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Finding Contextual Term from Index of Documents using Apriori Algorithm

Taruna Kumari, Annu Saini
2015 International Journal of Computer Applications  
Apriori employs an iterative approach known as levelwise search..  ...  The Apriori Algorithm for mining frequent itemsets for boolean association rules can be applied to the index file of a search engine to find contextually related terms i.e the terms which occur in number  ...  Step 2 Generating 2-termset frequent pattern After comparing support count of C3 termset with min_support we get L3 as shown above.  ... 
doi:10.5120/19200-0833 fatcat:jw5b75yd4zghjlgyjbgsgl4cvu

A new representation for protein secondary structure prediction based on frequent patterns

F. Birzele, S. Kramer
2006 Bioinformatics  
We discuss in detail how to identify frequent patterns in a protein sequence database using a level-wise search technique, how to define a set of features from those patterns and how to use those features  ...  Results: Three different sets of features based on frequent patterns are evaluated in a blind testing setup using 150 targets from the EVA contest and compared to predictions of PSI-PRED, PHD and PROFsec  ...  METHODS Finding Frequent Patterns using Levelwise Search Our approach to protein secondary structure prediction is based on frequent patterns of consecutive amino acids.  ... 
doi:10.1093/bioinformatics/btl453 pmid:16940325 fatcat:nvhajw7pife7nkl5snl3eoe2fa

Efficient Vertical Mining of Frequent Closures and Generators [chapter]

Laszlo Szathmary, Petko Valtchev, Amedeo Napoli, Robert Godin
2009 Lecture Notes in Computer Science  
The effective construction of many association rule bases requires the computation of both frequent closed and frequent generator itemsets (FCIs/FGs).  ...  However, only few miners address both concerns, typically by applying levelwise breadth-first traversal.  ...  Zart is an extension of Pascal [14] , i.e. first it finds all FIs using pattern-counting inference, then it filters FCIs, and finally the algorithm associates FGs to their closures.  ... 
doi:10.1007/978-3-642-03915-7_34 fatcat:nr5esej7tjb7noia6lel35ewaq

Probabilistic frequent subtrees for efficient graph classification and retrieval

Pascal Welke, Tamás Horváth, Stefan Wrobel
2017 Machine Learning  
and query graphs with small random samples of their spanning trees.  ...  Their practical use is, however, limited by the computational intractability of pattern enumeration and that of graph embedding into frequent subgraph feature spaces.  ...  Our implementation generates frequent trees with levelwise search. It uses the algorithm of Shamir and Tsur (1999) as the subroutine for the support counting step.  ... 
doi:10.1007/s10994-017-5688-7 fatcat:i6qa3j62cvhk5g5nu3mabqgjse

A condensed representation to find frequent patterns

Artur Bykowski, Christophe Rigotti
2001 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems - PODS '01  
We compared it with another representation of frequent patterns previously investigated in the literature called frequent closed sets.  ...  The idea presented in this paper is to extract a condensed representation of the frequent patterns called disjunction-free sets, instead of extracting the whole frequent pattern collection.  ...  all frequent patterns without costly scan of the original data and new support counting.  ... 
doi:10.1145/375551.375604 dblp:conf/pods/BykowskiR01 fatcat:qqcb5ukrtrej3aeqdvnvkzyxya

The iZi Project: Easy Prototyping of Interesting Pattern Mining Algorithms [chapter]

Frédéric Flouvat, Fabien De Marchi, Jean-Marc Petit
2010 Lecture Notes in Computer Science  
A common idea is to say that solutions devised so far for classical pattern mining problems, such as frequent itemset mining, should be useful to answer these tasks.  ...  From a theoretical point of view, this work takes advantage of the common theoretical background of pattern mining problems isomorphic to boolean lattices.  ...  The solution is to restrict the IND search space to INDs with a sorted left-hand side. Thanks to the "permutation inference rule", this restriction leads to no loss of knowledge [28].  ... 
doi:10.1007/978-3-642-14640-4_1 fatcat:tod2de5zjjgkxebzja5jdmoffe

A high-performance distributed algorithm for mining association rules

Assaf Schuster, Ran Wolff, Dan Trock
2005 Knowledge and Information Systems  
We present a new distributed association rule mining (D-ARM) algorithm that demonstrates superlinear speed-up with the number of computing nodes.  ...  Scale-up experiments over standard synthetic benchmarks demonstrate stable run time regardless of the number of computers.  ...  We thank Intel (Israel) and the Israeli ministry of defence (Mafaat) for their generous support of this research.  ... 
doi:10.1007/s10115-004-0176-3 fatcat:zdrh72xqnzfihmyxevyomex7s4

Frequent Subgraph Mining Algorithms – A Survey

T. Ramraj, R. Prabhakar
2015 Procedia Computer Science  
Graph Mining is one of the arms of Data mining in which voluminous complex data are represented in the form of graphs and mining is done to infer knowledge from them.  ...  Frequent sub graph mining is a sub section of graph mining domain which is extensively used for graph classification, building indices and graph clustering purposes.  ...  Comparative study between AGM and FSG In AGM, the candidate generation of the frequent induced sub graph is constructed by the levelwise search in terms of the size of the sub graph.  ... 
doi:10.1016/j.procs.2015.03.198 fatcat:t5whaholfrg4ffllgpzcwaqlji

Finding Frequent Subgraphs from Graph Structured Data with Geometric Information and Its Application to Lossless Compression [chapter]

Yuko Itokawa, Tomoyuki Uchida, Takayoshi Shoudai, Tetsuhiro Miyahara, Yasuaki Nakamura
2003 Lecture Notes in Computer Science  
As a knowledge representation, we define a layout term graph with structured variables. Secondly, we present an algorithm for finding frequent connected subgraphs in given data.  ...  Next, we design a method of lossless compression of graph structured data with geometric information by introducing the notion of a substitution in logic programming.  ...  Concluding Remarks In this paper, we considered the problems of (1) finding all frequent substructures from graph structured data with geometric information such as CAD, map data and drawing data, and  ... 
doi:10.1007/3-540-36175-8_58 fatcat:ytwqtmykuzdqhhy5cl3sh36squ

Inductive Databases and Multiple Uses of Frequent Itemsets: The cInQ Approach [chapter]

Jean-François Boulicaut
2004 Lecture Notes in Computer Science  
With an IDB the user/analyst performs a set of very different operations on data using a query language, powerful enough to perform all the required elaborations, such as data preprocessing, pattern discovery  ...  We introduce the concepts of pattern domain, evaluation functions, primitive constraints, inductive queries and solvers for itemsets.  ...  Mining Discriminant Patterns. An interesting application of frequency constraints concerns the search for patterns that are frequent in one data set and infrequent in another one.  ... 
doi:10.1007/978-3-540-44497-8_1 fatcat:eidindj7urhx5ij477velnmpze

Using transposition for pattern discovery from microarray data

François Rioult, Jean-François Boulicaut, Bruno Crémilleux, Jérémy Besson
2003 Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery - DMKD '03  
The frequent itemset (sets of columns) extraction technique enables to process difficult cases (millions of lines, hundreds of columns) provided that data is not too dense.  ...  We analyze expression matrices to identify a priori interesting sets of genes, e.g., genes that are frequently co-regulated.  ...  Acknowledgements This work has been partially funded by the EU contract cInQ IST-2000-26469 (FET arm of the IST programme). F.  ... 
doi:10.1145/882098.882099 fatcat:y4dbopwdbjfdnkzkap5ua5obfu

Using transposition for pattern discovery from microarray data

François Rioult, Jean-François Boulicaut, Bruno Crémilleux, Jérémy Besson
2003 Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery - DMKD '03  
The frequent itemset (sets of columns) extraction technique enables to process difficult cases (millions of lines, hundreds of columns) provided that data is not too dense.  ...  We analyze expression matrices to identify a priori interesting sets of genes, e.g., genes that are frequently co-regulated.  ...  Acknowledgements This work has been partially funded by the EU contract cInQ IST-2000-26469 (FET arm of the IST programme). F.  ... 
doi:10.1145/882082.882099 dblp:conf/dmkd/RioultBCB03 fatcat:kzpfrtddgzghdmmni576hxi6uy

Approximate mining of frequent patterns on streams

Claudio Silvestri, Salvatore Orlando, João Gama, Jesus Aguilar-Ruiz
2007 Intelligent Data Analysis  
Both upper and lower bounds on the support of each pattern found are returned along with the interpolated support.  ...  This paper introduces a new algorithm for approximate mining of frequent patterns from streams of transactions using a limited amount of memory.  ...  AP Stream exploits a novel interpolation method to infer the unknown past counts of some patterns, which are frequents only on recent data.  ... 
doi:10.3233/ida-2007-11104 fatcat:d4g3uvnfmnczlkd537ax4bdt2i

Ranking Sentences for Keyphrase Extraction: A Relational Data Mining Approach

Michelangelo Ceci, Corrado Loglisci, Lucrezia Macchia
2014 Procedia Computer Science  
or factor of significance is provided.  ...  Document summarization involves reducing a text document into a short set of phrases or sentences that convey the main meaning of the text.  ...  Acknowledgements This work fulfils the research objectives of the PON020056-33489339 project "PUGLIA@SERVICE -Internetbased Service Engineering enabling Smart Territory structural development" and the  ... 
doi:10.1016/j.procs.2014.10.011 fatcat:n4y6scv6evgfdjulchpkw55yia

Fast mining of spatial collocations

Xin Zhang, Nikos Mamoulis, David W. Cheung, Yutao Shou
2004 Proceedings of the 2004 ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '04  
Our technique is an extension of a spatial join algorithm that operates on multiple inputs and counts long pattern instances.  ...  An example of such a pattern can associate contaminated water reservoirs with certain deceases in their spatial neighborhood.  ...  Acknowledgments The authors would like to thank Zhong Zhi for his help with the implementation of the mining algorithm.  ... 
doi:10.1145/1014052.1014095 dblp:conf/kdd/ZhangMCS04 fatcat:xp2i5thppzfh5dcsso2hm2sa3y
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