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Associated rule mining has become a common subject in data mining research field that is very popular used for marketing basket analysis. The discovery knowledge pattern mined can provide insight to the data holder as well as be invaluable in important task, such as decision making and strategic planning. This paper presents an associated rule mining technique that significantly helping for improvement...
Human Resource department (HR) plays vital and tedious role in recruiting manpower for organization and forced to use more accurate talent evaluation applications for selecting multi-talented personnel based on resumes, received in huge quantity but most of the talent evaluation applications are based on evaluating talent but not risk factors. This paper presents the solution for selecting appropriate...
Real-time monitoring data mining has been a necessary means of improving operational efficiency, economic safety and fault detection of power plant. Based on the data mining arithmetic of interactive association rules and taken full advantage of the association characteristics of real-time test-spot data during the power steam turbine run, the principle of mining quantificational association rule...
To improve the intelligibility and efficiency of knowledge expression for the land evaluation, a land evaluation method combining simplified fuzzy classification association rules with fuzzy decision is proposed in this paper. To reduce the complexity of the land evaluation models and improve the efficiency and intelligibility of fuzzy classification association rules further, an algorithm to eliminate...
To dynamic increasing databases, the data dynamic reduction and decision-making rule mining are treated by the methods of repeat scan, order, search, reduction data set traditionally, this paper proposes a new mining algorithm, which treat two dispart table simultaneously by using program' many course parallel technology. This method improves greatly mining efficiency of the system, is of important...
Real-world data mining is a complex problem-solving system. In real data mining applications, more and more researchers realized the need from traditional data mining to knowledge discovery to deliver useful knowledge for the business decision-making. Thus, actionable knowledge discovery is introduced during the context. This study draws on analysis of the applications of actionable knowledge discovery...
This paper introduces improving rate and proposes the incremental mining algorithm with the weighted model for optimizing association rules based on CBA mining algorithm. The risk analysis of the strong association rules is proposed for trend forecasting. And the risk degree of the lost rules based on the incremental mining is also analyzed. Comparing with the traditional algorithm, the improved algorithm...
Supplier selection has a critical effect on the competitiveness of the entire supply chain network. It is not only a significant work in supply chain management but also a complex decision making problem which includes both qualitative and quantitative factors. Research results indicate that the supplier selection process appears to satisfy different evaluation criteria and business model in deciding...
Recent initiatives in defence related information systems have emphasised the need to bring together information from multiple sources and fuse it into a form suitable for decision makers. This paper outlines a four stage system for fusing unstructured and semi-structured text and numerical data by extraction of entities and relations, identification of duplicate entities, organisation into the most...
This paper introduces the application of association rules methods in data mining and the FP-tree algorithm for mining association rules in commercial sales analysis. It begins with the discussion of the concepts of association rules, followed by the analysis of mining for association rules and the FP-tree algorithm, and ended with their applications in commercial sales analysis as well as the demonstration...
Supplier selection and evaluation are one of the most critical activities of a company in today's competitive business world. Partnering with the suppliers has become a key factor to the success of an organization. The selection of supplier, satisfying different evaluation criteria, is therefore of main importance and builds the topic of this paper. This selection process is a difficult decision and...
The ability to have an insight into customer "values and action" is the foundation for enhancing managerial decision-making effectiveness and customer relationship. From the perspective of customer value, this paper proposes the customer "value-action" insight analysis model based on data mining technology. The assessment of customer value, subdivision and cluster of the customers,...
As data collection and data storage rates are growing at an exponential pace in the business world in this information age, data mining is becoming a key component of electronic commerce. Trends shows definitely that future decision making system in e-commerce would weigh on even quicker and more reliable technology used for data analysis. Confronted with huge mountains of data in business transactions,...
Negative association rules (NARs) catch mutually exclusive correlations among items. They play important roles in decision-making. But nowadays the techniques of NARs mining focus on mono-database. With the rapid development of information and communication technologies, multi-database mining is becoming more and more important. Knowledge conflicts within databases may occur when mining both the positive...
Product design case databases contain a lot potential knowledge, which can tell us the relations among parameters and some interesting experience patterns. While designing product, it is supposed to support the designers to make decisions better. Therefore many researchers are trying to find an effective approach to discover the unknown knowledge. In this paper, we presented several algorithms which...
With increasingly prevalent of E-learning, the intelligent Q/A system arise at the historic moment. In this paper we proposed an improved text cluster algorithm, with the improved association rules algorithm, it can classify the information in the database accurately according to the questions, locate the user's question fast and therefore speeds up the inquiry rate. The experimental result indicates...
Association rule mining (ARM) identifies frequent itemsets from databases and generates association rules by assuming that all items have the same significance and frequency of occurrence in a record i.e. their weight and utility is the same (weight=1 and utility=1) which is not always the case. However, items are actually different in many aspects in a number of real applications such as retail marketing,...
This paper introduces improving rate and proposes the incremental mining algorithm for optimizing association rules based on CBA mining algorithm. Comparing with the traditional algorithm, the improved algorithm is fast, efficient in incremental data mining and can find trends in association rules. The decision making reliability is enhanced by the association rules obtained from the improved algorithm...
This paper presents the weighted model in the incremental mining algorithm and proposes risk analysis of the strong association rules for trend forecasting. We also analyze the risk degree of the lost rules based on the incremental mining. In practical application, the new method improves the precision of the incremental mining and efficiently uses the mining results for the factual decision-making...
Association rule mining is concerned with the discovery of interesting association relationships hidden in databases. Traditional algorithms are only considering the constraints of minimum support and minimum confidence. However, sometimes it is essential to find stronger association rules for decision makers possessing inadequate resources, and sometimes less strong rules are needed. In this paper,...
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