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Fast Frequent Free Tree Mining in Graph Databases

Peixiang Zhao, Jeffrey Yu
2006 Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06)  
In this paper, we present a computationally efficient algorithm F3TM (Fast Frequent Free Tree Mining) to find all frequently-occurred free trees in a graph database, D = {g 1 , g 2 , · · · , g N }.  ...  The experiment results show that our algorithm F3TM outperforms the up-to-date algorithms by an order of magnitude in mining frequent free trees in large graph databases.  ...  A new fast algorithm: F3TM In this section, we present our frequent ftree mining algorithm F3TM (Fast Frequent Free Tree Mining).  ... 
doi:10.1109/icdmw.2006.79 dblp:conf/icdm/ZhaoY06 fatcat:moihnc6ydzdjbdyobwzdajn7ci

Fast Frequent Free Tree Mining in Graph Databases

Peixiang Zhao, Jeffrey Xu Yu
2007 World wide web (Bussum)  
In this paper, we present a computationally efficient algorithm F3TM (Fast Frequent Free Tree Mining) to find all frequently-occurred free trees in a graph database, D = {g 1 , g 2 , · · · , g N }.  ...  The experiment results show that our algorithm F3TM outperforms the up-to-date algorithms by an order of magnitude in mining frequent free trees in large graph databases.  ...  A new fast algorithm: F3TM In this section, we present our frequent ftree mining algorithm F3TM (Fast Frequent Free Tree Mining).  ... 
doi:10.1007/s11280-007-0031-z fatcat:qqmmr3sdybcsznn6w6nw34s6te

Querying Large Graph Databases [chapter]

Yiping Ke, James Cheng, Jeffrey Xu Yu
2010 Lecture Notes in Computer Science  
to manipulate than graphsTrees retain more structural info than paths  Main idea:  Filtering by discriminative frequent subtrees  Fast sub-Iso testing by measuring distance between tree centers  ...  , Tree+∆, FG-index, QuickSI  Closure-based approach: C-tree, FG-index  Verification-free approach: FG-index, GDIndex  Coding-based approach: GString, GCoding  Fast sub-Iso approach: QuickSI, C-tree  ...  Candidate Generation  Candidate generation Derive a lower bound for the joint support in D q Generate candidates from D q by FG-mining with the above bound  Advantages Significant reduction in search  ... 
doi:10.1007/978-3-642-12098-5_57 fatcat:x4a5sd6aijfzxjyzp7lqgjw75y

FreeS: A Fast Algorithm to Discover Frequent Free Subtrees Using a Novel Canonical Form [chapter]

Israt J. Chowdhury, Richi Nayak
2015 Lecture Notes in Computer Science  
In this paper, a computationally fast algorithm FreeS is presented to discover all frequently occurring free subtrees in a database of labelled free trees.  ...  Web data can often be represented in free tree form; however, free tree mining methods seldom exist.  ...  [3] have proposed algorithms for mining frequent free trees from a graph database.  ... 
doi:10.1007/978-3-319-26190-4_9 fatcat:p4uir62blrgtrh43nzhvqm5xhu

Frequent free tree discovery in graph data

Ulrich Rückert, Stefan Kramer
2004 Proceedings of the 2004 ACM symposium on Applied computing - SAC '04  
In this paper, we are investigating the middle ground between these two extremes: mining free (that is, unrooted) trees in graph data.  ...  In recent years, researchers in graph mining have been exploring linear paths as well as subgraphs as pattern languages.  ...  In this paper, we are presenting FreeTreeMiner, a new algorithm for finding frequently occurring free trees in graph databases.  ... 
doi:10.1145/967900.968018 dblp:conf/sac/RuckertK04 fatcat:lgpf2myerbdybfmkaiiuwxgtce

SPIN

Jun Huan, Wei Wang, Jan Prins, Jiong Yang
2004 Proceedings of the 2004 ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '04  
Our method first mines all frequent trees from a general graph database and then reconstructs all maximal subgraphs from the mined trees.  ...  In large graph databases, the total number of frequent subgraphs can become too large to allow a full enumeration using reasonable computational resources.  ...  Jack Snoeyink in the University of North Carolina for helpful discussions about the paper.  ... 
doi:10.1145/1014052.1014123 dblp:conf/kdd/HuanWPY04 fatcat:ahjzbnbcafandoodi3f6kfxix4

iGraph

Wook-Shin Han, Jinsoo Lee, Minh-Duc Pham, Jeffrey Xu Yu
2010 Proceedings of the VLDB Endowment  
Given a query graph Q, the subgraph isomorphism problem is to find a set of graphs containing Q from a graph database, which is NP-complete.  ...  Recently, there have been a lot of research efforts to solve the subgraph isomorphism problem for a large graph database by utilizing graph indexes.  ...  The Tree+∆ and SwiftIndex perform their own tree mining algorithms to extract trees from graphs since the most frequent features are trees, and the cost of tree mining from graphs may be cheaper than that  ... 
doi:10.14778/1920841.1920901 fatcat:nwpo24ygonfj5n54gpuumkvlza

Towards Generic Pattern Mining [chapter]

Mohammed J. Zaki, Nagender Parimi, Nilanjana De, Feng Gao, Benjarath Phoophakdee, Joe Urban, Vineet Chaoji, Mohammad Al Hasan, Saeed Salem
2005 Lecture Notes in Computer Science  
Frequent Pattern Mining (FPM) is a very powerful paradigm for mining informative and useful patterns in massive, complex datasets.  ...  DMTL provides a systematic solution to a whole class of common FPM tasks like itemset, sequence, tree and graph mining.  ...  Such schemes exist for sequences and ordered trees as well, but more complex patterns like unordered trees, free trees, directed acyclic graphs (DAGs) and generic graphs shall require some form of isomorphism  ... 
doi:10.1007/978-3-540-32262-7_1 fatcat:mnkjx3xn65gpdmyhcbi3kligve

FAST ALGORITHM FOR MINING ASSOCIATION RULE

M. H. Margahny, A. Shakour
2006 JES. Journal of Engineering Sciences  
Can one develop a method that may avoid or reduce candidate generation and test and utilize some novel data structures to reduce the cost in frequent pattern mining ?  ...  One of the important problems in data mining is discovering association rules from databases of transactions where each transaction consists of a set of items.  ...  The frequent itemset mining problem is to find all frequent itemset in a given transaction database.  ... 
doi:10.21608/jesaun.2006.110079 fatcat:whq5ypli6fd67cj5iwbm5ke4yi

A survey of frequent subgraph mining algorithms

Chuntao Jiang, Frans Coenen, Michele Zito
2012 Knowledge engineering review (Print)  
Graph mining is an important research area within the domain of data mining. The field of study concentrates on the identification of frequent subgraphs within graph data sets.  ...  This paper presents a survey of current research in the field of frequent subgraph mining, and proposed solutions to address the main research issues.  ...  Free tree mining Free tree mining algorithms, as the name suggests, are directed at the discovery frequent subtrees in collections of free trees.  ... 
doi:10.1017/s0269888912000331 fatcat:pxye65ayvzgevplfpkjhwissn4

Frequent subgraph mining in outerplanar graphs

Tamás Horváth, Jan Ramon, Stefan Wrobel
2010 Data mining and knowledge discovery  
While the frequent connected subgraph mining problem for tree datasets can be solved in incremental polynomial time, it becomes intractable for arbitrary graph databases.  ...  In recent years there has been an increased interest in frequent pattern discovery in large databases of graph structured objects.  ...  can perform frequent pattern discovery in databases of structured objects such as trees or arbitrary graphs.  ... 
doi:10.1007/s10618-009-0162-1 fatcat:jui5vimh3vck5loqyiuc6wdlzy

Frequent subgraph mining in outerplanar graphs

Tamás Horváth, Jan Ramon, Stefan Wrobel
2006 Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '06  
While the frequent connected subgraph mining problem for tree datasets can be solved in incremental polynomial time, it becomes intractable for arbitrary graph databases.  ...  In recent years there has been an increased interest in frequent pattern discovery in large databases of graph structured objects.  ...  can perform frequent pattern discovery in databases of structured objects such as trees or arbitrary graphs.  ... 
doi:10.1145/1150402.1150427 dblp:conf/kdd/HorvathRW06 fatcat:yrtcrbafqbewbm4nhd247b5niq

Mining top−k frequent patterns without minimum support threshold

Abdus Salam, M. Sikandar Hayat Khayal
2011 Knowledge and Information Systems  
To effectively achieve this, the method employs construction of an all path source-to-destination tree to discover all maximal cycles in the graph.  ...  Finding frequent patterns play an important role in mining association rules, sequences, episodes, Web log mining and many other interesting relationships among data.  ...  Construction of association ratio graph Certainly frequent pattern mining is of greater value when applied to transaction databases that are large in size, and the entire database cannot completely fit  ... 
doi:10.1007/s10115-010-0363-3 fatcat:zmbc2ddatngapcppaf2igmcbdy

The Smallest Valid Extension-Based Efficient, Rare Graph Pattern Mining, Considering Length-Decreasing Support Constraints and Symmetry Characteristics of Graphs

Unil Yun, Gangin Lee, Chul-Hong Kim
2016 Symmetry  
Frequent graph mining has been proposed to find interesting patterns (i.e., frequent sub-graphs) from databases composed of graph transaction data, which can effectively express complex and large data  ...  In addition, various applications for graph mining have been suggested.  ...  Chul-Hong Kim investigated and reviewed references for graph theories and graph pattern mining applications to contribute to enhance the introduction and related work parts.  ... 
doi:10.3390/sym8050032 fatcat:w6cmt75hmrgcpnafi72ikzi2na

Graph Indexing: Tree + Delta >= Graph

Peixiang Zhao, Jeffrey Xu Yu, Philip S. Yu
2007 Very Large Data Bases Conference  
In this paper, we propose a new cost-effective graph indexing method based on frequent tree-features of the graph database.  ...  In order to achieve better pruning ability than existing graph-based indexing methods, we select, in addition to frequent tree-features (Tree), a small number of discriminative graphs (∆) on demand, without  ...  Ambuj Singh for providing C-Tree code, and Dr. Michihiro Kuramochi and Prof. George Karypis for providing the synthetic graph data generator.  ... 
dblp:conf/vldb/ZhaoYY07 fatcat:djh2s3gdk5dh7lqrkmbnhg4sq4
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