An Electronic Market Space Architecture Based On Intelligent Agents And Data Mining Technologies

This paper presents an overview of current trends in electronic Business (E-Business), and discusses how an enterprise can use the Electronic Market space based on intelligent agents and data mining techniques to its strategic advantage. We define an agency as a multi-agent system created by integrating agents, selected from a library of reusable agents that have formed a federation. A federation of agents comprises of a set of registered agents, witch are themselves complete knowledge-based system [1].multi-agent system, e-business, data mining, artificial neural networks

An intelligent integrated e-Government framework: The case of Jordan

This research develops a framework for e-governments that integrates personalization of services, such as intelligent software agents (ISA), integrating technologies, such as web services (WS) and Enterprise Service Bus (ESB), and data analytics such as data mining (DM) and business intelligence (BI). The paper focuses on government-to-citizen (G-to-C) model that seamlessly exchanges data and information among three citizen-based government services: passport, automobile, and civil services. Intelligent software agents will act as a liaison between users: namely citizens, management, and the databases. For citizens, the ISA will remind each citizen with timely-based, expiration-based, and requirements-based of these three activities. For the manager, ISA will activate data-mining/business intelligence request to query the database for patterns, trends, and predict certain unexpected flow of activities. This type of framework would enable countries to enter the fifth stage of e-government (networked), where data from every department is integrated together

A Blueprint for Applications in Enterprise Information Portals

Electronic Commerce (E-Commerce, EC) is thoroughly changing business models of organizations (governments, corporations, and communities) and individuals the way of living and working. However, the major success will accrue to those companies that are willing to transform their organizations and business processes, which is the scope of e-Business. An Enterprise Information Portal (EIP) provides real time information and integrated applications to knowledge workers, employees, customers, business partners and the general public as well. Effective applications of EIP facilitate high quality strategic decisions. That is, an EIP can enhance an organization’s productivity, improve the collaboration to facilitate E-Commerce and gain competitive advantages. However, the EIP solutions are usually too expensive to small businesses. With Enterprise Application Integration (EAI) approach, this paper presents an economic way to design a low-cost EIP that leverages existing systems. Moreover, a prototype is implemented to show the feasibility. For the external data access, the web mining technology is utilized to mine some relevant and valuable web contents from the Internet and put these contents into the document warehouse. By combining the textual information inside the document warehouse and the numeric data from the data warehouse, competitive advantages can be provided over those who work with just the numbers

Security challenges and solutions for e-business

The advantages of economic growth and increasing ease of operation afforded by e-business and e-commerce developments are unfortunately matched by growth in cyber attacks. This paper outlines the common attacks faced by e-business and describes the defenses that can be used against them. It also reviews the development of newer security defense methods. These are: (1) biometrics for authentication; parallel processing to increase power and speed of defenses; (2) data mining and machine learning to identify attacks; (3) peer-to-peer security using blockchains; 4) enterprise security modelling and security as a service; and (5) user education and engagement. The review finds overall that one of the most prevalent dangers is social engineering in the form of phishing attacks. Recommended counteractions include education and training, and the development of new machine learning and data sharing approaches so that attacks can be quickly discovered and mitigated

An Electronic Market Space Architecture Based On Intelligent Agents And Data Mining Technologies

This paper presents an overview of current trends in electronic Business (E-Business), and discusses how an enterprise can use the Electronic Market space based on intelligent agents and data mining techniques to its strategic advantage. We define an agency as a multi-agent system created by integrating agents, selected from a library of reusable agents that have formed a federation. A federation of agents comprises of a set of registered agents, witch are themselves complete knowledge-based system [1]

Mobile agents over e-business

[[abstract]]Due to the popularization of Internet and World Wide Web (WWW), thelimitation of distance and region are broken for business behaviors.E-Commerce can help a company or enterprise to extend its market placeto unlimited region. Agent technique is one of the importanttechnologies developed to support the Internet applications.Especially, the Internet and WWW technologies broken the limitation ofspace of enterprise marketing, and the agent techniques solve theproblems of temporality. Because of when the users are off-line, theagents are still active in the world of computer network and play therole of their users. In this paper, a mechanism is proposed forelectronic marketplace based on agents and mobile agents. There aresome issues will be researched. They include the platform of mobileagents, the types and classifications of agents and mobile agents,behaviors of commerce transactions and processing models, negotiationmechanisms, authentication and security, ...etc. Moreover, theyinclude the techniques of information retrieval, data mining, andknowledge base, ...etc. Based on this architecture of E-marketplace,the applications of E-commerce will be more effective, easier todevelop, and more creating the marketing of business.[[sponsorship]]淡江大學[[notice]]補正完畢[[conferencetype]]國際[[conferencetkucampus]]淡水校園[[conferencedate]]20010926~20010928[[booktype]]紙本[[iscallforpapers]]Y[[conferencelocation]]臺北縣, 臺

Time Series Data Mining: A Retail Application Using SAS Enterprise Miner

Modern technologies have allowed for the amassment of data at a rate never encountered before. Organizations are now able to routinely collect and process massive volumes of data. A plethora of regularly collected information can be ordered using an appropriate time interval. The data would thus be developed into a time series. With such data, analytical techniques can be employed to collect information pertaining to historical trends and seasonality. Time series data mining methodology allows users to identify commonalities between sets of time-ordered data. This technique is supported by a variety of algorithms, notably dynamic time warping (DTW). This mathematical technique supports the identification of similarities between numerous time series. The following research aims to provide a practical application of this methodology using SAS Enterprise Miner, an industry-leading software platform for business analytics. Due to the prevalence of time series data in retail settings, a realistic product sales transaction data set was analyzed. This information was provided by dunnhumbyUSA. Interpretations were drawn from output that was generated using “TS nodes” in SAS Enterprise Miner

Model-driven Enterprise Systems Configuration

Enterprise Systems potentially lead to significant efficiency gains but require a well-conducted configuration process. A promising idea to manage and simplify the configuration process is based on the premise of using reference models for this task. Our paper continues along this idea and delivers a two-fold contribution: first, we present a generic process for the task of model-driven Enterprise Systems configuration including the steps of (a) Specification of configurable reference models, (b) Configuration of configurable reference models, (c) Transformation of configured reference models to regular build time models, (d) Deployment of the generated build time models, (e) Controlling of implementation models to provide input to the configuration, and (f) Consolidation of implementation models to provide input to reference model specification. We discuss inputs and outputs as well as the involvement of different roles and validation mechanisms. Second, we present an instantiation case of this generic process for Enterprise Systems configuration based on Configurable EPCs