Design and implementation of a case-based reasoning system for marketing plans

Unstructured intangible experiences and knowledge are usually difficult to represent and instantiate, which engenders the hardship of knowledge transfer and sharing. Past marketing plans are such valuable documents containing strategic planning knowledge and experiences. Case-Based Reasoning (CBR), which consists of retrieving, reusing, revising, and retaining cases, has been proved effective in retrieving information and knowledge from prior situations and being widely researched and applied in a great variety of problem territories. This paper targets at designing a CBR architecture and a method that facilitate the sharing and retrieving of cases of great concern to the marketing personnel. After an intensive survey of CBR methods and applications, a CBR system embedding multi-attribute decision making method, which provides both overall similarity level and similarity level of each selected attribute, is proposed to enhance the adaptation of a new marketing plan. In addition, a multi-attribute gap analysis diagram is developed to visualize the similarity along with the gap between candidate and target cases, so as to better support interaction and group decision making in the process of strategically formulating a new marketing plan. The CBR system was implemented and successfully demonstrated on case retrieval of a telecommunication company. (C) 2004 Elsevier Ltd. All rights reserved

On-line personalized sales promotion in electronic commerce

Electronic Commerce encompasses all electronically conducted business activities, operations, and transaction processing. With the development of electronic commerce in the Internet, companies have changed the way they connect to and deal with their customers and partners. Businesses now could overcome the space and time barriers and are capable of serving customers electronically and intelligently. However. it is quite a great challenge to attract and retain the customers over Internet due to the low barrier of entrance and severe competition. Personalization, a special form of differentiation, when applied in market fragmentation can transform a standard product or service into a specialized solution for an individual. In this research, an on-line personalized sales promotion decision support system is proposed. The proposed system consists of three modules: (I) marketing strategies, (2) promotion patterns model, and (3) personalized promotion products. The marketing strategies contain sales promotion strategies and pricing strategies. Promotion patterns are generated according to various sales promotion strategies, and the promoted prices for the promotion products are generated by considering both the current stages of business life cycle and product life cycle. In the promotion patterns model, by segmenting the market, customer behaviors of three categories can be analyzed by utilizing data mining techniques and statistical analysis to generate personalized candidate promotion products. Finally. multiple evaluation indicators are used and adjusted to rank and obtain the final personalized promotion products. With the promotion products based on customers past frequent purchase patterns, it has the potential to increase the success rate of promotion, customer satisfaction. and loyalty. In this paper, a prototype system was developed to illustrate how the proposed on-line personalized promotion decision support system works in electronic commerce and a simplified case of performance analysis was conducted for evaluation. (C) 2003 Elsevier Ltd. All rights reserved

A Petri-Net based modeling approach to concurrent software engineering tasks

The rapid growth in demand on information systems and the uncertainties associated with the development process for such systems has revealed problems such as inappropriate human resource management, poor quality, and serious delay. Traditional project management approaches emphasize the importance of scheduling, while careful allocation of resources across projects is critical and has a direct influence on the project quality and time management. According to the report on Concurrent Engineering (CE) implementation, it has significantly improved the time to market, quality, costs, etc. in the manufacturing industry. This research attempts to introduce the philosophy of CE into software project management and proposes a Concurrent Project Modeling Method (CPM-M) to realize concurrent software engineering tasks. CPM-M consists of two components: Concurrent Information Sharing Framework (CISF) and Concurrent Project Modeling Diagram (CPM-D). The CISF is a conceptual framework that facilitates concurrent cross-functional sharing of information among product, activity and resource pools, while the CPM-D inherits capability from the Petri Net and further expands so as to guide the project management by simultaneously considering the three pools at each decision point of the development process. The proposed approach was illustrated and simulated on the development of a web-based campaign system for the marketing division of a bank

Assessing users' product-specific knowledge for personalization in electronic commerce

While many electronic commerce (EC) companies are adopting one-to-one marketing approaches using various personalization technologies to make their products and services unique for the purpose of attracting and retaining customers and improving their completion edges in the EC ecosystem, which, nevertheless, has low entrance barriers for new players to join and further intensify the competition, none or few of them consider a fundamental issue-the user's product-specific knowledge. Our research proposed to add this new domain of the customer's knowledge on appropriate target products into the personalization process as a part of the overall EC strategy for businesses. In this paper, we present our initial design for assessing the user's product-specific knowledge using the proposed innovative method for detecting it directly in a non-intrusive way without asking users to answer or fill out any types of questionnaires. Our method is based on customer's on-line navigation behaviors by analyzing their navigation patterns through pre-trained artificial neural networks. An empirical study designed for a case of EC store selling digital cameras was conducted in our research to prove the concept, and a good preliminary result was derived from the study. For the purpose of comparing the performances between the conventional approach of using questionnaire and the proposed innovative approach of navigation pattern mining, a questionnaire based approach for evaluating the user's product-specific knowledge was designed and incorporated into our knowledge level assessment system (KLAS). Our study result shows that although the pure questionnaire-based KLAS is intrusive and may not be accepted by some users, for those users willing to complete the questionnaire, the proposed navigation pattern approach can be combined with the questionnaire-based approach to create a hybrid KLAS which has a significantly improved accuracy rate in detecting the customer's product knowledge level. (c) 2005 Elsevier Ltd. All rights reserved

A data mining approach to database compression

Data mining can dig out valuable information from databases to assist a business in approaching knowledge discovery and improving business intelligence. Database stores large structured data. The amount of data increases due to the advanced database technology and extensive use of information systems. Despite the price drop of storage devices, it is still important to develop efficient techniques for database compression. This paper develops a database compression method by eliminating redundant data, which often exist in transaction database. The proposed approach uses a data mining structure to extract association rules from a database. Redundant data will then be replaced by means of compression rules. A heuristic method is designed to resolve the conflicts of the compression rules. To prove its efficiency and effectiveness, the proposed approach is compared with two other database compression methods