibility of the approach. The methodology also gives guidance on how to deal with pragmatically important situations such as rules that involve both automated and human tasks, nondeterministic rules, and goal-oriented versus operational rules.     

Prioritization of association rules in data mining: Multiple criteria decision approach

Data mining techniques, extracting patterns from large databases are the processes that focus on the automatic exploration and analysis of large quantities of raw data in order to discover meaningful patterns and rules. In the process of applying the methods, most of the managers who are engaging the business encounter a multitude of rules resulted from the data mining technique. In view of multi-faceted characteristics of such rules, in general, the rules are featured by multiple conflicting criteria that are directly related with the business values, such as, e.g. expected monetary value or incremental monetary value.

In the paper, we present a method for rule prioritization, taking into account the business values which are comprised of objective metric or managers’ subjective judgments. The proposed methodology is an attempt to make synergy with decision analysis techniques for solving problems in the domain of data mining. We believe that this approach would be particularly useful for the business managers who are suffering from rule quality or quantity problems, conflicts between extracted rules, and difficulties of building a consensus in case several managers are involved for the rule selection.     

Decision supporting functionality in a virtual enterprise network

Enterprises are now facing growing global competition and the continual success in the marketplace depends very much on how efficient and effective the companies are able to respond to customer demands. The Internet has provided a powerful tool to link up manufacturers, suppliers and consumers to facilitate the bi-directional interchange of useful information. The formation of virtual enterprise network is gathering momentum to meet this challenge. The idea of virtual enterprise network is meant to establish a dynamic organization by the synergetic combination of dissimilar companies with different core competencies, thereby forming a “best of everything” consortium to perform a given business project to achieve maximum degree of customer satisfaction. In this emerging business model of virtual enterprise network, the decision support functionality, which addresses the issues such as selection of business partners, coordination in the distribution of production processes and the prediction of production problems, is an important domain to be studied. This paper attempts to introduce a Neural On-Line Analytical Processing System (NOLAPS), which is able to contribute to the creation of decision support functionality in a virtual enterprise network. NOLAPS is equipped with two main technologies for achieving various objectives, including neural network for extrapolating probable outcomes based on available pattern of events and data mining for converting complex data into useful corporate information. A case example is also covered to validate the feasibility of the adoption of NOLAPS in real industrial situations.     

Prioritization of association rules in data mining: Multiple criteria decision approach

Data mining techniques, extracting patterns from large databases are the processes that focus on the automatic exploration and analysis of large quantities of raw data in order to discover meaningful patterns and rules. In the process of applying the methods, most of the managers who are engaging the business encounter a multitude of rules resulted from the data mining technique. In view of multi-faceted characteristics of such rules, in general, the rules are featured by multiple conflicting criteria that are directly related with the business values, such as, e.g. expected monetary value or incremental monetary value.In the paper, we present a method for rule prioritization, taking into account the business values which are comprised of objective metric or managers’ subjective judgments. The proposed methodology is an attempt to make synergy with decision analysis techniques for solving problems in the domain of data mining. We believe that this approach would be particularly useful for the business managers who are suffering from rule quality or quantity problems, conflicts between extracted rules, and difficulties of building a consensus in case several managers are involved for the rule selection.     

基于协同ERP的群体决策支持系统集成化研究模型

首先系统地分析了ERP软件的研究发展现状,明确定义了协同商务时代ERP(Collaboration Business Enterprise Resource Planning,简称CERP或协同ERP)概念模式,其次,对群体决策支持系统(Group Decision Support System, 简称GDSS)研究模进行系统研究,最后,集成协同ERP概念模式与GDSS研究模型,首次提出了基于协同 ERP的 GDSS集 成化研究模型。     

企业应用软件架构分析

通过对企业业务体系的根本需求进行分析,描述了企业业务及其支持软件的特点.从时间和空间两个维度上对企业软件架构进行了描述,通过分析企业应用软件架构与企业业务改进过程的关系,对架构的开发和部署过程提出了一些建议.     

Unternehmensarchitektur – Literaturüberblick und Stand der Praxis

Organization and management of enterprise architecture have gained increasing significance in recent years. Enterprise architecture management is based on a consistent, aggregate model of the enterprise in order to support decisions such as the design of business areas and products, corresponding business processes and organizational structures as well as application systems and infrastructure operations. Stakeholders have heterogeneous requirements concerning the views on enterprise architecture. The resulting model itself has to be manageable and has to deliver benefits. This article provides an overview of the state-of-the-art of enterprise architecture / enterprise architecture management in the literature as well as current practices in companies. In addition to a literature overview, current practices are presented based on results of an empirical study.     

基于业务行为与业务对象约束的业务规则研究

研究了一类基于业务行为与业务对象约束的业务规则。从业务需求的复杂业务规则出发，探讨了这类复杂业务规则的含义，以及业务行为和业务对象、业务约束的关系。在此基础上，对此类业务规则提出了一种形式化描述。提出了此类业务规则驱动的面向对象建模方法。实例表明，该方法较好地解决了由于类之间关系改变使得应用程序频繁变化的问题。     

面向业务过程的企业应用集成方法

业务过程集成是企业应用集成的核心,文章根据企业业务过程集成的需要提出了面向业务过程的企业应用集成方法。并根据在业务过程集成中业务过程逻辑与应用过程逻辑相分离的原则,以J2EE应用服务器为集成平台通过利用JMS消息传递机制和基于JCA规范的连接器实现了应用系统之间的消息传递解偶和消除了不同应用系统对异构数据格式的依赖。     

基于数据包络和数据挖掘的财务危机预测模型研究

以往的企业财务危机预测研究只能预测企业是否具有财务危机,无法预测企业财务危机的程度,这是由于在界定企业财务危机时,只依据了企业是否为ST企业的分类方式。鉴于此,通过数据包络分析法,近一步细化了企业财务危机的分类,再使用关联规则算法筛选出重要的预测变量,最后使用决策树技术构建企业财务危机预测模型,并对分类的有效性和预测的准确率进行了验证。实证结果表明,基于数据包络和数据挖掘的财务危机预测模型既能保持较高的准确率,又能预测企业财务危机的程度,使得预测结果更具有参考价值。     

基于CAFISE Framework的高适应性面向服务软件开发

在企业及电子政务应用中,由资源分布异构及需求动态变化而产生的问题越来越严重,如何让应用快速适应这些变化一直是人们关注的一个研究难题.首先给出了一个面向服务的支持业务端编程的适应性软件结构框架CAFISE(convergent approach for information system evolution)Framework,然后给出了基于该框架的面向服务的适应性软件开发方法.CAFISE Framework对异构资源的服务化、业务化及开放动态的面向服务软件体系结构提供了较好的支持.基于该结构框架的开发方法,从对影响软件的环境要素分析入手,通过质量属性驱动的体系结构分析,重点针对应用要适应的变化进行结构设计,最终通过以体系结构为基础的业务端编程,实现面向服务应用的即时开发与演化.在实际项目中的使用及实验证明:用该框架和方法开发的面向服务应用,能够较好地适应异构资源的动态变化及用户业务变更,能以较低的代价实现企业及电子政务面向服务应用的持续演化.     

Towards the development of the framework for inter sensing enterprise architecture

Inter-enterprise architecture (IEA) is a new concept that seeks to apply the tools and methodologies of enterprise architecture (EA) in a collaborative context, in order to model collaborative organizations in an inclusive manner. According to the main enterprise architectures proposed to this point, an EA should be conformed at least for a framework, a methodology and a modelling language. Sensing enterprise (SE) is an attribute of an enterprise or a network that allows it to react to business stimuli originating on the Internet. These fields have come into focus recently, and there is not evidence of the use of IEA for modelling a SE, while finding an interesting gap to work on. Thus, this paper proposes an initial framework for inter sensing enterprise architecture (FISEA), which seeks to classify, organize, store and communicate, at the conceptual level, all the elements for inter-sensing enterprise architectures and their relationships, ensuring their consistency and integrity. This FISEA provides a clear idea about the elements and views that create collaborative network and their inter-relationships, based on the support of Future Internet.