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Xinjie Li - IEEE Xplore Author Profile

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Author details

Xinjie Li

Publications

2

Citations

49

Publications by Year

20202025

Co-Authors:

Guojia HouShi JinYong LiWanquan LiuLu Tan

Show All Co-Authors (7)

Xinjie Li

Affiliation

National Mobile Communications Research Laboratory

Southeast University

Nanjing, China

National Key Laboratory of Advanced Communication Networks

Shijiazhuang

Hebei, China

Publication Topics

Additive Noise,
Artificial Light,
Balancing Algorithm,
Blue Component,
Channel Correlation,
Channel Estimation,
Channel Estimation Error,
Channel Realizations,
Color Channels,
Color Correction,
Color Difference,
Color Distortion

Biography

Xinjie Li received the B.S. degree in software engineering from Qingdao University, in 2018, where he is currently pursuing the master’s degree. His research interests include image processing and computer vision.(Based on document published on 28 October 2020).

Publications

2

Citations

49

Publications by Year

20202025

Co-Authors:

Guojia Hou
Shi Jin
Yong Li
Wanquan Liu
Lu Tan

Show All Co-Authors (7)

Author's Published Works

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Showing 1-25 of 2,245 resultsfor "Index Terms":Strong Rules

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Department of Electrical Engineering, Princeton University, Princeton, NJ, USA(7)
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Research on strong-association rule based web application vulnerability detection

He Tian;Jing Xu;Kunmei Lian;Ying Zhang

2009 2nd IEEE International Conference on Computer Science and Information Technology

Year: 2009 | Conference Paper |

Cited by: Papers (7)

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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

Research on strong-association rule based web application vulnerability detection

He Tian;Jing Xu;Kunmei Lian;Ying Zhang

2009 2nd IEEE International Conference on Computer Science and Information Technology

Year: 2009 | Conference Paper |

Ontology-Based Association Rule Quality Evaluation Using Information Theory

Xia Shi Xiong;Li Fan;Zhang Lei

2010 International Conference on Computational and Information Sciences

Year: 2010 | Conference Paper |

Cited by: Papers (4)

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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

Ontology-Based Association Rule Quality Evaluation Using Information Theory

Xia Shi Xiong;Li Fan;Zhang Lei

2010 International Conference on Computational and Information Sciences

Year: 2010 | Conference Paper |

Fuzzy association rules mining algorithm based on output specification and redundancy of rules

Toshihiko Watanabe

2011 IEEE International Conference on Systems, Man, and Cybernetics

Year: 2011 | Conference Paper |

Cited by: Papers (3)

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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

Fuzzy association rules mining algorithm based on output specification and redundancy of rules

Toshihiko Watanabe

2011 IEEE International Conference on Systems, Man, and Cybernetics

Year: 2011 | Conference Paper |

Mining multilevel association rules with dynamic concept hierarchy

Yin-bo Wan;Yong Liang;Li-ya Ding

2008 International Conference on Machine Learning and Cybernetics

Year: 2008 | Conference Paper |

Cited by: Papers (3) | Patents (1)

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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

Mining multilevel association rules with dynamic concept hierarchy

Yin-bo Wan;Yong Liang;Li-ya Ding

2008 International Conference on Machine Learning and Cybernetics

Year: 2008 | Volume: 1 | Conference Paper |

A New Method for Eliminating Redundant Association Rules

Ye Xin;Wang Na;Wang Chunyu

2010 International Conference on Intelligent Computation Technology and Automation

Year: 2010 | Conference Paper |

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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

A New Method for Eliminating Redundant Association Rules

Ye Xin;Wang Na;Wang Chunyu

2010 International Conference on Intelligent Computation Technology and Automation

Year: 2010 | Volume: 1 | Conference Paper |

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 |

Cited by: Papers (2) | Patents (1)

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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

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 |

An encounter with Strong Association Rules

G. S. Bhamra;A.K. Verma;R. B. Patel

2010 IEEE 2nd International Advance Computing Conference (IACC)

Year: 2010 | Conference Paper |

Cited by: Papers (1)

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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

An encounter with Strong Association Rules

G. S. Bhamra;A.K. Verma;R. B. Patel

2010 IEEE 2nd International Advance Computing Conference (IACC)

Year: 2010 | Conference Paper |

New Criterion for Mining Strong Association Rules in Unbalanced Events

Tong-yan Li;Xing-ming Li

2008 International Conference on Intelligent Information Hiding and Multimedia Signal Processing

Year: 2008 | Conference Paper |

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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

New Criterion for Mining Strong Association Rules in Unbalanced Events

Tong-yan Li;Xing-ming Li

2008 International Conference on Intelligent Information Hiding and Multimedia Signal Processing

Year: 2008 | Conference Paper |

CSRule: Efficient mining of closed strong association rules in the resource effectiveness matrix

Lihua Zhang;Zhengjun Zhai;Miao Wang;Guoqing Wang

2013 6th International Conference on Biomedical Engineering and Informatics

Year: 2013 | Conference Paper |

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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

CSRule: Efficient mining of closed strong association rules in the resource effectiveness matrix

Lihua Zhang;Zhengjun Zhai;Miao Wang;Guoqing Wang

2013 6th International Conference on Biomedical Engineering and Informatics

Year: 2013 | Conference Paper |

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 |

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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

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 |

Mining Condensed and Lossless Association Rules by Pruning Redundancy

Lu Liu;Yin Chen;Siqing Shan;Lu Yin

2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery

Year: 2008 | Conference Paper |

Cited by: Papers (2)

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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 Condensed and Lossless Association Rules by Pruning Redundancy

Lu Liu;Yin Chen;Siqing Shan;Lu Yin

2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery

Year: 2008 | Volume: 2 | Conference Paper |

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)

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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 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 |

Mining positive and negative association rules

B. Ramasubbareddy;A. Govardhan;A. Ramamohanreddy

2010 5th International Conference on Computer Science & Education

Year: 2010 | Conference Paper |

Cited by: Papers (9)

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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

Mining positive and negative association rules

B. Ramasubbareddy;A. Govardhan;A. Ramamohanreddy

2010 5th International Conference on Computer Science & Education

Year: 2010 | Conference Paper |

Privacy Preserving Association Rules by Using Greedy Approach

Chieh-Ming Wu;Yin-Fu Huang;Jian-Ying Chen

2009 WRI World Congress on Computer Science and Information Engineering

Year: 2009 | Conference Paper |

Cited by: Papers (7)

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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

Privacy Preserving Association Rules by Using Greedy Approach

Chieh-Ming Wu;Yin-Fu Huang;Jian-Ying Chen

2009 WRI World Congress on Computer Science and Information Engineering

Year: 2009 | Volume: 4 | Conference Paper |

A New Approach of Self-adaptive Discretization to Enhance the Apriori Quantitative Association Rule Mining

Dancheng Li;Ming Zhang;Shuangshuang Zhou;Chen Zheng

2012 Second International Conference on Intelligent System Design and Engineering Application

Year: 2012 | Conference Paper |

Cited by: Papers (5)

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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

A New Approach of Self-adaptive Discretization to Enhance the Apriori Quantitative Association Rule Mining

Dancheng Li;Ming Zhang;Shuangshuang Zhou;Chen Zheng

2012 Second International Conference on Intelligent System Design and Engineering Application

Year: 2012 | Conference Paper |

Implementation of Dynamic Association Rule Mining Using Back Navigation Approach

Surbhi Huria;Jaiteg Singh

2015 Fifth International Conference on Communication Systems and Network Technologies

Year: 2015 | Conference Paper |

Cited by: Papers (1)

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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

Implementation of Dynamic Association Rule Mining Using Back Navigation Approach

Surbhi Huria;Jaiteg Singh

2015 Fifth International Conference on Communication Systems and Network Technologies

Year: 2015 | Conference Paper |

An Association Rules Algorithm Based on Biclustering

Min Zhang;Wenhang Ge;Yu Hou

2011 14th IEEE International Conference on Computational Science and Engineering

Year: 2011 | Conference Paper |

Cited by: Papers (1)

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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

An Association Rules Algorithm Based on Biclustering

Min Zhang;Wenhang Ge;Yu Hou

2011 14th IEEE International Conference on Computational Science and Engineering

Year: 2011 | Conference Paper |

DRAC: A Direct Rule Mining Approach for Associative Classification

Jinzheng Song;Zhixin Ma;Yusheng Xu

2010 International Conference on Artificial Intelligence and Computational Intelligence

Year: 2010 | Conference Paper |

Cited by: Papers (1)

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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

DRAC: A Direct Rule Mining Approach for Associative Classification

Jinzheng Song;Zhixin Ma;Yusheng Xu

2010 International Conference on Artificial Intelligence and Computational Intelligence

Year: 2010 | Volume: 2 | Conference Paper |

Feature selection based on fuzzy clustering analysis and association rule mining for soft-sensor

Ling Wang;Hui Guo

Proceedings of the 33rd Chinese Control Conference

Year: 2014 | Conference Paper |

Cited by: Papers (1)

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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

Feature selection based on fuzzy clustering analysis and association rule mining for soft-sensor

Ling Wang;Hui Guo

Proceedings of the 33rd Chinese Control Conference

Year: 2014 | Conference Paper |

Application of associate rules mining on CGF's behavior modeling

Gong Jianglei;Gong Guanghong;Song Xiao

2010 International Conference on Computer Application and System Modeling (ICCASM 2010)

Year: 2010 | Conference Paper |

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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

Application of associate rules mining on CGF's behavior modeling

Gong Jianglei;Gong Guanghong;Song Xiao

2010 International Conference on Computer Application and System Modeling (ICCASM 2010)

Year: 2010 | Volume: 5 | Conference Paper |

The Application of Association Rules Algorithm in the Optimization of Information Processing in Intelligent Question-Answering System

Liang Yunjuan;Kong Dechuan;Zhang Lijun;Yin Liqiang

2011 International Symposium on Computer Science and Society

Year: 2011 | Conference Paper |

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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

The Application of Association Rules Algorithm in the Optimization of Information Processing in Intelligent Question-Answering System

Liang Yunjuan;Kong Dechuan;Zhang Lijun;Yin Liqiang

2011 International Symposium on Computer Science and Society

Year: 2011 | Conference Paper |

Discovering Informative Association Rules for Associative Classification

Zhitong Su;Wei Song;Danyang Cao;Jinhong Li

2008 IEEE International Symposium on Knowledge Acquisition and Modeling Workshop

Year: 2008 | Conference Paper |

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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

Discovering Informative Association Rules for Associative Classification

Zhitong Su;Wei Song;Danyang Cao;Jinhong Li

2008 IEEE International Symposium on Knowledge Acquisition and Modeling Workshop

Year: 2008 | Conference Paper |

Based on the Reinforcement Learning Association Rules Recommendation Study

Jinqiao Wang;Qing Yang;Li Zhu;JunLi Sun

2009 Fifth International Conference on Semantics, Knowledge and Grid

Year: 2009 | Conference Paper |

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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

Based on the Reinforcement Learning Association Rules Recommendation Study

Jinqiao Wang;Qing Yang;Li Zhu;JunLi Sun

2009 Fifth International Conference on Semantics, Knowledge and Grid

Year: 2009 | Conference Paper |

Risk Analysis of the Association Rules in the Incremental Mining Based on the Weighted Model

Ying Mei;Liangsheng Zhu

2008 International Conference on Computer Science and Information Technology

Year: 2008 | Conference Paper |

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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

Risk Analysis of the Association Rules in the Incremental Mining Based on the Weighted Model

Ying Mei;Liangsheng Zhu

2008 International Conference on Computer Science and Information Technology

Year: 2008 | Conference Paper |

Strongest Association Rules Mining for Efficient Applications

Jie Li;Yong Xu;Yunfeng Wang;Chao-Hsien Chu

2007 International Conference on Service Systems and Service Management

Year: 2007 | Conference Paper |

Cited by: Papers (7)

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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

Strongest Association Rules Mining for Efficient Applications

Jie Li;Yong Xu;Yunfeng Wang;Chao-Hsien Chu

2007 International Conference on Service Systems and Service Management

Year: 2007 | Conference Paper |

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