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Skyline queries are useful in many applications such as multicriteria decision-making, data mining, and user-preference queries. However, the probability that a point dominates another one reduces significantly as the number of dimensions increases, which results in the number of skyline points becoming too numerous to offer any interesting insights. The concept of the k-dominant skyline was previously...
Customer Relationship Management (CRM) is an overall process of building and retaining profitable customers with an organization and directed towards improving business relationship with customers. With analysis of customer data in the CRM database helps to create new approach to lead the business strategies. Analytical CRM helps to analyze customer data and interactions through various data mining...
Single-criteria decision making queries can be answered using simple SQL queries, however a multi-criteria decision making problems are often not answered by normal SQL queries. In order to solve these types of queries we may need to use co-operative query languages etc. However using additional query based system incurs extra cost. Moreover, if the criteria in a query are complementary to each other...
Extracting the data and information from manual data repository is difficult, costly and time-consuming. They have prospects for making decision in construction process. Decision making can be performed by collecting data timely and cost effectively from the data warehouse by providing a model of the decision making process and programming pertinent knowledge into it. Data mining automates the process...
Modern societies produce a huge amount of open source information that is often published on the Web in a natural language form. The impossibility of reading all these documents is paving the way to semantic-based technologies that are able to extract from unstructured documents relevant information for analysts. Most solutions extract uncorrelated pieces of information from individual documents;...
Data mining is a knowledge discovery process which deals with the broad process of finding knowledge in data analyzing large storage of data in order to identify the relevant data. It is a powerful tool to uncover relationships within the data. Business intelligence (BI), is a distinctive term that refers to a lot of software applications, it is normally used to investigate a company's raw data for...
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...
Most of the databases are multi-relational, but the existing data mining approaches verify the classification rules in a single data relation. This paper introduces an efficient algorithm for mining important classification rule for multi-relational database using distributed data mining ideas. To achieve this, an Intelligent Agent is used. An Intelligent agent is an entity that observes and acts...
In this paper, we have proposed a novel algorithm based on Ant Colony Optimization (ACO) for finding near-optimal solutions for the Multi-dimensional Multi-choice Knapsack Problem (MMKP). MMKP is a discrete optimization problem, which is a variant of the classical 0-1 Knapsack Problem and is also an NP-hard problem. Due to its high computational complexity, exact solutions of MMKP are not suitable...
In the process of software production, testing is the premise to guarantee the quality of software. With the extensive application of network software, Web security test has become a key point that can not neglect. Based on the Analytic Hierarchy Process (AHP) algorithm, a new kind of Web security testing programme was introduced in this paper. According to which it realized the Web Security auto-Testing...
World Wide Web is a huge data repository and is growing with the explosive rate of about 1 million pages a day, web log records each access of the web page and number of entries in the web logs is increasing rapidly. These web logs, when mined properly can provide useful information for decision-making. Sequential pattern mining discovers frequent user access patterns from web logs. Since Apriori-like...
Previous studies have focused on serveral aspects of CRM (Customer Relationship Management). However, there is a lack of research that focuses on the customer segmentation of shipping enterprises using data mining. Data mining technology can be used to in modern CRM to greatly enhance it function and efficiency. Based on the technologies of clustering and classification in data mining, this paper...
Electronic patient record mining deals with the implicit and useful medical information stored in the electronic patient record database. By this technology the useful knowledge is extracted and the scientific and auxiliary decision-making is proved for the diagnosis and treatment of disease. In this paper, a rough knowledge mining algorithm (named RKMA) based on extension decision rule lattice is...
This article gives the requirement, theory and common character of manage information system base on indicator evaluation system, by analyzing the system. Then according to the principal of designing the common indicator evaluation system, the analyzing and designing method of system are given. It can provide the more effective and reasonable method and reference of how to analyze and design the information...
Cognitive maps, one of the hot topic in the research of computational intelligence, have been widely used in knowledge representation and decision-making. In mining of cognitive maps on the basis of data resources, outlier data seriously affect the accuracy of cognitive maps. Therefore, this paper, based on the analysis of traditional ones, proposes a new outlier data detection algorithm. The algorithm...
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...
Conceptual hierarchy represents the relationship between objects or concepts in a hierarchical form. The work presented here focuses on creating hierarchies which have a relationship between parent and child nodes but not between siblings. When we evaluate or classify certain objects (e.g., service quality), we often use a conceptual hierarchy which has various items (concept) at its nodes. If the...
In this paper, a more subjective Synthesis Evaluation algorithm is studied, in which hierarchy of criteria is generated through analysing the internal structure of research data by using exploratory factor analysis, weights are determined by using confirmatory factor analysis and with the application of TFN, more reliable judgements and reasonable evaluation results will be acquired. Furthermore,...
Recommender Systems have emerged as an imperative research domain ever since the explosion of information on the web made it impractical to review the exhaustive data in search of specific/valuable content. The application of this technique in various e-commerce related fields have exposed several downsides related to the process through which the online user profiles are evaluated, the semantics...
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...
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