基于商业智能的小区日用水量预测模型研究

商业智能现在已广泛应用于各个领域,利用商业智能可以对趋势预测做出良好的支持,本文将其中一种常用商业智能的工具——数据仓库技术,应用于小区家庭的用水量预测研究。     

A generic model for building design

The design of building structures has benefited considerably through computer automation, but further developments in this field are still required. This paper presenis a generic approach to computer automation of the detailed design of building structures. Because of its high level of abstraction, the resulting model is applicable to a wide range of structure types. Other advantages include the use of a consistent data model for software design and implementation, abstract data types for the representation of engineering data, the ability to represent heuristic knowledge, and the ability to evaluate design results in an intelligent manner.     

A generic model for software architectures

In other industries, the idea of build corporate culture by establishing a common level of “best practice” is widely known and used. The architecture concept directly supports this goal for our industry and can help us improve problem areas dominated by organizational and social issues, such as health care organizations, educational systems, and so on. Our proposed reference model for architecture specification and development is organized around a set of aspects that structure concepts and rules; these, in turn, specify a conceptual architecture. We have added principles and guidelines to the concepts and rules to give a more complete picture of the architecture and to provide a place to store and communicate successfully applied design patterns and other knowledge related to the architecture. Adding architectural elements is a step toward a more constructive type of architecture representation. Our current research is focused on further refining these concepts and developing a formal specification of the architecture reference model. We are continuing to test our ideas in case studies, such as applying our model to the OSCA architecture and the application machine concept. We are also developing a prototype architecture editor, and we are testing different tools to learn more about integrating them into a real infrastructure and to learn what typical services an infrastructure must provide     

A model of customer relationship management and business intelligence systems for catalogue and online retailers

As more retailers evolve into customer-centric and segment-based business, business intelligence (BI) and customer relationship management (CRM) systems are playing a key role in achieving and maintaining competitive advantage. For the past ten years, the authors have had the rare opportunity of observing and interviewing employees and managers of three different management teams at three separate Fingerhut companies as they experimented with various ITs for their companies. When the first Fingerhut company peaked in 1998, as many as 200 analysts and 40 statisticians mined the database for insights that helped predict consumer shopping patterns and credit behaviour. Data mining and BI helped Fingerhut spot shopping patterns, bring product offerings to the right customers, and nurture customer relationships. By 1998, Fingerhut was the second largest catalogue retailer in the U.S. with revenues nearing $2 billion. However, after Federated acquired Fingerhut in 1999 and made it a subsidiary, Fingerhut Net, it suffered great losses and was eventually liquidated. Finally, a new company, Fingerhut Direct Marketing, was resurrected in 2002 under a new management team, and it once again became successful. What went right? What went wrong? The paper concludes with CRM and BI systems success factors and a discussion of lessons learned.     

FACETS: A cognitive business intelligence system

A cognitive decision support system called FACETS was developed and evaluated based on the situation retrieval (SR) model. The aim of FACETS is to provide decision makers cognitive decision support in ill-structured decision situations. The design and development of FACETS includes novel concepts, models, algorithms and system architecture, such as ontology and experience representation, situation awareness parsing, data warehouse query construction and guided situation presentation. The experiments showed that FACETS is able to play a significant role in supporting ill-structured decision making through developing and enriching situation awareness.     

基于支持向量机的商务智能系统综合评价研究*

在建立商务智能系统(BIS)综合评价指标体系的基础上,应用支持向量机,研究了BIS综合评价问题,通过仿真实验发现基于支持向量机(SVM)综合评价的测试排序与专家排序保持一致,且测试结果的相对误差较小。结果表明,基于支持向量机的综合评价方法能较好地反映BIS评价问题的序结构,是一种研究BIS综合排序评价问题的有效方法。     

A generic model for Immersive Documentation Environments

We propose a generic model for designing systems relying on augmented reality techniques in the context of an Immersive Documentation Environment (IDE). This model encompasses a user/system interaction paradigm, system architecture and exploitation scenario. We illustrate the use of this model on several virtually documented environment systems providing the user with enhanced interaction capabilities. These systems are dedicated to several applications where the operator needs natural (hands free) access to information, to carry out measurements and/or operate on devices (e.g. maintenance, instruction). These systems merge live images acquired by a video camera with synthetic data (multimedia documents including CAD models and text) and present the result properly registered in the real world. Vocal commands as well as multimodal interaction, associating speech and gesture, are used to improve interaction.     

A generic data model for moving objects

Moving objects databases should be able to manage trips that pass through several real world environments, e.g., road network, indoor. However, the current data models only deal with the movement in one situation and cannot represent comprehensive trips for humans who can move inside a building, walk on the pavement, drive on the road, take the public vehicles (bus or train), etc. As a result, existing queries are solely limited to one environment. In this paper, we design a data model that is able to represent moving objects in multiple environments in order to support novel queries on trips in different surroundings and various transportation modes (e.g., Car, Walk, Bus). A generic and precise location representation is proposed that can apply in all environments. The idea is to let the space for moving objects be covered by a set of so-called infrastructures each of which corresponds to an environment and defines the available places for moving objects. Then, the location is represented by referencing to the infrastructure. We formulate the concept of space and infrastructure and propose the methodology to represent moving objects in different environments with the integration of precise transportation modes. Due to different infrastructure characteristics, a set of novel data types is defined to represent infrastructure components. To efficiently support new queries, we design a group of operators to access the data. We present how such a data model is implemented in a database system and report the experimental results. The new model is designed with attention to the data models of previous work for free space and road networks to have a consistent type system and framework of operators. In this way, a powerful set of generic query operations is available for querying, together with those dealing with infrastructures and transportation modes. We demonstrate these capabilities by formulating a set of sophisticated queries across all infrastructures.     

A new generic approach to model reduction for complex physiologically based drug models

This paper explores the identification problem when dealing with physiological models relating to anaesthetic drugs such as fentanyl. The Mapleson model for drug concentration, which will be the focus of this study, is described by algebraic equations, which are derived from the laws of physics and chemistry, and there are some limitations in its system's analysis, i.e. in the study of its relevant dynamics, and its exploitation from a control design viewpoint. Hence, we propose to represent this model via dynamic differential equations with a reduced number of variables using MATLAB–SIMULINK. Using Mapleson's approach for modelling, the input–output data for each organ can be obtained under a particular drug regimen which in turn can be used to obtain a continuous time-transfer function fit for each of these organs.     

Advanced topic modeling for social business intelligence

Social business intelligence combines corporate data with user-generated content (UGC) to make decision-makers aware of the trends perceived from the environment. A key role in the analysis of textual UGC is played by topics, meant as specific concepts of interest within a subject area. To enable aggregations of topics at different levels, a topic hierarchy has to be defined. Some attempts have been made to address the peculiarities of topic hierarchies, but no comprehensive solution has been found so far. The approach we propose to model topic hierarchies in ROLAP systems is called meta-stars. Its basic idea is to use meta-modeling coupled with navigation tables and with dimension tables: navigation tables support hierarchy instances with different lengths and with non-leaf facts, and allow different roll-up semantics to be explicitly annotated; meta-modeling enables hierarchy heterogeneity and dynamics to be accommodated; dimension tables are easily integrated with standard business hierarchies. After outlining a reference architecture for social business intelligence and describing the meta-star approach, we formalize its querying expressiveness and give a cost model for the main query execution plans. Then, we evaluate meta-stars by presenting experimental results for query performances and disk space.     

基于Web访问信息挖掘的商业智能发现研究

针对Web访问信息的特征和现有数据挖掘方法的局限性,提出将传统数据挖掘算法改进后扩展应用于电子商务环境,实现对Web访问信息进行深层次分析以获取商业智能的思路,从实际应用的角度设计了一个基于Web访问信息挖掘的应用模型,给出了若干关键技术实现的方法,并用改进后的FP-growth算法对电子商务客户访问数据进行兴趣关联规则挖掘实验,验证了挖掘模型的可行性和有效性.     

A generic model for semantics-based versioning in projects

Large projects generally involve a number of phases and evolve over a period of time. Several revisions of the individual artifacts consisting of the project take place during the various phases. These revisions and refinements are normally captured as different versions using configuration/version management tools. But the semantics of these refinements with respect to the project are not captured by existing mechanisms. In addition to the above, a change in the semantics of a project artifact may require suitable changes in other related artifacts. Existing mechanisms for configuration management do not provide mechanisms for change propagation based on the change semantics. In this paper, we propose a generic model for semantics-based version management in projects, which can be built over existing tools. The model also provides support for capturing how changes propagate in a project. We then elucidate the generality of the model by applying it to a project involving a CAD framework and a software development project     

A generic stochastic model for supply-and-return network design

This paper presents a generic stochastic model for the design of networks comprising both supply and return channels, organized in a closed loop system. Such situations are typical for manufacturing/re-manufacturing type of systems in reverse logistics. The model accounts for a number of alternative scenarios, which may be constructed based on critical levels of design parameters such as demand or returns. We describe a decomposition approach to this model, based on the branch-and-cut procedure known as the integer L-shaped method. Computational results in an illustrative numerical setting show a consistent performance efficiency of the method. Moreover, the stochastic solution features a significant improvement in terms of average performance over the individual scenario solutions. A modeling and solution methodology as presented here can contribute to the efficient solution of network design models under uncertainty for reverse logistics.     

基于Web Services的商业智能系统研究与设计

针对传统商业智能存在移植性、集成性和可扩展性差等弱点,研究基于Web Services的商业智能平台.在分析商业智能当前应用状况和商业智能体系结构的基础上,给出了整个系统比较完善的解决方案,构建了基于Web服务的新型的数据ETL和前端展现方式,引入语义层作为数据仓库到商业智能服务器的连接中间层,增强了可理解性和可扩展性.     

基于产业链型数据的分布式隐私保护商务智能研究

随着经济的快速发展,当前很多企业构成了产业链,通过对其进行分布式的商务智能分析,能够获取很多有价值的信.研究了适用于产业链型数据的大规模分布式隐私保护数据挖掘架构,重点研究基于安全多方计算技术的分布式隐私保护数据挖掘通用算法组件,特别是研究面向产业链型数据的分布式隐私保护数据挖掘算法.该研究不仅将有助于大规模分布式环境下的隐私保护数据挖掘系统的研发,而且能够达到更好地服务经济的目的.     

Strong tracking filter based adaptive generic model control

Generic Model Control (GMC) is a control algorithm capable of using nonlinear process model directly. Parameters in GMC controllers are easily tuned, and measurable disturbances can be compensated effectively. However, the existence of large modeling errors and unmeasurable disturbances will make the performance of GMC deteriorate. In this paper, based on the theory of Strong Tracking Filter (STF), a new approach to Adaptive Generic Model Control (AGMC) is proposed. Two AGMC schemes are developed. The first is a parameter-estimation-based AGMC. After introducing a new concept of Input Equivalent Disturbance (IED), another AGMC scheme called IED-estimation-based AGMC is further proposed. The unmeasurable disturbance and structural process/model mismatches can be effectively overcome by the second AGMC scheme. The laboratory experimental results on a three-tank-system demonstrate the effectiveness of the proposed AGMC approach.     

A framework for the operationalization of monitoring in business intelligence requirements engineering

Business intelligence (BI) is perceived as a critical activity for organizations and is increasingly discussed in requirements engineering (RE). RE can contribute to the successful implementation of BI systems by assisting the identification and analysis of such systems’ requirements and the production of the specification of the system to be. Within RE for BI systems, we focus in this paper on the following questions: (i) how the expectations of a BI system’s stakeholders can be translated into accurate BI requirements, and (ii) how do we operationalize specifically these requirements in a system specification? In response, we define elicitation axes for the documentation of BI-specific requirements, give a list of six BI entities that we argue should be accounted for to operationalize business monitoring, and provide notations for the modeling of these entities. We survey important contributions of BI to define elicitation axes, adapt existing BI notations issued from RE literature, and complement them with new BI-specific notations. Using the i* framework, we illustrate the application of our proposal using a real-world case study.     

Self-service business intelligence and analytics application scenarios: A taxonomy for differentiation

Self-service business intelligence and analytics (SSBIA) empowers non-IT users to create reports and analyses independently. SSBIA methods and processes are discussed in the context of an increasing number of application scenarios. However, previous research on SSBIA has made distinctions among these scenarios only to a limited extent. These scenarios include a wide variety of activities ranging from simple data retrieval to the application of complex algorithms and methods of analysis. The question of which dimensions are suitable for differentiating SSBIA application scenarios remains unanswered. In this article, we develop a taxonomy to distinguish among SSBIA applications more effectively by analyzing the relevant scientific literature and current SSBIA tools as well as by conducting a case study in a company. Both researchers and practitioners can use this taxonomy to describe and analyze SSBIA scenarios in further detail. In this way, the opportunities and challenges associated with SSBIA application can be identified more clearly. In addition, we conduct a cluster analysis based on the SSBIA tools thus analyzed. We identify three archetypes that describe typical SSBIA tools. These archetypes identify the application scenarios that are addressed most frequently by SSBIA tool providers. We conclude by highlighting the limitations of this research and suggesting an agenda for future research.

     

A quantitative correlation coefficient mining method for business intelligence in small and medium enterprises of trading business

Business intelligence based on data mining has been one of the popular and indispensable tools for identifying business opportunity in sales and marketing of new products. The traditional data mining methods based on association rules may be inadequate in completely uncovering the hidden patterns of sales based on transaction records. This paper presents a qualitative correlation coefficient mining method which is capable of uncovering hidden patterns of sales and market. Hence, a prototype business intelligence system (BIS) named correlation coefficient sales data mining system (CCSDMS) has been developed and successfully trial implemented in a selected reference site. A series of experiments have been conducted to evaluate the performance of the proposed system. The results generated by the BIS are compared with a well known market available data mining system. The proposed quantitative correlation coefficient mining method is found to possess higher accuracy, better computational effectiveness and higher predictive power. With the new approach, associations for product relations and customer periodic demands are revealed and this can help to leverage organizational marketing capital to enhance quality and speed of promotions as well as awareness of product relations.