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Data mining has been gaining popularity in knowledge discovery field. In recent years, data mining based intrusion detection systems (IDSs) have demonstrated high accuracy, good generalization to novel types of intrusion, and robust behavior in a changing environment. Still, significant challenges exist in design and implementation of production quality IDSs. Masquerade attacks pose a serious threat...
The five-year survival rate of liver cancer is low, 14% according to the Surveillance, Epidemiology, and End Results (SEER) Program database of the National Cancer Institute from 2003 to 2007 [3]. Since in the early stages of liver cancer, patients usually do not show signs or symptoms, improving early diagnosis is essential in order to reduce morbidity and mortality rates.
Association rules are an important branch of data mining. Aiming at the update maintenance problem of association rules when increase the database data while keep the minimum support unchanged, on the basis of FUP algorithm, this paper proposes a matrix-based incremental association rules mining algorithm, namely MBFUP algorithm. The algorithm just scans the database once, and doesn't produce candidate...
Web data mining is a key tool for e-commerce in such an age of Internet. Due to previous studies, there is no such a mining technology superior to others. Therefore, this paper can give a simplified comprehension of web data mining and indicate the improvement direction of each kind of mining algorithm based on their existing defects. This paper first introduces the main process of data mining, including...
The Moroccan financial system has undergone major changes since the early 90s. The financial market authority makes available a multitude of public information and statistics on the financial operations of the issuers. Other than the classification by sector or by type and / or amount of the issue, there is no classification model to predict the behavior of an issuer based on financial indicators...
Granular association rule mining is a new relational data mining approach to reveal patterns hidden in multiple tables. The current research of granular association rule mining considers only nominal data. In this paper, we study the impact of discretization approaches on mining semantically richer and stronger rules from numeric data. Specifically, the Equal Width approach and the Equal Frequency...
The use of so-called fuzzy numbers for approximate calculations leads to significant problems, because the underlying mathematical structure is weaker than ordinary arithmetic. Many of these problems arise from the fact that the fuzzy quantities are actually fuzzy intervals. Gradual numbers were recently proposed as a better representation for fuzzy quantities. In this paper, we describe the X-μ approach,...
Data, especially in large item sets, hide a wealth of information on the processes that have created and modified them. Often, a data-field or a set of data-fields are not modified only through well-defined processes, but also through latent processes; without the knowledge of the second type of processes, testing cannot be considered exhaustive. As a matter of fact, changes in the data deriving from...
Learning Materials are structured as Learning Objects and are available in Learning Object Repository(LOR) which are used in various courses of an Elearning environment. Learning Management System aggregates these objects found in LOR, provides an infrastructure and platform through which learning content is delivered and managed. Adaptation, personalization, usage statistics are some of the LMS functionality...
This paper applies Association Rule Mining algorithm to sports management, especially mining relationship from data on performance of Indian cricket team in one day international (ODI) matches. This analysis will help in determining factors associated with the match outcome so as to enable the team to formulate match winning strategies. Data has been obtained from secondary sources to obtain deeper...
In this paper, the intelligent recommended algorithms of association rule and collaborative filtering (CF) technology are designed to solve the problem of low utilization and waste time in the usage of digital library. Neighbor user sets are generated by CF and user-user association firstly, and then recommended lists are generated by URL association rule based on the history of neighbor user set...
In recent years, the library service has become more and more to meet the requirements of customers personalized service. With the rapid development of computer technology, the use of data mining technology can effectively achieve the goal. in using data mining technology, realization of the algorithm is the key, there are some problems to realize the personalized service in the use of the classical...
Ontology has become a very vital issue to solve important issues regarding human diseases through data integration of chemical and biological data. Mining such data discovers highly important knowledge about diseases can give an important insight to arrive to new drug targets and assist in personalized medicine. In the current paper, a mining technique for diseases is developed based on integrated...
The view that sampling technology could improve the efficiency of data mining significantly has been widely accepted by the research community. The key to sample in data mining is how to design a sampling strategy to get a favorable sample to execute the mining algorithm at minor cost of accuracy. In this article we propose a progressive sampling algorithm based on confusion matrix to determine the...
With the rapid development of communication network, management and maintenance about network becomes more and more difficult. Fault management for a network management system is essential and very important. It has direct impact on the performance of network management system. This paper analyzed and studied the application of Apriori algorithm and association rule in network fault management system.
Communication Network exist a large number of alarm information. Through the data mining method to mine these alarm information to develop and establish the intelligent network alarm correlative rules analysis system. This article uses the data mining method to mine alarm association rules in massive alarm information. According to the characteristic of alarms and the type of network element in the...
The main difference of the associative classification algorithms is how to mine frequent item sets, analyze the rules exported and use for classification. This paper presents an associative classification algorithm based on Trie-tree that named CARPT, which remove the frequent items that cannot generate frequent rules directly by adding the count of class labels. And we compress the storage of database...
There exists certain relevance between many different courses generally, and usually a course is also a prerequisite for other courses. However, under current credit system, students have many choices in taking courses and arranging the course sequences, generally resulting in different achievements for students of different course sequences and different teaching efficiency. Based on the method of...
To maximize customer profitability, companies should exert effort to acquire new customers, as well as to retain existing customers and add value. An efficient way of achieving such goals is to explore and profile customers' past purchase behavior and mine out their possible further needs and wants. When faced with increasingly diversified consumption demands, customers should be segmented based on...
Due to the pressure from work load and daily life, there is an increase in geriatric depression population. However, some people may not notice or have no idea about the symptom of melancholia. More research input is needed to diagnose severity of melancholia at an early stage. To help users diagnose their physical fitness and mental health condition before outpatient service, two approaches are considered...
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