Ida Ngambeki - IEEE Xplore Author Profile

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Author details

Ida Ngambeki

Also published under: Ida B. Ngambeki

Publications

9

Citations

25

Publications by Year

20062021

Co-Authors:

Grusha AhluwaliaIsslam AlhasanSubia AnsariGlaris Lancia Raja ArulMarlo Basil-Camino

Show All Co-Authors (31)

Ida Ngambeki

Also published under: Ida B. Ngambeki

Affiliation

Department of Computer and Information Technology

Purdue University

West Lafayette, USA

Publication Topics

Computer Science,
Concept Mapping,
Conceptual Understanding,
Delphi Method,
Information Security,
Abstract Concepts,
Active Learning,
Algebraic Calculations,
Area Of Research,
Attack Strategy,
Attack Vector,
Authentic Learning

Biography

Ida Ngambeki, Graduate Student, School of Engineering Education, Purdue University, ingambek@purdue.edu.(Based on document published on 2 February 2012).

Publications

9

Citations

25

Publications by Year

20062021

Co-Authors:

Grusha Ahluwalia
Isslam Alhasan
Subia Ansari
Glaris Lancia Raja Arul
Marlo Basil-Camino

Show All Co-Authors (31)

Author's Published Works

Search History

Showing 1-25 of 13,807 resultsfor "Index Terms":Association rules

Conferences (12,285)

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Department of Computer Science and Information Engineering, National University of Kaohsiung, Kaohsiung, Taiwan(61)
Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan(43)
School of Computer Engineering, Nanyang Technological University, Singapore(32)
Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan(29)
Graduate School of Information, Production and Systems, Waseda University, Fukuoka, Japan(26)
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IEEE Transactions on Knowledge and Data Engineering(229)
2002 IEEE International Conference on Data Mining, 2002. Proceedings.(39)
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Association Rule Mining(6,751)
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The application of improved Fp-growth algorithm in online test system

Chen Wen;Nu Lan

2011 International Conference on Electrical and Control Engineering

Year: 2011 | Conference Paper |

Based on Fp-growth algorithm framework, association rules mining with probability has been proposed under the situations of uneven distribution items in random draw-out test. Moreover, the association rule evaluation method applied in experimental results are presented to demonstrate its accuracy and effectiveness.Show More

The application of improved Fp-growth algorithm in online test system

Chen Wen;Nu Lan

2011 International Conference on Electrical and Control Engineering

Year: 2011 | Conference Paper |

Probability-Based Incremental Association Rule Discovery Algorithm

Ratchadaporn Amornchewin;Worapoj Kreesuradej

International Symposium on Computer Science and its Applications

Year: 2008 | Conference Paper |

Cited by: Papers (3)

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In dynamic databases, new transactions are appended as time advances. This may introduce new association rules and some existing association rules would become invalid. Thus, the maintenance of association rules for dynamic databases is an important problem. In this paper, probability-based incremental association rule discovery algorithm is proposed to deal with this problem. The proposed algorit...Show More

Probability-Based Incremental Association Rule Discovery Algorithm

Ratchadaporn Amornchewin;Worapoj Kreesuradej

International Symposium on Computer Science and its Applications

Year: 2008 | Conference Paper |

Improved extraction of quantitative rules using Best M Positive Negative Association Rules Algorithm

Sheetal Naredi;Rushali A. Deshmukh

2015 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)

Year: 2015 | Conference Paper |

Cited by: Papers (3)

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Mining association rules is a fundamental data mining task. Association rule greatly help to identify trends and pattern from huge data set. Algorithms for mining association rules put more stress on positive rules rather than negative rules. Negative rules specify the attribute present in the data set to the attribute absent. In this paper we propose an algorithm BMPNAR, Best M Positive Negative ...Show More

Improved extraction of quantitative rules using Best M Positive Negative Association Rules Algorithm

Sheetal Naredi;Rushali A. Deshmukh

2015 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)

Year: 2015 | Conference Paper |

An Efficient Algorithm for Association Mining

2009 Second International Symposium on Knowledge Acquisition and Modeling

Year: 2009 | Conference Paper |

Cited by: Papers (1)

Association rule discovery plays an important role in knowledge discovery and data mining, and efficiency is especially crucial for an algorithm to find frequent patterns from a large database. In this paper, a new algorithm called LogApriori algorithm is proposed by the idea of reducing unnecessary scanning of database in Apriori algorithm. The correctness of LogApriori algorithm is proved in thi...Show More

An Efficient Algorithm for Association Mining

2009 Second International Symposium on Knowledge Acquisition and Modeling

Year: 2009 | Volume: 1 | Conference Paper |

k-Frequent itemsets generation algorithm based on bit matrix

2011 International Conference on Electrical and Control Engineering

Year: 2011 | Conference Paper |

The generation of frequent itemsets is the key of association rules mining. Based on bit vectors and its intersection operation of the DLG ideas, this paper presents a new k-frequent itemsets generation algorithm based on bit matrix. The algorithm scans the database only once, using bit matrix of alternative association graph to store, constructing screening conditions to reduce the validation of ...Show More

k-Frequent itemsets generation algorithm based on bit matrix

2011 International Conference on Electrical and Control Engineering

Year: 2011 | Conference Paper |

A Lazy Approach to Associative Classification

Elena Baralis;Silvia Chiusano;Paolo Garza

IEEE Transactions on Knowledge and Data Engineering

Year: 2008 | Volume: 20, Issue: 2 | Journal Article |

Cited by: Papers (72)

Associative classification is a promising technique to build accurate classifiers. However, in large or correlated datasets, association rule mining may yield huge rule sets. Hence, several pruning techniques have been proposed to select a small subset of high quality rules. We argue that rule pruning should be reduced to a minimum, since the availability of a "rich" rule set may improve the accur...Show More

A Lazy Approach to Associative Classification

Elena Baralis;Silvia Chiusano;Paolo Garza

IEEE Transactions on Knowledge and Data Engineering

Year: 2008 | Volume: 20, Issue: 2 | Journal Article |

An improved design approach in spatial databases using frequent Association Rule Mining algorithm

Animesh Tripathy;Subhalaxmi Das;Prashanta Kumar Patra

2010 IEEE 2nd International Advance Computing Conference (IACC)

Year: 2010 | Conference Paper |

Cited by: Papers (3)

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Recently Negative Association Rule Mining (NARM) has become a focus in the field of spatial data mining. Negative association rules are useful in data analysis to identify objects that conflict with each other or that complement each other. Much effort has been devoted for developing algorithms for efficiently discovering relation between objects in space. All the traditional association rule mini...Show More

An improved design approach in spatial databases using frequent Association Rule Mining algorithm

Animesh Tripathy;Subhalaxmi Das;Prashanta Kumar Patra

2010 IEEE 2nd International Advance Computing Conference (IACC)

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 |

Application of Fuzzy Association Rules in Intrusion Detection

Kai Xing Wu;Juan Hao;Chunhua Wang

2011 International Conference on Internet Computing and Information Services

Year: 2011 | Conference Paper |

Cited by: Papers (2)

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Intrusion detection system (IDS) is based on data mining technology in this paper. Association rule mining which is a method of data mining will make the boundaries of intervals hard. It will increase the information loss. In this paper, a novel framework based on data mining techniques is proposed for designing IDS. In this framework, the classification engine, which is actually the core of the I...Show More

Application of Fuzzy Association Rules in Intrusion Detection

Kai Xing Wu;Juan Hao;Chunhua Wang

2011 International Conference on Internet Computing and Information Services

Year: 2011 | Conference Paper |

Research on Mining Sequential Positive and Negative Association Rules

He Jiang;Runian Geng;Baoyou Sun

2009 Second International Conference on Intelligent Computation Technology and Automation

Year: 2009 | Conference Paper |

Cited by: Papers (1)

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Mining sequential positive and negative association rules is to mine the inner association or the causal relationship among data in sequential database, which will find some rules that have practical significance for the industry decision-making analysis among the sequence. This paper proposes the relational notions of sequential positive and negative association rule. Based on the new questions w...Show More

Research on Mining Sequential Positive and Negative Association Rules

He Jiang;Runian Geng;Baoyou Sun

2009 Second International Conference on Intelligent Computation Technology and Automation

Year: 2009 | Volume: 3 | Conference Paper |

Mining Direct and Indirect Weighted Fuzzy Association Rules in Large Transaction Databases

Weimin Ouyang;Qinhua Huang

2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery

Year: 2009 | Conference Paper |

Cited by: Papers (4)

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Association rule is an important research topic in data mining and knowledge discovery. Traditional algorithms for mining association rules are built on the binary attributes databases, which has three limitations. Firstly, it can not concern quantitative attributes; secondly, it treats each item with the same significance although different item may have different significance; thirdly, only the ...Show More

Mining Direct and Indirect Weighted Fuzzy Association Rules in Large Transaction Databases

Weimin Ouyang;Qinhua Huang

2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery

Year: 2009 | Volume: 3 | Conference Paper |

Study on a Data Warehouse Mining Oriented Fuzzy Association Rule Mining Algorithm

2014 Fifth International Conference on Intelligent Systems Design and Engineering Applications

Year: 2014 | Conference Paper |

Cited by: Papers (3)

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This paper concentrate the problem of fuzzy association rule mining for data warehouse mining. The aims of our algorithm are to obtain the frequent fuzzy grids, and then mining useful fuzzy association rules. Next, some definitions are provided to describe the theoretical basis of this paper. Afterwards, the framework of the proposed association rule mining algorithm consists of four parts: (1) Mi...Show More

Study on a Data Warehouse Mining Oriented Fuzzy Association Rule Mining Algorithm

2014 Fifth International Conference on Intelligent Systems Design and Engineering Applications

Year: 2014 | Conference Paper |

Application of Negative Association Rules in Multi-database

Xiangjun Dong;Shiju Shang;Jie Li;He Jiang

2008 International Symposium on Information Science and Engineering

Year: 2008 | Conference Paper |

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The increasing use of multi-database technology has led to the development of many multi-database systems for real-world application. Large companies may have to confront the multiple data-source problem,so multi-database mining has been an important research area. Negative association rules (NARs) play important roles in decision-making. But nowadays the techniques of NARs mining focus on mono-da...Show More

Application of Negative Association Rules in Multi-database

Xiangjun Dong;Shiju Shang;Jie Li;He Jiang

2008 International Symposium on Information Science and Engineering

Year: 2008 | Volume: 1 | Conference Paper |

Fuzzy association rules mining algorithm based on equivalence redundancy of items

Toshihiko Watanabe;Ryosuke Fujioka

2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

Year: 2012 | Conference Paper |

Cited by: Papers (13)

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In data mining approaches, quantitative attributes should be appropriately dealt with as well as Boolean attributes. This paper presents an essential improvement for extracting fuzzy association rules from a database. The objective of this paper is to improve the computational time of mining and to prune extracted redundant rules simultaneously for an actual data mining application. In this paper,...Show More

Fuzzy association rules mining algorithm based on equivalence redundancy of items

Toshihiko Watanabe;Ryosuke Fujioka

2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

Year: 2012 | Conference Paper |

A Method of Mining the Meta-association Rules for Dynamic Association Rule Based on the Model of AR-Markov

Feng Jingjing;Zeng Qingfei;Zhang Zhonglin

2010 Second International Conference on Networks Security, Wireless Communications and Trusted Computing

Year: 2010 | Conference Paper |

Cited by: Papers (2)

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Based on the dynamic association rules, this paper puts forward the formal definition of meta-rules which makes use of the support vector and confidence vector as evaluation of rules, and introduces the usual mining process of the Meta-association Rules for dynamic association rule by the model of AR-Markov, the examples show that this method is effective in the analysing and predicting the change...Show More

A Method of Mining the Meta-association Rules for Dynamic Association Rule Based on the Model of AR-Markov

Feng Jingjing;Zeng Qingfei;Zhang Zhonglin

2010 Second International Conference on Networks Security, Wireless Communications and Trusted Computing

Year: 2010 | Volume: 2 | Conference Paper |

Discovery of multivariate phenotypes using association rule mining and their application to genome-wide association studies

Sung Hee Park;Sangsoo Kim

2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)

Year: 2010 | Conference Paper |

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Genome-wide association studies (GWAS) have served crucial roles in investigating disease susceptible loci for single traits. On the other hand, the GWAS have been limited in measuring genetic risk factors for multivariate phenotypes from pleiotropic genetic effects of genetic loci. This work reports a data mining approach to discover patterns of multivariate phenotypes expressed as association ru...Show More

Discovery of multivariate phenotypes using association rule mining and their application to genome-wide association studies

Sung Hee Park;Sangsoo Kim

2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)

Year: 2010 | Conference Paper |

Research of Mining Positive and Negative Weighted Association Rules Based on Chi-Squared Analysis

Yuan-yuan Zhao;He Jiang

2009 Second International Conference on Information and Computing Science

Year: 2009 | Conference Paper |

Cited by: Papers (2)

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Recently, mining negative association rules has received some attention and proved to be useful. Several algorithms have been proposed. However, there are some questions with those algorithms, for example, misleading rules will occur when the positive and negative rules are mined simultaneously. The chi-squared test can avoid the problem in the paper because of the mature theory basis. It is based...Show More

Research of Mining Positive and Negative Weighted Association Rules Based on Chi-Squared Analysis

Yuan-yuan Zhao;He Jiang

2009 Second International Conference on Information and Computing Science

Year: 2009 | Volume: 1 | Conference Paper |

Emergency Resource Planning by Using Spatial Data Association Rule Mining and Linear Programming Method

Bo Fan;Jinhong Li

2011 Fourth International Joint Conference on Computational Sciences and Optimization

Year: 2011 | Conference Paper |

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Spatial attributes are important factors that affect the whole process of emergency events. However, studies on this subject have not sufficiently been carried out. This paper presents a new idea that incorporates spatial predicates describing the spatial relationships between emergency locations and surrounding objects into emergency event analysis. Furthemore, a multi-level spatial data associat...Show More

Emergency Resource Planning by Using Spatial Data Association Rule Mining and Linear Programming Method

Bo Fan;Jinhong Li

2011 Fourth International Joint Conference on Computational Sciences and Optimization

Year: 2011 | Conference Paper |

The research and application of a spatial transverse mining algorithm

Gang Fang;Zu-Kuan Wei;Jiang Xiong;Cheng-Sheng Tu

The 2nd International Conference on Information Science and Engineering

Year: 2010 | Conference Paper |

this paper proposes an algorithm of spatial association rules mining based on orientation frequent, which is suitable for mining transverse spatial association. The algorithm uses the method of orientation frequent item set to generate frequent candidate items by down-up strategy, which is able to efficiently reduce repeating computing and redundant operation to improve the efficiency of algorithm...Show More

The research and application of a spatial transverse mining algorithm

Gang Fang;Zu-Kuan Wei;Jiang Xiong;Cheng-Sheng Tu

The 2nd International Conference on Information Science and Engineering

Year: 2010 | Conference Paper |

Association rule mining algorithm based on privacy preserving

Sun Wei;Wang Yonggui

2010 The 2nd International Conference on Computer and Automation Engineering (ICCAE)

Year: 2010 | Conference Paper |

Cited by: Papers (2)

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The goal of privacy preserving association rule is to find an approach of the original data set, making the relevant sensitive rules not to be found in a process of data mining. In order to efficiently achieve privacy preserving, this paper proposes an effective method for privacy preserving association rule. Trough the way of combining the basic strategies of PPARM algorithm and IMBA which are im...Show More

Association rule mining algorithm based on privacy preserving

Sun Wei;Wang Yonggui

2010 The 2nd International Conference on Computer and Automation Engineering (ICCAE)

Year: 2010 | Volume: 4 | Conference Paper |

A High Coherent Association Rule Mining Algorithm

Chun-Hao Chen;Guo-Cheng Lan;Tzung-Pei Hong;Yui-Kai Lin

2012 Conference on Technologies and Applications of Artificial Intelligence

Year: 2012 | Conference Paper |

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The goal of data mining is to help market managers find relationships among items from large data sets to increase sales volume. The Apriori algorithm is a method for association rule mining, a data mining technique. Although a lot of mining approaches have been proposed based on the Apriori algorithm, most focus on positive association rules, such as "If milk is bought, then bread is bought". How...Show More

A High Coherent Association Rule Mining Algorithm

Chun-Hao Chen;Guo-Cheng Lan;Tzung-Pei Hong;Yui-Kai Lin

2012 Conference on Technologies and Applications of Artificial Intelligence

Year: 2012 | Conference Paper |

Fuzzy association rule mining and classifier with chi-squared correlation measure using genetic network programming

Karla Taboada;Shingo Mabu;Eloy Gonzales;Kaoru Shimada;Kotaro Hirasawa

2009 ICCAS-SICE

Year: 2009 | Conference Paper |

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One of the most important issues in any association rule mining is the interpretation and evaluation of discovered rules. Thus, most algorithms employ the support-confidence framework for evaluating association and classification rules. Unfortunately, recent studies show that the support and confidence measures are insufficient for filtering out uninteresting association rules, for instance, even ...Show More

Fuzzy association rule mining and classifier with chi-squared correlation measure using genetic network programming

Karla Taboada;Shingo Mabu;Eloy Gonzales;Kaoru Shimada;Kotaro Hirasawa

2009 ICCAS-SICE

Year: 2009 | Conference Paper |

Maintenance of multi-level association rules discovery in dynamic database under a change of support threshold

Nophadon Pumjun;Worapoj Kreesuradej

2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

Year: 2015 | Conference Paper |

Cited by: Papers (1)

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An association rule mining is often performed with a dynamic database and hierarchical items. The big problem of data mining process is a maintenance association rules while the database always changing. The purpose of this study is to extend the MLUp algorithm which can maintain a multilevel association rules discovery at the same minimum support threshold. In general, several mining tasks are re...Show More

Maintenance of multi-level association rules discovery in dynamic database under a change of support threshold

Nophadon Pumjun;Worapoj Kreesuradej

2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

Year: 2015 | Conference Paper |

Exploring the Effects of Text Clustering on On-Line Military News Based on Quantitative Association Rule

Liang-chu Chen;Chyi-Bao Yang;Jih-Hsin Chen;Yen-Hsuan Lien

2009 International Conference on Asian Language Processing

Year: 2009 | Conference Paper |

Cited by: Papers (2)

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Text clustering is an automatic technique to group texts using the approach of feature extraction and term connection to calculate the similarities among subject contents of texts. Since the properties of terms in Chinese text (e.g. segmentation and annotation) are not as clear as the other languages, extracting and distinguishing features from Chinese text is therefore much more difficult, which ...Show More

Exploring the Effects of Text Clustering on On-Line Military News Based on Quantitative Association Rule

Liang-chu Chen;Chyi-Bao Yang;Jih-Hsin Chen;Yen-Hsuan Lien

2009 International Conference on Asian Language Processing

Year: 2009 | Conference Paper |

The intrusion detection system based on fuzzy association rules mining

2010 2nd International Conference on Computer Engineering and Technology

Year: 2010 | Conference Paper |

Cited by: Papers (2)

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In this paper, we integrate fuzzy association rules to design and implement an abnormal network intrusion detection system. Since the association rules used in traditional information detection cannot effectively deal with changes in network behavior, it will better meet the actual needs of abnormal detection to introduce the concept of fuzzy association rules to strengthen the adaptability. This ...Show More

The intrusion detection system based on fuzzy association rules mining

2010 2nd International Conference on Computer Engineering and Technology

Year: 2010 | Volume: 7 | Conference Paper |

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