面向商业智能的数据挖掘算法和多智能体系统的体系结构以及优化
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摘要
目前，对于组织机构，数据挖掘大势所趋、广为应用。因为不管何时何地，一切皆为数据。为了有效应对，他们聘请数据处理专家，探索动态的开发工具和方法。热衷于隐私保护的人则关心数据的处理、管理以及再应用。科学家、数据员，技术专家以及企业家期望找到新的方法来搜索、提取，并预测可用的信息和知识。数据挖掘，商业智能和多智能体系统作为一种单一的搜索技术已经非常成熟。在当代商务领域，科技及工程理论、数据建构、存储设施都已基本完备。然而用工具和专属技术来挖掘有价值的信息，准确获取和传递数据，仍面临挑战。因此，发展一种信息整合的、智能的方法处理、管理和有效地利用数据，涌现出大量的需求，也是迎接数据时代挑战的根本之路。在信息技术发展，商业的动态性，用户的需求以及导致商业成功的背景中，对于优化工具、智能体的应用及其性能，至关重要。然而,单一的工具或是代理技术不能满足目前的商业需求，我们需要寻求一种可视化的、在大数据中挖掘有效信息的途径，在此前提下，多方法融合的智能的数据处理、管理和使用方法应运而生。
本文研究了一种一般化的方法，对于发展物理、生物以及社会系统的一般模型有贡献意义。本研究主要侧重于研究大数据是如何有效利用的，来更好地发挥出信息的力量。在本文中，我们引入了基于商业智能的数据挖掘、多智能体系统的集成模式，提出了一种简单的一般推测模型和挖掘算法。该方法可以可扩展性地发展多个商业智能工具，可以让用户方便地根据所需传播信息的动态架构。为了搜索大范围的数据，我们采用了一种系统新颖的方法，优化了现有的工具和应用智能体的技术。为现代商业系统的优化提供了一种可行方法。这些尝试是对传统挖掘技术的革新，可以生成一种通用模型，结合了物理、生物、社会系统的特点，进行商业智能系统的配置。此外，多种挖掘算法和技术也经过了作者深入的比较、探讨和改进。
此外，本文还尝试了两种不同分支间的重要交融。一是商业和科学的交融，把传统的挖掘方法和商务智能相结合，主要体现在第3、5、6和7章。技术细节和算法可以通过商务智能工具DW，OLAP, OLTP和在其他动态建模基础上量化和实现，并允许用户按需接入和传播数据。这是一种对于高级工具使用的代理技术在大数据上应用的新尝试，可以用于优化现有的商务智能系统。第二点融合是应用工具与代理技术的交融，并以可视化的形式呈献给用户，这要求决策者、用户、研究人员在传统商务流程中加入软实力来重建商务模式，第8、9和10章做了具体探讨。全文第4章是商务预期探讨，而第11章是对现有方法的融合及尝试。因此，没有工具的应用和代理技术，就谈不上商务决策的优化和效率。数据挖掘和多智能体系统的集成是处理大数据的可视化工具。这些可视化信息对于商业或者整个组织机构有易读性，为普适计算，数据数字化提供了一条有效路径。目前，对于商业组织，数字化已经不再是一个选择，而成为必备的技术手段，因为集成和智能方法的问题求解，性能优化和风险削减，也是现代商务的基本任务和方法，即“从信息时代到知识时代的转变”，是研究集成的应用和代理技术的科学方法。集成的应用和代理技术能够动态的自适应的解决各种问题。归根结底，数据挖掘是以解决实际问题为导向的。本论文的重要成果总结如下：-处理商业挑战的单一方法在诸多原因的限制下并不都是有效的。在本文中，我们讨论并提出了一种新颖的智能工具和智能体集成技术。该技术对于特定的商业需求，能给出最好的自适应方案，供决策者做出最优的判断。-可视化图示对于情景的概念化具有挑战。纵观文献，人们尝试了各种模型来应对这些棘手的问题。本文提出并发展了一种通用商业智能模型，并集成了数据挖掘算法。这些挖掘算法对于挖掘复杂而海量的数据是非常有必要的，并且它可以通过描画许多相关知识来辅助商业智能系统以及信息挖掘过程，以扩展用户的能力。-该研究所用的通用模块提供了一个共用框架，对概念和词表进行精确的识别、描绘，在分析各种商业活动中，缩短了决策者和专家之间的距离，可以对商务问题多角度地进行描述。
本论文工作将分为三大部分，包括：（i）第1，2，3章讨论了研究的理论与技术，并做出需求分析。（ii）第4，5，6，7章引入模型与算法，进行新的系统构想。（iii）第8，9，10，11章提供了建模和性能评价，并展开了具体应用，第12章是结论与未来的研究方向。
本论文的第6章到第11章由12篇论文作为支撑，其中包括6篇已发表文章（EI：2，国际会议：2，数据挖掘方面的书籍章节：2）。其他的6篇文章（其中1篇已录用）在审稿修订中。除此之外，本研究工作由9个相关主题课堂作业支撑，其中5篇论文已被国际会议收录。
These days, organizations using DM are not a choice, since, everything is data, and it collects or generateseverywhere, in every activity or process that they are falling all over it, which hire data scientists anddynamic exploratory tools in comprehensive systems. Since, privacy advocates are concerned about thiswealthy handling, managing and reuse. Therefore, Scientists, data explorer, and users scramble to findnew ways to search, extract and change into a presumable object “that is information and knowledge."DM, BI and MAS for searching valuable information are well matured and in the modern businesses orother fields’ data/information and storage facilities, structures are no longer big issues. However, singleapproaches for tools and agent technologies could not be addressed business challenges, which theapplication tools and technologies as individual approaching of searching valuable information and accessor disseminations are problems that visualize how organizations are starving information. It is theemerging of an integrated and intelligent way of handling, managing, using the available data.
Therefore, in this dissertation, we introduced and deeply discussed on Architectures and Optimization of aParadigm Integrating for DM and MAS with BI. It is a fundamental way of avoiding these challenges andsystematic tactics and scenarios, which is essential to optimize tools and agent's applications andperformance in parallel to the growth of IT, business's dynamisms, users’ desires and domain contextsthat led to the ultimate goal of business success. We applied different modeling architecture andalgorithms based on scientific theories and principles as the domain context and users need. Theapproaches are an IET or changes of the classic mining process into an integrated and intelligent systemto optimizing BI performance and application. The outcomes of the dissertation are developing a genericmodel, which are significant to describe physical, biological and social systems that can be a singleinference and crosscutting model. Besides to these, innovative and novel modeling and mining algorithmsand techniques are introduced, explored and evaluated.
Furthermore, this dissertation has two fundamental interventions, such as Science and business. As asconce intervention, it is the approaches of change of classical mining approach into an integrated andintelligent system. Chapter3,5,6and7mainly focused on it. The details' techniques and algorithms arecapable and scalable to involve various BI tools such as DW, OLAP, OLTP and others in dynamicarchitecture bases that allowing users to access and disseminate data/information as they need. It is amethodical and novel approach to optimize advanced tool's applications and agents’ technologies toexplore the available large-scale data, which would be the possible way of optimization the modern BIsystems. The second or business intervention visualized as Integration of tool's applications and agents’ technologies are the newly IET, which requires for decision makers, researchers and users as an effectivemeans to enhance their businesses “soft power” and added value for the reconstruction and revolution ofthe traditional business process. These are mainly discussed on chapter8,9and10, whereas chapter4both data science as the business prospects and chapter11domain based exploration of the proposedapproaches. Therefore, without integrating for tool's applications and agents’ technologies will not end upcomplete and promising conclusions into consideration of efficiency and effectiveness to be solutions ofbusiness challenges.
Integrating for DM and MAS are powerful visualization of large and complex data sets, the kinds ofinformation that would be readily apparent about business or organization as a whole, which provides anaccess of ubiquitous computing, any data, accessing and disseminating that made fetching to improve theBPs of BPM systems. Since it is the issues or demand of efficiency and effectiveness of BP throughintegration and intelligent approach's problem solving, performance optimization and risk mitigation,which the fundamental tasks and methodologies of modern business that help to describe real-worldmatters.“It is the transformation from information to intelligent ages.” It is a paradigm and scientificapproaches of integrating for applications and agent's technologies, which are capable, dynamic andadaptable, various issues and fields. The prominent contribution of this dissertation is summarized asfollows.-Single approaches of tackling business challenges did not effective in many reasons. In thisresearch, we introduced and discussed a novel integration for tools and agents techniques andmethodologies, which gives insight a best adaptation of business scanning system to the specificneeds of the various businesses that allowing decision-makers to optimum decision outcomes,-Graphic representation of challenges and its appropriate solutions, which is vitally significant andeasy to conceptualize the business context. The modern architecture of a generic BI model andmining algorithms are required for mining complex or large-scale data and describes the variousrelevant aspects of BP that help for easing in BI systems and tools to maximize user’s capability.-This research outcome vitally significant to narrow the communication gap between decision-makers and experts by providing them a common reference framework, concepts and vocabularyto be accurate identify and describe or access and analyze the various aspects,
This dissertation is organized into three major categories, which include the (i) research foundation arts oftechnologies, and requirement analysis that discussed in chapter1,2and3.(ii) Models and algorithmsdevelopments and proposed innovative approaches, which discussed in chapter4,5,6and7.(iii) Modeling exploration, discussion and performance measurements, including applications under chapter8,9,10and ii, and final conclusion and research direction in chapter12which followed by the cited list ofreferences.
The dissertation, specifically chapter6-11is supported by12scientific papers, which are6published (2EI indexed journals,2international conference and EI and ISTP indexed, and2by the known publisherData mining Book chapters). The other6(one is accepted, and5under review) in different status andtime. Besides to these, the research work supported by9subject matter courses work papers among these5papers were accepted for international conference.
本文研究了一种一般化的方法，对于发展物理、生物以及社会系统的一般模型有贡献意义。本研究主要侧重于研究大数据是如何有效利用的，来更好地发挥出信息的力量。在本文中，我们引入了基于商业智能的数据挖掘、多智能体系统的集成模式，提出了一种简单的一般推测模型和挖掘算法。该方法可以可扩展性地发展多个商业智能工具，可以让用户方便地根据所需传播信息的动态架构。为了搜索大范围的数据，我们采用了一种系统新颖的方法，优化了现有的工具和应用智能体的技术。为现代商业系统的优化提供了一种可行方法。这些尝试是对传统挖掘技术的革新，可以生成一种通用模型，结合了物理、生物、社会系统的特点，进行商业智能系统的配置。此外，多种挖掘算法和技术也经过了作者深入的比较、探讨和改进。
此外，本文还尝试了两种不同分支间的重要交融。一是商业和科学的交融，把传统的挖掘方法和商务智能相结合，主要体现在第3、5、6和7章。技术细节和算法可以通过商务智能工具DW，OLAP, OLTP和在其他动态建模基础上量化和实现，并允许用户按需接入和传播数据。这是一种对于高级工具使用的代理技术在大数据上应用的新尝试，可以用于优化现有的商务智能系统。第二点融合是应用工具与代理技术的交融，并以可视化的形式呈献给用户，这要求决策者、用户、研究人员在传统商务流程中加入软实力来重建商务模式，第8、9和10章做了具体探讨。全文第4章是商务预期探讨，而第11章是对现有方法的融合及尝试。因此，没有工具的应用和代理技术，就谈不上商务决策的优化和效率。数据挖掘和多智能体系统的集成是处理大数据的可视化工具。这些可视化信息对于商业或者整个组织机构有易读性，为普适计算，数据数字化提供了一条有效路径。目前，对于商业组织，数字化已经不再是一个选择，而成为必备的技术手段，因为集成和智能方法的问题求解，性能优化和风险削减，也是现代商务的基本任务和方法，即“从信息时代到知识时代的转变”，是研究集成的应用和代理技术的科学方法。集成的应用和代理技术能够动态的自适应的解决各种问题。归根结底，数据挖掘是以解决实际问题为导向的。本论文的重要成果总结如下：-处理商业挑战的单一方法在诸多原因的限制下并不都是有效的。在本文中，我们讨论并提出了一种新颖的智能工具和智能体集成技术。该技术对于特定的商业需求，能给出最好的自适应方案，供决策者做出最优的判断。-可视化图示对于情景的概念化具有挑战。纵观文献，人们尝试了各种模型来应对这些棘手的问题。本文提出并发展了一种通用商业智能模型，并集成了数据挖掘算法。这些挖掘算法对于挖掘复杂而海量的数据是非常有必要的，并且它可以通过描画许多相关知识来辅助商业智能系统以及信息挖掘过程，以扩展用户的能力。-该研究所用的通用模块提供了一个共用框架，对概念和词表进行精确的识别、描绘，在分析各种商业活动中，缩短了决策者和专家之间的距离，可以对商务问题多角度地进行描述。
本论文工作将分为三大部分，包括：（i）第1，2，3章讨论了研究的理论与技术，并做出需求分析。（ii）第4，5，6，7章引入模型与算法，进行新的系统构想。（iii）第8，9，10，11章提供了建模和性能评价，并展开了具体应用，第12章是结论与未来的研究方向。
本论文的第6章到第11章由12篇论文作为支撑，其中包括6篇已发表文章（EI：2，国际会议：2，数据挖掘方面的书籍章节：2）。其他的6篇文章（其中1篇已录用）在审稿修订中。除此之外，本研究工作由9个相关主题课堂作业支撑，其中5篇论文已被国际会议收录。
These days, organizations using DM are not a choice, since, everything is data, and it collects or generateseverywhere, in every activity or process that they are falling all over it, which hire data scientists anddynamic exploratory tools in comprehensive systems. Since, privacy advocates are concerned about thiswealthy handling, managing and reuse. Therefore, Scientists, data explorer, and users scramble to findnew ways to search, extract and change into a presumable object “that is information and knowledge."DM, BI and MAS for searching valuable information are well matured and in the modern businesses orother fields’ data/information and storage facilities, structures are no longer big issues. However, singleapproaches for tools and agent technologies could not be addressed business challenges, which theapplication tools and technologies as individual approaching of searching valuable information and accessor disseminations are problems that visualize how organizations are starving information. It is theemerging of an integrated and intelligent way of handling, managing, using the available data.
Therefore, in this dissertation, we introduced and deeply discussed on Architectures and Optimization of aParadigm Integrating for DM and MAS with BI. It is a fundamental way of avoiding these challenges andsystematic tactics and scenarios, which is essential to optimize tools and agent's applications andperformance in parallel to the growth of IT, business's dynamisms, users’ desires and domain contextsthat led to the ultimate goal of business success. We applied different modeling architecture andalgorithms based on scientific theories and principles as the domain context and users need. Theapproaches are an IET or changes of the classic mining process into an integrated and intelligent systemto optimizing BI performance and application. The outcomes of the dissertation are developing a genericmodel, which are significant to describe physical, biological and social systems that can be a singleinference and crosscutting model. Besides to these, innovative and novel modeling and mining algorithmsand techniques are introduced, explored and evaluated.
Furthermore, this dissertation has two fundamental interventions, such as Science and business. As asconce intervention, it is the approaches of change of classical mining approach into an integrated andintelligent system. Chapter3,5,6and7mainly focused on it. The details' techniques and algorithms arecapable and scalable to involve various BI tools such as DW, OLAP, OLTP and others in dynamicarchitecture bases that allowing users to access and disseminate data/information as they need. It is amethodical and novel approach to optimize advanced tool's applications and agents’ technologies toexplore the available large-scale data, which would be the possible way of optimization the modern BIsystems. The second or business intervention visualized as Integration of tool's applications and agents’ technologies are the newly IET, which requires for decision makers, researchers and users as an effectivemeans to enhance their businesses “soft power” and added value for the reconstruction and revolution ofthe traditional business process. These are mainly discussed on chapter8,9and10, whereas chapter4both data science as the business prospects and chapter11domain based exploration of the proposedapproaches. Therefore, without integrating for tool's applications and agents’ technologies will not end upcomplete and promising conclusions into consideration of efficiency and effectiveness to be solutions ofbusiness challenges.
Integrating for DM and MAS are powerful visualization of large and complex data sets, the kinds ofinformation that would be readily apparent about business or organization as a whole, which provides anaccess of ubiquitous computing, any data, accessing and disseminating that made fetching to improve theBPs of BPM systems. Since it is the issues or demand of efficiency and effectiveness of BP throughintegration and intelligent approach's problem solving, performance optimization and risk mitigation,which the fundamental tasks and methodologies of modern business that help to describe real-worldmatters.“It is the transformation from information to intelligent ages.” It is a paradigm and scientificapproaches of integrating for applications and agent's technologies, which are capable, dynamic andadaptable, various issues and fields. The prominent contribution of this dissertation is summarized asfollows.-Single approaches of tackling business challenges did not effective in many reasons. In thisresearch, we introduced and discussed a novel integration for tools and agents techniques andmethodologies, which gives insight a best adaptation of business scanning system to the specificneeds of the various businesses that allowing decision-makers to optimum decision outcomes,-Graphic representation of challenges and its appropriate solutions, which is vitally significant andeasy to conceptualize the business context. The modern architecture of a generic BI model andmining algorithms are required for mining complex or large-scale data and describes the variousrelevant aspects of BP that help for easing in BI systems and tools to maximize user’s capability.-This research outcome vitally significant to narrow the communication gap between decision-makers and experts by providing them a common reference framework, concepts and vocabularyto be accurate identify and describe or access and analyze the various aspects,
This dissertation is organized into three major categories, which include the (i) research foundation arts oftechnologies, and requirement analysis that discussed in chapter1,2and3.(ii) Models and algorithmsdevelopments and proposed innovative approaches, which discussed in chapter4,5,6and7.(iii) Modeling exploration, discussion and performance measurements, including applications under chapter8,9,10and ii, and final conclusion and research direction in chapter12which followed by the cited list ofreferences.
The dissertation, specifically chapter6-11is supported by12scientific papers, which are6published (2EI indexed journals,2international conference and EI and ISTP indexed, and2by the known publisherData mining Book chapters). The other6(one is accepted, and5under review) in different status andtime. Besides to these, the research work supported by9subject matter courses work papers among these5papers were accepted for international conference.
引文
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