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The characteristics of e-commerce are described. The function and technology of data mining are analyzed. The processes of data mining in electronic commerce are discussed. A new improved algorithm is proposed through analyzing the advantages and disadvantages of Fp-growth association rules mining. It is proved that the improved algorithm has higher efficiency and lesser memory cost than Fp-growth...
In association rule mining, utility has recently been regarded as a practical measure for a rule's usefulness in that it can reflect the actual amount of output achieved by applying each rule. Even the same rule may have different utilities depending on how well the rule fits a specific business purpose. However, most recent studies have tried to apply a uniform standard to assessing rules disregarding...
As the de facto standard, Business Process Execution Language (BPEL) is widely used in the composition and orchestration of web services; however, it is tiring and error-prone if we just rely on the developers to create every activity icon and assign it an atomic service. On the basis of the author's early work, this paper creatively applies association rules mining to the analysis of BPEL process,...
With the rapid development of online shopping, on-line one-to-one marketing becomes a great assistance to e-shoppers. One of the most important marketing resources is the prior daily transaction records in the database. In this study, the paper propose a new methodology for predict e-shoppers' purchase behavior that uses e-shoppers' purchase sequences. First, transaction clustering is conducted, then...
Knowledge discovery has received more and more attention from the business community for the last few years. One of the most important and challenging problems in it is the definition of discovery process model, which are well understood, efficiency, and quality of outcome. A conceptual infrastructure for knowledge discovery process is proposed with business understanding, model selection and domain...
Information retrieval is the most popular database technology, which is focusing on data analysis, association rules, pattern discovery and so on. It is critical to find efficient ways of mining large data sets. In this paper we present a Personalized Travel Information System, called PTIS. PTIS can automatically link to the travel sites to collect information, and then create new data rules. According...
In data processing of the supermarket, people often use the Apriori algorithm to analyze the customer “shopping basket” Due to the large computation, Apriori algorithm has controlled the number of frequent item sets by using the minimum supporting threshold and pruning techniques, but meaningless frequent item sets still possibly exist. Divide goods into several broad categories and set up the weighted...
For quickly locating the specific user groups in the mobile payment market, this paper investigates and analyzes the Mobile Ticketing in mobile payment service from five main aspects, the users awareness, demand, usage, using willingness and users evaluation. We use data mining methods of association rules to do analysis to 1615 valid questionnaires and locate the user groups who are most likely to...
In the real manufacturing process, many conditions influence its process. However, there are three important factors consisting of final customer feedback information, flexible manufacturing and supplier selection affect the manufacturing process. In order to satisfy the real requirements of manufacturing process, this paper employs association rule mining of data mining technology including the above...
Association rule mining has been an area of active research in the field of knowledge discovery and numerous algorithms have been developed to this end. Of late, data mining researchers have improved upon the quality of association rule mining for business development by incorporating the influential factors like value (utility), quantity of items sold (weight) and more, for the mining of association...
In the paper, we discussed the characteristics of data mining on association rules for multi-dimension data. Then through the multi-dimension data attributes analysis and OLAP operations, we integrate the OLAP and data mining based on their advantages to one method which is called On-Line Analysis Mining (OLAM). Based on OLAM, an algorithm for multi-dimension data on association rules has been reformed...
In this paper, we introduce a web data mining solution to e-commerce to discover hidden patterns and business strategies from their customer and web data, propose a new framework based on data mining technology for building a Web-page recommender system, and demonstrate how data mining technology can be effectively applied in an ecommerce environment.
Text Mining (TM) is the process of analyzing a semantically rich document or set of documents to understand the content and meaning of the information they contain. The research in Text Mining will enhance human's ability to process massive quantities of information, and it has high commercial values. Firstly, the paper discusses the introduction of TM and its definition and then gives an overview...
Mining patterns in large databases is a challenging task facing NP-hard problems. Research focused attention on the most occurrent patterns, although less frequent patterns still offer interesting insights. In this paper we propose a new algorithm for discovering infrequent patterns and compare it to other solutions.
In financial system, the general use of financial data has also been unable to meet the inherent need of the deepening of financial information and management modernization. The financial informationization is faced with needs of the growing use of financial data analysis. Under this background, this paper analyzes the financial income of certain city in a certain period. Association rules are mined...
Efficient Store Management is one important strategy of Category Management, how to get the character of the store and how to classify the stores is the aims of this study. Using the Association to find the goods selling knowledge, building the similarity matrix, and applying the Fuzzy Cluster to classify the stores, so the special promotion to different type of store. The Precision Marketing is realized...
Data mining technology makes it possible to discover knowledge from daily operational data. As we know, Web log contains a lot of information about web users' behavior on the Website, for example, Web users' access path. Information discovered from those data will be very useful to website design and promotion. In this paper, we propose an analysis model by using multidimensional association rules...
Apriori -the classical association rules mining algorithm is a way to find out certain potential, regular knowledge from the massive ones. But there are two more serious defects in the data mining process. The first needs many times to scan the business database and the second will inevitably produce a large number of irrelevant candidate sets which seriously occupy the system resources. An improved...
Association rule mining is a well-known data mining task for discovering association rules between items in a dataset. It has been successfully applied to different domains especially for business applications. However, the mined rules rely heavily on human interpretation in order to infer their semantic meanings. In this paper, we mine a new kind of association rules, called conceptual association...
Data mining aims to discover useful patterns (rules) in large datasets. In order to enhance the interestingness of the patterns produced, we propose an algorithm to mine both association and correlation patterns among items. In the mining process the all-confidence and correlation-confidence measures are adopted simultaneously. The effectiveness of the proposed approach is demonstrated with the experiment...
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