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Interrelation analysis of celestial spectra data using constrained frequent pattern trees

Jifu Zhang, Xujun Zhao, Sulan Zhang, Shu Yin, Xiao Qin
2013 Knowledge-Based Systems  
Next, we propose a concept of constrained frequent pattern trees (CFP) along with an algorithm used to construct CFPs, aiming to improve the efficiency and pertinence of association rule mining.  ...  Association rule mining, in which generating frequent patterns is a key step, is an effective way of identifying inherent and unknown interrelationships between characteristics of celestial spectra data  ...  trees efficiently using the first-order predicate logic to represent background knowledge.  ... 
doi:10.1016/j.knosys.2012.12.013 fatcat:uetlaxjtibbmbadjpws6d2tzra

SAS: Implementation of scaled association rules on spatial multidimensional quantitative dataset

M. N., Sapna Jain, M Afshar
2012 International Journal of Advanced Computer Science and Applications  
The present paper proposed a new algorithm by extracting maximum frequent itemsets based on spatial multidimensional quantitative dataset.  ...  Algorithms for mining spatial association rules are similar to association rule mining except consideration of special data, the predicates generation and rule generation processes are based on Apriori  ...  CONCLUSION In this paper we proposed a practical to find frequent patterns using X Tree. X-tree compresses both dense and sparse datasets by using numerical value representation.  ... 
doi:10.14569/ijacsa.2012.030919 fatcat:hgog3euaofcupnrsfhtnvmkl44

A Novel Algorithm for Mining Hybrid-Dimensional Association Rules

R. Chithra, S. Nickolas
2010 International Journal of Computer Applications  
In this paper, a novel algorithm is proposed for mining hybrid-dimensional association rules which are very useful in business decision making.  ...  Compared to traditional algorithms, this algorithm efficiently finds association rules in multidimensional datasets, by scanning the database only once, thus enhancing the process of data mining.  ...  M ultidimensional association rule mining uses two basic approaches to deal with quantitative attributes.  ... 
doi:10.5120/342-521 fatcat:xgtmwifpsnfydbiu6bldfvmkla

Specifying mining algorithms with iterative user-defined aggregates

F. Giannotti, G. Manco, F. Turini
2004 IEEE Transactions on Knowledge and Data Engineering  
We present a way of exploiting domain knowledge in the design and implementation of data mining algorithms, with special attention to frequent patterns discovery, within a deductive framework.  ...  predicates.  ...  ACKNOWLEDGMENTS The authors would like to thank Carlo Zaniolo for useful comments and discussions and Hiaxun Wang for his support with the LDL þþ system.  ... 
doi:10.1109/tkde.2004.64 fatcat:5kdulezhtfgbhi35hqj3tb3gj4

Comparative study of different data mining prediction algorithms

2016 International Journal of Latest Trends in Engineering and Technology  
The main algorithms which were involved in this study include classification using decision tree, clustering algorithm, Apriori algorithm and association rules.  ...  The main objective of this research paper is to prove the efficiency of high dimensional data analysis and different algorithms in the prediction process of Data mining.  ...  Models used in Predictive Data Mining The models mainly used in predictive data mining includes Regression, Time series, neural networks, statistical mining tools, pattern matching, association rules,  ... 
doi:10.21172/1.72.562 fatcat:v5uqwagsofax5fnvfgjpivz7pq

Extraction of Contextual Relevance of the Web Document using F-P Growth

Nidhi Tyagi, Rahul Rishi, R. P. Agarwal
2013 International Journal of Computer Applications  
This can be achieved through data mining technique for generating frequent patterns, using FP-Growth.  ...  The contextual relevance of the web documents can be known, if the frequent occurring patterns of the keywords in the web page are identified.  ...  The FP-tree is mined by creating the conditional pattern bases and frequent pattern are generated as {K2, K1, K5} and {K2, K1, K3}.  ... 
doi:10.5120/10047-4632 fatcat:mxn6js6strfbpkob4au7glrzbu

Data Mining Techniques and Applications [chapter]

2009 Design and Implementation of Data Mining Tools  
Data mining is a process which finds useful patterns from large amount of data.  ...  The paper discusses few of the data mining techniques, algorithms and some of the organizations which have adapted data mining technology to improve their businesses and found excellent results.  ...  Data mining is a process of extraction of useful information and patterns from huge data.  ... 
doi:10.1201/9781420045918-p1 fatcat:uevabkr5trbbnnnldgmlmigse4

Data Mining Techniques and Applications [chapter]

2009 Design and Implementation of Data Mining Tools  
Data mining is a process which finds useful patterns from large amount of data.  ...  The paper discusses few of the data mining techniques, algorithms and some of the organizations which have adapted data mining technology to improve their businesses and found excellent results.  ...  Data mining is a process of extraction of useful information and patterns from huge data.  ... 
doi:10.1201/9781420045918-c2 fatcat:qeaw3ukcwbhlxojths3fhaxqnm

Survey on Frequent Pattern Discovery and its Approaches using: Data Mining

W. Sarada, P. V.
2018 International Journal of Computer Applications  
Apriori algorithm has been imperative algorithm in association rule mining. Main proposal of this algorithm is to find useful patterns between different set of data.  ...  This study is focused on how to solve the efficient problems of Apriori algorithm and raise another association rules mining algorithm.  ...  It hopes to dig out more useful information.  ... 
doi:10.5120/ijca2018917050 fatcat:cnnr3hibvjfe7ifvmndeo4hwtu

Sequential Pattern Mining for Situation and Behavior Prediction in Simulated Robotic Soccer [chapter]

Andreas D. Lattner, Andrea Miene, Ubbo Visser, Otthein Herzog
2006 Lecture Notes in Computer Science  
These patterns can be later applied during runtime in order to predict future situations and behaviors. The pattern mining approach was applied to two games of the 2D RoboCup simulation league.  ...  In this work we present an approach which applies unsupervised symbolic learning off-line to a qualitative abstraction in order to create frequent patterns in dynamic scenes.  ...  At each level of the pattern mining just the frequent patterns of the previous step are taken into account knowing that only combinations of frequent patterns can result in frequent patterns again which  ... 
doi:10.1007/11780519_11 fatcat:2sosommn6bcc7ninlz7lit2iqi


Sheng Zhang, Ji Zhang, Han Liu, Wei Wang
2005 Special interest tracks and posters of the 14th international conference on World Wide Web - WWW '05  
and memory constraint of the system, for efficient data selection and AR mining.  ...  In this paper, we propose a framework, called XAR-Miner, for mining ARs from XML documents efficiently.  ...  Association Rule (AR) mining is frequently used to reveal interesting trends, patterns, and rules in large datasets.  ... 
doi:10.1145/1062745.1062785 dblp:conf/www/ZhangZLW05 fatcat:fl3qx7el5bfdrc5x6vfxsmxfqi

Finding Efficient Positive and Negative Itemsets Using Interestingness Measures

P. Asha, T. Prem Jacob, A. Pravin
2018 International Journal of Engineering & Technology  
Mining these data and bringing out useful patterns seems difficult. Various data mining algorithms were put forth for this purpose.  ...  The associated patterns generated by the association rule mining algorithms are large in number.  ...  Reduced I/O Overhead With Single Scan To Db, Time Efficient, Appends The New Items Directly Into A Tree. Difficult To Add New Data Or To Delete Old Data Into The Tree While Mining Frequent Patterns.  ... 
doi:10.14419/ijet.v7i4.36.24133 fatcat:q2lelzatxfdwxhvbykkg6ug62u

Mining Rare Patterns by Using Automated Threshold Support

Prof. Mangesh Ghonge, Miss Neha Rane
2018 International Journal of Engineering & Technology  
Considering the thought of weight for each and every apparent items brings effectiveness for mining the pattern efficiently.  ...  Essentially the most primary and crucial part of data mining is pattern mining.  ...  Hence they have proposed rare sequential pattern over data stream using sliding window and also have proved it efficient For mining rare pattern ,one of the concept called nave approach is also used.  ... 
doi:10.14419/ijet.v7i3.8.15225 fatcat:svkt345yvbgj7dh5bvxeaeiqwu

Relational Frequent Patterns Mining for Novelty Detection from Data Streams [chapter]

Michelangelo Ceci, Annalisa Appice, Corrado Loglisci, Costantina Caruso, Fabio Fumarola, Carmine Valente, Donato Malerba
2009 Lecture Notes in Computer Science  
Frequent relational patterns are efficiently extracted at each time point, and a time window is used to filter out novelty patterns.  ...  An application of the proposed algorithm to the problem of detecting anomalies in network traffic is described and quantitative and qualitative results obtained by analyzing real stream of data collected  ...  The huge amount of data generated by these applications demands for the development of specific data mining techniques which can effectively and efficiently discover the hidden, useful knowledge embedded  ... 
doi:10.1007/978-3-642-03070-3_32 fatcat:vxhhe2maczdevhkxvnhy44t62m

Unsupervised pattern mining from symbolic temporal data

Fabian Mörchen
2007 SIGKDD Explorations  
For both pattern languages efficient mining algorithms have been proposed.  ...  For univariate data and limited gaps suffix tree methods are more efficient. Recently, efficient algorithms have been proposed to mine the more general concept of partial order from time points.  ...  The pattern format is equivalent to [52] but uses only a subset of Allen's relations. A tree-based enumeration algorithm [13] is used for efficient mining.  ... 
doi:10.1145/1294301.1294302 fatcat:rwcvkifhknh2reo6zp2tkco4vq
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