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Showing 1-25 of 2,245 resultsfor "Index Terms":Strong Rules
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Research on strong-association rule based web application vulnerability detection
2009 2nd IEEE International Conference on Computer Science and Information Technology
Year: 2009 | Conference Paper |
Cited by: Papers (7)
With the increase of the web applications in information society, Web application software security become more and more important. Recent investigations show that web application vulnerabilities have become the largest security threat. Websense security report shows that in the first half of year 2008 above 75% of the most popular Web site have utilized by the hackers to run malicious code. Detec...Show More
Ontology-Based Association Rule Quality Evaluation Using Information Theory
2010 International Conference on Computational and Information Sciences
Year: 2010 | Conference Paper |
Cited by: Papers (4)
Support and confidence are two main parameters of association rule mining, the first is used to measure the statistics importance of association rule, and the second is used to measure the reliability of association rule. The quality of association rule does not have quantitative evaluation criterion. In this paper, Quality index is proposed, the subjective and objective aspects are integrated and...Show More
Fuzzy association rules mining algorithm based on output specification and redundancy of rules
2011 IEEE International Conference on Systems, Man, and Cybernetics
Year: 2011 | Conference Paper |
Cited by: Papers (3)
In data mining approach, the quantitative attributes should be appropriately dealt with as well as the Boolean attributes. This paper presents a fast algorithm for extracting fuzzy association rules from database. The objective of the algorithm is to improve the computational time of mining for actual applications. In this paper, we propose a basic algorithm based on the Apriori algorithm for rule...Show More
Mining multilevel association rules with dynamic concept hierarchy
2008 International Conference on Machine Learning and Cybernetics
Year: 2008 | Conference Paper |
Association rule mining has attracted wide attention in both research and application areas recently. The mining of multilevel association rules is one of the important branches of it. In most of the studies, multilevel rules will be mined through repeated mining from databases or mining the rules at each individually levels, it affects the efficiency, integrality and accuracy. In this paper, a no...Show More
A New Method for Eliminating Redundant Association Rules
2010 International Conference on Intelligent Computation Technology and Automation
Year: 2010 | Conference Paper |
As one of the fundamental data mining methods, the association rule mining has widely been used in many fields. However, the existence of massive redundant rules has made the analysis very difficult, and has been a main barrier to efficient utilization of discovered association rules. This paper studies the characteristic of commonsense knowledge which is use to eliminate redundant association rul...Show More
Development of knowledge model for insurance product decision using the associative classification approach
Azuraliza Abu Bakar;Zalinda Othman;Mohd Saiful Nizam Md Yusoff;Ruhaizan Ismail
2010 10th International Conference on Intelligent Systems Design and Applications
Year: 2010 | Conference Paper |
Individual protection, physically or mentally, is very important for someone living in a risk environment. Insurance is one of the individual protections due to accident, blaze, critical diseases or death. Insurance company plays a critical role in providing competitive product insurance that covers flexible features depend on customer requirements. In order to compete with other competitors and f...Show More
An encounter with Strong Association Rules
2010 IEEE 2nd International Advance Computing Conference (IACC)
Year: 2010 | Conference Paper |
Cited by: Papers (1)
Data mining (DM) is the process of automated extraction of interesting data patterns representing knowledge, from the large data sets. Frequent itemsets are the itemsets that appear in a data set frequently. Finding such frequent itemsets plays an essential role in mining associations, correlations, and many other interesting relationships among itemsets in transactional database. In this paper an...Show More
New Criterion for Mining Strong Association Rules in Unbalanced Events
2008 International Conference on Intelligent Information Hiding and Multimedia Signal Processing
Year: 2008 | Conference Paper |
Association rules mining is an important task in data mining and the normal measures support and confidence are useful for finding association rules between the items. However, the process of finding frequent items would prune infrequent items which may include some useful relationships of association patterns. The new measures comsup, comcof and comsup' are proposed to resolve this problem effect...Show More
CSRule: Efficient mining of closed strong association rules in the resource effectiveness matrix
2013 6th International Conference on Biomedical Engineering and Informatics
Year: 2013 | Conference Paper |
Association rules which are used to mine resource failure, can reduce the number of wrong alarm resources to be replaced. In this paper, we proposed an efficient algorithm: CSRule, for mining closed strong association rules based on merging strategies. Firstly, it generates all pairs of association rules which only have two resources; secondly, all the closed strong association rules are mind usin...Show More
Many-to-one mapping: The principle of Chinese medicinal property theory learned from strong association rules
Rui Jin;Chun-miao Xue;Li-li Wu;Bing Zhang;Qian Lin;Sen-mao Liu
2013 Ninth International Conference on Natural Computation (ICNC)
Year: 2013 | Conference Paper |
Knowledge discovery in databases is believed to be a promising technique in the modernization of Traditional Chinese Medicine (TCM), especially for understanding the mysterious TCM theory. Based on the classic literature resources, this paper mined the association rules between the Chinese medicinal property (nature or flavor) and the practical efficacy by the Apriori algorithm. The results showed...Show More
Mining Condensed and Lossless Association Rules by Pruning Redundancy
2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery
Year: 2008 | Conference Paper |
Cited by: Papers (2)
There are excessive and disordered rules generated by traditional approaches of association rule mining, many of which are redundant, so that they are difficult for users to understand and make use of. Han et al pointed out the bottleneck of association rules mining is not on whether we can derive the complete set of rules under certain constraints efficiently but on whether we can derive a compac...Show More
Mining Strong Valid Association Rule from Frequent Pattern and Infrequent Pattern Based on Min-Max Sinc Constraints
Mukesh Poundekar;Amitkumar S. Manekar;Mukesh Baghel;Hitesh Gupta
2014 Fourth International Conference on Communication Systems and Network Technologies
Year: 2014 | Conference Paper |
Cited by: Papers (1)
Rule mining is very efficient technique for find relation of correlated data. The correlation of data gives meaning full extraction process. For the mining of rule mining a variety of algorithm are used such as Apriori algorithm and tree based algorithm. Some algorithm is wonder performance but generate negative association rule and also suffered from multi-scan problem. In this paper we proposed ...Show More
Mining positive and negative association rules
2010 5th International Conference on Computer Science & Education
Year: 2010 | Conference Paper |
Cited by: Papers (9)
Association rule mining is one of the most popular data mining techniques to find associations among items in a set by mining necessary patterns in a large database. Typical association rules consider only items enumerated in transactions. Such rules are referred to as positive association rules. Negative association rules also consider the same items, but in addition consider negated items (i.e. ...Show More
Privacy Preserving Association Rules by Using Greedy Approach
2009 WRI World Congress on Computer Science and Information Engineering
Year: 2009 | Conference Paper |
Cited by: Papers (7)
Data mining techniques have been developed in many applications. However, they also cause a threat to privacy. In this paper, we proposed a greedy method for hiding the number of sensitive rules. The experimental results showed that the undesired side effects can be avoided in the rule hiding process by use of our approach. The results also revealed that in most cases, all the sensitive rules are ...Show More
A New Approach of Self-adaptive Discretization to Enhance the Apriori Quantitative Association Rule Mining
2012 Second International Conference on Intelligent System Design and Engineering Application
Year: 2012 | Conference Paper |
Cited by: Papers (5)
Apriori algorithm was widely applied in association rule mining. Generally, we have to specify different ranges manually to discretize numeral fields to nominal fields, which may weaken the result due to unfit partitions. This paper introduced an approach to make discretized partitions in a self adaptive way to enhance the numeral quantitative association rule mining result.Show More
Implementation of Dynamic Association Rule Mining Using Back Navigation Approach
2015 Fifth International Conference on Communication Systems and Network Technologies
Year: 2015 | Conference Paper |
Cited by: Papers (1)
ARM (Association Rule Mining), one of the most frequently used technique in the domain of data mining and machine learning. Using association rule mining or rule learning extracts the hidden patterns in terms of the association between entities of the training data set. This technique is applied on number of data sets by different researchers and academicians, still this area is under research as ...Show More
An Association Rules Algorithm Based on Biclustering
2011 14th IEEE International Conference on Computational Science and Engineering
Year: 2011 | Conference Paper |
Cited by: Papers (1)
Existing association rules mining algorithm for small scale data have good results, but with a lot of data collection and storage, will greatly reduce the efficiency of the existing algorithm. In this paper transformed association rules problem into Biclustering problem, complete association rule mining well, its efficiency and complexity of the issues is lower than the Apriori algorithm.Show More
DRAC: A Direct Rule Mining Approach for Associative Classification
2010 International Conference on Artificial Intelligence and Computational Intelligence
Year: 2010 | Conference Paper |
Cited by: Papers (1)
The application of associative rule mining in classification (associative classification) has demonstrated its power in recent years. The current associative classifier building often adopts three phases: Rule Generation, Building Classifier and Classification. Unfortunately, in rule generation phase, a large number of rules are usually produced, which could not only slow down the mining process b...Show More
Feature selection based on fuzzy clustering analysis and association rule mining for soft-sensor
Proceedings of the 33rd Chinese Control Conference
Year: 2014 | Conference Paper |
Cited by: Papers (1)
Soft-sensors have been widely used for estimating product quality or other key variables. To achieve high estimation performance for soft-sensor design, it is important to select appropriate input or explanatory variables. This paper presents a new feature selection method applied to Soft-sensors. The proposed method, referred to as FCA-ARM (fuzzy clustering analysis-association rule mining). The ...Show More
Application of associate rules mining on CGF's behavior modeling
2010 International Conference on Computer Application and System Modeling (ICCASM 2010)
Year: 2010 | Conference Paper |
In this paper, Computer Generated Forces (CGF) behavior modeling was studied from the viewpoint of associate data mining, for the large quantity of data, rules and models in its process. Because CGF behavior models data source was the combination of staticDB and dynamic data stream, the paper advanced the methods of item truncation and aim-pattern restriction. Through pretreatment, coding, searchi...Show More
The Application of Association Rules Algorithm in the Optimization of Information Processing in Intelligent Question-Answering System
2011 International Symposium on Computer Science and Society
Year: 2011 | Conference Paper |
This paper applied association rule mining method in the intelligent question-answering system, dug out the potential rules which user uses to sort the results in the process of browsing the results, and then generated the rule base and optimized the processing of information. Present the steps of mining association rules. Through pre-mining resources and analysis of mining association rules, focu...Show More
Discovering Informative Association Rules for Associative Classification
2008 IEEE International Symposium on Knowledge Acquisition and Modeling Workshop
Year: 2008 | Conference Paper |
The application of association rule mining to classification has led to a new family of classifiers which are often referred to as associative classifiers (ACs). An advantage of ACs is that they are rule-based and thus lend themselves to an easier interpretation. However, it is common knowledge that association rule mining typically yields a sheer number of rules defeating the purpose of a human r...Show More
Based on the Reinforcement Learning Association Rules Recommendation Study
2009 Fifth International Conference on Semantics, Knowledge and Grid
Year: 2009 | Conference Paper |
Reinforcement learning is an important method of machine learning. This paper using the graph theory to express varieties of knowledge points, which their's relationship is expressed by the graph of topological graph. Applied the Technology of association rule Recommendation to deal with the relationship between these knowledge points, give the corresponding of the recommendation work flow chart. ...Show More
Risk Analysis of the Association Rules in the Incremental Mining Based on the Weighted Model
2008 International Conference on Computer Science and Information Technology
Year: 2008 | Conference Paper |
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-makin...Show More
Strongest Association Rules Mining for Efficient Applications
2007 International Conference on Service Systems and Service Management
Year: 2007 | Conference Paper |
Cited by: Papers (7)
Rule explosion has become an important problem of association rules mining, as conventional mining algorithms often produce too many rules for decision makers to digest. In this paper, the notion of strongest association rules (SAR) is proposed for representing all association information with fewer rules, and a matrix-based algorithm is developed for mining SAR set. Our experiments show that the ...Show More
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