• Journal of Information Technology Services
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• v.2 no.2
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• pp.87-95
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• 2003

With the increasing proliferation of World Wide Web, electronic mail systems have become very widely used communication tools. Researches on e-mail classification have been very important in that e-mail classification system is a major engine for e-mail response management systems which mine unstructured e-mail messages and automatically categorize them. in this research we develop e-mail classifiers for e-mail Response Management Systems (ERMS) using naive bayesian learning and centroid-based classification. We analyze which method performs better under which conditions, comparing classification accuracies which may depend on the structure, the size of training data set and number of classes, using the different data set of an on-line shopping mall and a credit card company. The developed e-mail classifiers have been successfully implemented in practice. The experimental results show that naive bayesian learning performs better, while centroid-based classification is more robust in terms of classification accuracy.

• Journal of Information Technology Applications and Management
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• v.10 no.4
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• pp.51-63
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• 2003

This study designs and implements a new approach to the classification of e-mail requests from customer based on machine learning techniques. The work on building an electronic mall classifier can be cast into the framework of text classification, since an e-mail is a viewed as a document, and judgement of interest is viewed as a class level given to the e-mail document. It is also implemented an e-mall based automated response system that integrate with Call Center in a practical use.

• Journal of Intelligence and Information Systems
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• v.9 no.2
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• pp.121-133
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• 2003

Due to the rapid growth of Internet, means of communication with customers in a traditional customer support environment such as telephone calls are being replaced by mainly e-mail in a Web-based customer support system. Although such a Web-based support is efficient and promises potential benefits for firms, including reduced transaction costs, reduced time, and high quality of support, there are some difficulties associated with responding to many types of customer's inbound e-mails appropriately. As many types of e-mail are received, considerable attention is being paid to methods for increasing the efficiency of managing and responding e-mails. This research proposes an intelligent system for managing customer's inbound e-mails in organizations by applying case based reasoning technique for responding to various customers' inbound e-mails more effectively. In this approach, a case is represented as a frame-typed data structure corresponding to an inbound e-mail, keywords, and its reply e-mail. In the retrieval procedure, keywords and affinity set is developed to index a case, and then the case is represented as a vector, a case vector. Also, cosines value is calculated to measure the similarity between a new inbound e-mail and the cases in the case base. In the adaptation procedure, we provide several adaptation strategies to adapt and modify the retrieved case. The strategies guide to make an outbound e-mail using product databases, databases for customer support, etc. Additionally, the Web-based system architecture is proposed to implement our methodology. The proposed methodology and system will be helpful for developing more efficient Web-based customer support.

• Proceedings of the KAIS Fall Conference
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• 2003.11a
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• pp.185-190
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• 2003

Due to the rapid growth of Internet, means of communication with customers in a traditional customer support environment such as telephone calls are being replaced by mainly e-mail in a Web-based customer support system. Although such a Web-based support is efficient and promises potential benefits for firms, including reduced transaction costs, reduced time, and high quality of support, there are some difficulties associated with responding to many types of customer’s inbound e-mails appropriately .As many types of e-mail are received, considerable attention is being paid to methods for increasing the efficiency of managing and responding e-mails. This research proposes an intelligent system for managing customer’s inbound e-mails in organizations by applying case based reasoning technique for responding to various customers' inbound e-mails more effectively. In this approach, a case is represented as a frame-typed data structure corresponding to an inbound e-mail, keywords, and its reply e-mail. In the retrieval procedure, keywords and affinity set is developed to index a case, and then the case is represented as a vector, a case vector. Also, cosines value is calculated to measure the similarity between a new inbound e-mail and the cases in the case base. In the adaptation procedure, we provide several adaptation strategies to adapt and modify the retrieved case. The strategies guide to make an outbound e-mail using product databases, databases for customer support, etc. Additionally, the Web-based system architecture is proposed to implement our methodology. The proposed methodology and system will be helpful for developing more efficient Web-based customer support.

• IE interfaces
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• v.18 no.1
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• pp.10-21
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• 2005

With the increasing proliferation of World Wide Web, electronic mail systems have become very widely used communication tools. Researches on e-mail classification have been very important in that e-mail classification system is a major engine for e-mail response management systems which mine unstructured e-mail messages and automatically categorize them. In this research we compare the performance of Naive Bayesian learning and Centroid-Based Classification using the different data set of an on-line shopping mall and a credit card company. We analyze which method performs better under which conditions. We compared classification accuracy of them which depends on structure and size of train set and increasing numbers of class. The experimental results indicate that Naive Bayesian learning performs better, while Centroid-Based Classification is more robust in terms of classification accuracy.

• Journal of Internet Computing and Services
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• v.9 no.2
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• pp.139-145
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• 2008

CRM(Customer Relationship Management) improves the competitiveness of small companies to large enterprises. E-mail, SMS (Short Message Service), telephony service, DM (Direct Mail) are used for customer response in many companies. In order to improve company's profit, business diversification is in progress with protecting the succession of existing customers, and the only of new customers. Futhermore, BPR (Business Process Re-engineering) and BPM (Business Process Management) of the CRM can be easily found in many companies, because it is the first contact point to the company at the customer's view. This paper discusses the development of CRM, and proposes a call object routing agent that is the main engine of the CRM. Result of performance evaluation of proposed method show that the system is effective and powerful enough to use at the multi-channel environment.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.7
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• pp.520-533
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• 2007

The CRM(Customer Relationship Management) is the business strategy model for higher profits and competitive power of the enterprise in a new business environment. The large-scale customer response service technique uses internet, e-mail, SMS (Short Message Service), Telephony service, DM(Direct Mail) by customer channel point. Recently, business model diversify for new contract and retaining existing customer to the effort for a profitable model of business. This paper is based on Avaya PDS(Predictive Dialing System) model for CRM bond center. If the number of "available" agents are less than the number of inbound channels, then there may be real-time response problems in PDS system implemented. The Organization cannot afford to have many agents in available mode because of the high cost of manpower. This paper provides two contributions to the study. First, we present Call Object Management Mechanism of Customer Channel integration for reduce outbound consulting and reduce CallBack data in the PDS. Second, we design and implement the proposed system. Our simulation results show analysis of old model and proposed model. The proposed model can be efficiently used in Large-scale CRM.

• The KIPS Transactions:PartC
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• v.9C no.3
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• pp.359-366
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• 2002

Nowadays, the hacking techniques are developed increasingly with wide use of internet. The recent type of scanning attack is appeared in against with multiple target systems on the large scaled domain rather than single network of an organization. The development of scan detection management system which can detect and analyze scan activities is necessary to prevent effectively those attacking at the central system. The scan detection management system is useful for effective utilization of various detection information that received from scan detection agents. Real time scan detection management system that can do the integrated analysis of high lever more that having suitable construction in environment of large scale network is developed.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.445-447
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• 2001

본 논문에서는 콜센터를 위하여 설계 및 구현된 전자메일 자동응답 및 관리 시스템 주에서 서버 시스템에 해당하는 뿐을 기술하였다. 본 연구에서는 도메인에 특성화된 표현 형식 개발을 개발하여 보다 효율적인 3단계 매칭방법을 가진 자동응답기, 학습에 기반한 도메인 비의존적인 자동분류기 및 적용방법의 재배열이 가능한 담당자 분배기를 구현하였다.

• The Transactions of the Korea Information Processing Society
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• v.7 no.5S
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• pp.1708-1718
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• 2000

In the operating of electronic commerce system, the information about consumer purchasing intention to product through e-mail has caused the problems in the management aspects. These are the using of information again and response to the situations promptly in consumer purchasing intension, etc. Moreover, it has brought out the issues timely to operate the electronic commerce system strategically with reapplication of consumer intention information. In this studies, the agent system AWEC(Agent Windows for EC) was proposed as an alternative paln, which charges of he getting and transmitting information of consumers intension in the electronic commerce system. In this proposed AWEC, the functional structure and working allocation were executed. And also eh performance of the proposed system is analyzed and evaluated through experiment.