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A Survey of Fuzzy Based Association Rule Mining to Find CoOccurrence Relationships

Anubha Sharma, Asst. Prof. Nirupama Tiwari
2014 IOSR Journal of Computer Engineering  
This paper provides the major advancement in the approaches for association rule mining using fuzzy algorithms.  ...  The overall goal of the data mining process is to extract knowledge from an existing data set and transform it into a human-understandable structure.In data mining, association rule learning is a popular  ...  in batch from the compact sub-tree and later release the current subtree from memory leaving the space for next subtree thus significantly outperforms the other algorithms on both execution times, memory  ... 
doi:10.9790/0661-16158387 fatcat:c2gzdb24y5crzkbh43kpsdilfy

Compact transaction database for efficient frequent pattern mining

Qian Wan, Aijun An
2005 2005 IEEE International Conference on Granular Computing  
In this paper, we propose an innovative approach to generating compact transaction databases for efficient frequent pattern mining.  ...  This allows the CT-Apriori algorithm, which is revised from the classical Apriori algorithm, to generate frequent patterns quickly by skipping the initial database scan and reducing a great amount of I  ...  The algorithm for generating a CT-tree from a transaction database and for generating a compact transaction database from a CT-tree is described as follows.  ... 
doi:10.1109/grc.2005.1547372 dblp:conf/grc/WanA05 fatcat:bui3faqv5jf7vc73qobp7zm5nu

Survey: Efficent tree based structure for mining frequent pattern from transactional databases

Hitul Patel Hitul Patel
2013 IOSR Journal of Computer Engineering  
Different types of data structure and algorithm have been proposed to extract frequent pattern from a given databases.  ...  One of the fastest and efficient frequent pattern mining algorithm is CATS algorithm which represent the data and allow mining with a single scan of database.  ...  I will also thank my class mates in laboratory for their concern and support both in study and life.  ... 
doi:10.9790/0661-0957581 fatcat:cz43s6w4ujdflkbnak7odlii2y

Compact Weighted Class Association Rule Mining Using Information Gain

Syed Ibrahim, Chandran
2011 International Journal of Data Mining & Knowledge Management Process  
This paper proposes compact weighted class association rule mining method, which applies weighted association rule mining in the classification and constructs an efficient weighted associative classifier  ...  This proposed associative classification algorithm chooses one non class informative attribute from dataset and all the weighted class association rules are generated based on that attribute.  ...  Kleinberg [11] used HITS algorithm in bipartite graph and weights are derived from the internal structure of the database.  ... 
doi:10.5121/ijdkp.2011.1601 fatcat:khfgjg55vbbt7k436nhl7hl5iy

Efficient Mining Algorithm For Reducing Number Of Itemsets Using Chud

Hari. D, Suganya. R
2016 International Journal Of Engineering And Computer Science  
Data Mining plays an essential role for mining useful pattern hidden in large databases. Apriori algorithm is used to find frequent itemsets in large databases.  ...  To mine the Closed High Utility Itemsets the system addresses an efficient Depth-First search algorithm named CHUD.  ...  as other algorithms are derived from this algorithm.  ... 
doi:10.18535/ijecs/v5i4.44 fatcat:624yzvapdfdhvdxk75hd3t6xn4

NCFP-tree: A Non-Recursive Approach to CFP-tree using Single Conditional Database

R. Prabamanieswari
2017 International Journal for Research in Applied Science and Engineering Technology  
Efficient algorithms for mining frequent itemsets are crucial for mining association rules as well as for many other data mining tasks.  ...  Many algorithms and techniques based on tree [9] are posed for enumerating itemsets from transactional databases.  ...  CT-PRO [15] is also a variation of classic FP-tree algorithm [9] . It is based upon the compact tree structure [16] for efficiently mining frequent patterns.  ... 
doi:10.22214/ijraset.2017.11058 fatcat:atkqknshejdppelt4jzpcnyfha

Induction of compact decision trees for personalized recommendation

Daniel Nikovski, Veselin Kulev
2006 Proceedings of the 2006 ACM symposium on Applied computing - SAC '06  
algorithms for the purposes of simplification and compaction of the recommendation policies.  ...  We propose a method for induction of compact optimal recommendation policies based on discovery of frequent itemsets in a purchase database, followed by the application of standard decision tree learning  ...  Table 1 : 1 Example database T Table 3 : 3 Recommendation policy derived from T .  ... 
doi:10.1145/1141277.1141410 dblp:conf/sac/NikovskiK06 fatcat:zonbdamazzg6tba3y3scaqgsve

Efficiently Identifying Exploratory Rules' Significance [chapter]

Shiying Huang, Geoffrey I. Webb
2006 Lecture Notes in Computer Science  
The situation gets worse as the size of the database increases. In this paper, we propose two approaches for improving the efficiency of significant exploratory rule discovery.  ...  We also evaluate the experimental effect in impact rule discovery which is suitable for discovering exploratory rules in very large, dense databases.  ...  However, the values used for comparison are derived from samples instead of from the total population.  ... 
doi:10.1007/11677437_6 fatcat:xw2iewi3cvfo7m7ugqgjl4vwae

An Efficient Algorithm for Distributed Incremental Updating of Frequent Item-Sets on Massive Database [chapter]

Jiangtao Qiu, Changjie Tang, Lei Duan, Chuan Li, Shaojie Qiao, Peng Chen, Qihong Liu
2006 Lecture Notes in Computer Science  
for frequent item-sets incremental updating; (d) in order to further improve performance, proposes the algorithm DFIIU for distributed incremental updating of frequent Item-sets on massive database; (  ...  The main contributions include: (a) introduces the concept of Interesting Support Threshold; (b) proposes Frequent Item-sets Tree (FITr) with compact structure; (c) proposes and implements algorithm FIIU  ...  Let DB be database and R be a set of criteria for mining association rules.  ... 
doi:10.1007/11906070_6 fatcat:xcsqq3wub5gwpmsb5a4vpaib4u

Selective provenance for datalog programs using top-k queries

Daniel Deutch, Amir Gilad, Yuval Moskovitch
2015 Proceedings of the VLDB Endowment  
To this end, we propose a novel top-k query language for querying datalog provenance, supporting selection criteria based on tree patterns and ranking based on the rules and database facts used in derivation  ...  We propose an efficient novel algorithm based on (1) instrumenting the datalog program so that, upon evaluation, it generates only relevant provenance, and (2) efficient top-k (relevant) provenance generation  ...  CONCLUSION We have presented in this paper selPQL, a top-k query language for datalog provenance, and an efficient algorithm for tracking selective provenance guided by a selPQL query.  ... 
doi:10.14778/2824032.2824039 fatcat:r4h75gcxavexpk7k74owb5kohu

Self-adaptive semantic schema mechanism for multimedia databases

Jun Yang, Qing Li, Yueting Zhuang, LiWei Zhou, Chung-Sheng Li, Yoshiji Suzuki
2002 Electronic Imaging and Multimedia Technology III  
As an endeavor to strike the balance between these two goals, this paper presents a self-adaptive semantic schema mechanism (SSM) for multimedia databases.  ...  As its most distinguishable feature, when the conditions of certain ECA-rules are satisfied, SSM supports adaptive evolution of a schema in the form of expansion with new classes and/or compaction by removing  ...  Therefore, it is removed by the schema compaction algorithm with its objects migrated to class Animal. 3 In the case study, the initials E, C, and A stand for Event, Condition, and Action of an ECA-rule  ... 
doi:10.1117/12.481571 fatcat:k2wglbf4gze5foshld5gobpdyu

Direct Discriminative Pattern Mining for Effective Classification

Hong Cheng, Xifeng Yan, Jiawei Han, Philip S. Yu
2008 2008 IEEE 24th International Conference on Data Engineering  
In this paper, we propose a direct discriminative pattern mining approach, DDPMine, to tackle the efficiency issue arising from the two-step approach.  ...  It often adopts a two-step approach: frequent pattern (or classification rule) mining followed by feature selection (or rule ranking).  ...  Jianyong Wang at Tsinghua Univ. for giving us the HARMONY software.  ... 
doi:10.1109/icde.2008.4497425 dblp:conf/icde/ChengYHY08 fatcat:mbxun7vpuvgzhfedeb4xkweom4

EGEA : A New Hybrid Approach Towards Extracting Reduced Generic Association Rule Set (Application to AML Blood Cancer Therapy) [chapter]

M. A. Esseghir, G. Gasmi, S. Ben Yahia, Y. Slimani
2006 Lecture Notes in Computer Science  
Once, the relevant attributes (genes) have been selected, they serve as an input for a second approach stage, i.e., extracting generic association rules from this reduced set of genes.  ...  To avoid obtaining an unmanageable highly sized association rule sets-compounded with their low precision-that often make the perusal of knowledge ineffective, the extraction and exploitation of compact  ...  In this respect, extracting generic basis of association rules seems to be an efficient approach for providing extra-added value knowledge for biologists.  ... 
doi:10.1007/11823728_47 fatcat:rrkyrh6lqbeejk5qxwxtjzfdim

Association Rule Hiding Techniques for Privacy Preserving Data Mining: A Study

Gayathiri P, Dr. B
2015 International Journal of Advanced Computer Science and Applications  
Association rule mining is an efficient data mining technique that recognizes the frequent items and associative rule based on a market basket data analysis for large set of transactional databases.  ...  Identifying associative rules of a transactional database in data mining may expose the confidentiality and privacy of an organization and individual.  ...  Efficient mechanisms are needed to increase the speed of the rule hiding process for large databases.  ... 
doi:10.14569/ijacsa.2015.061232 fatcat:n4y6tjn6rzhzfmo566mefzggtu

New Approach to Optimize the Time of Association Rules Extraction [article]

Thabet Slimani
2013 arXiv   pre-print
To address this limitation, the objective of this work is to adapt a new method for optimizing the time of association rules extractions from large databases.  ...  The knowledge discovery algorithms have become ineffective at the abundance of data and the need for fast algorithms or optimizing methods is required.  ...  By running Apr+, Rs+, and BF-ARM algorithms, we got identical rules. Conclusion In this paper, we propose a new method to derive association rules from large databases using Ptree structure.  ... 
arXiv:1312.4800v1 fatcat:5bvmagodtjd6bccmcuwknsdczu
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