Mining Graph Patterns
暂无分享,去创建一个
Jiawei Han | Hong Cheng | Xifeng Yan | Jiawei Han | Hong Cheng | Xifeng Yan
[1] Jia Wang,et al. Redundancy-aware maximal cliques , 2013, KDD.
[2] Charalampos E. Tsourakakis,et al. Denser than the densest subgraph: extracting optimal quasi-cliques with quality guarantees , 2013, KDD.
[3] Ashraf Aboulnaga,et al. Scalable maximum clique computation using MapReduce , 2013, 2013 IEEE 29th International Conference on Data Engineering (ICDE).
[4] Divesh Srivastava,et al. Dense subgraph maintenance under streaming edge weight updates for real-time story identification , 2012, The VLDB Journal.
[5] James Cheng,et al. Fast algorithms for maximal clique enumeration with limited memory , 2012, KDD.
[6] Jia Wang,et al. Truss Decomposition in Massive Networks , 2012, Proc. VLDB Endow..
[7] Srinivasan Parthasarathy,et al. Extracting Analyzing and Visualizing Triangle K-Core Motifs within Networks , 2012, 2012 IEEE 28th International Conference on Data Engineering.
[8] Sergei Vassilvitskii,et al. Densest Subgraph in Streaming and MapReduce , 2012, Proc. VLDB Endow..
[9] Geoff Holmes,et al. Mining frequent closed graphs on evolving data streams , 2011, KDD.
[10] Charu C. Aggarwal,et al. Discovering highly reliable subgraphs in uncertain graphs , 2011, KDD.
[11] James Cheng,et al. Efficient core decomposition in massive networks , 2011, 2011 IEEE 27th International Conference on Data Engineering.
[12] Anthony K. H. Tung,et al. On Triangulation-based Dense Neighborhood Graphs Discovery , 2010, Proc. VLDB Endow..
[13] Philip S. Yu,et al. On dense pattern mining in graph streams , 2010, Proc. VLDB Endow..
[14] Jianzhong Li,et al. Discovering frequent subgraphs over uncertain graph databases under probabilistic semantics , 2010, KDD.
[15] Jeffrey Xu Yu,et al. Finding maximal cliques in massive networks by H*-graph , 2010, SIGMOD Conference.
[16] Ambuj K. Singh,et al. GraphSig: A Scalable Approach to Mining Significant Subgraphs in Large Graph Databases , 2009, 2009 IEEE 25th International Conference on Data Engineering.
[17] Nicole Krämer,et al. Partial least squares regression for graph mining , 2008, KDD.
[18] Philip S. Yu,et al. Mining significant graph patterns by leap search , 2008, SIGMOD Conference.
[19] Siegfried Nijssen,et al. What Is Frequent in a Single Graph? , 2007, PAKDD.
[20] Mohammad Al Hasan,et al. ORIGAMI: Mining Representative Orthogonal Graph Patterns , 2007, Seventh IEEE International Conference on Data Mining (ICDM 2007).
[21] Ambuj K. Singh,et al. Efficient Algorithms for Mining Significant Substructures in Graphs with Quality Guarantees , 2007, Seventh IEEE International Conference on Data Mining (ICDM 2007).
[22] Koji Tsuda,et al. Entire regularization paths for graph data , 2007, ICML '07.
[23] Jiawei Han,et al. Discriminative Frequent Pattern Analysis for Effective Classification , 2007, 2007 IEEE 23rd International Conference on Data Engineering.
[24] George Karypis,et al. A Multi-Level Parallel Implementation of a Program for Finding Frequent Patterns in a Large Sparse Graph , 2007, 2007 IEEE International Parallel and Distributed Processing Symposium.
[25] Christian Borgelt,et al. Support Computation for Mining Frequent Subgraphs in a Single Graph , 2007, MLG.
[26] Kamalakar Karlapalem,et al. MARGIN: Maximal Frequent Subgraph Mining , 2006, Sixth International Conference on Data Mining (ICDM'06).
[27] Jiawei Han,et al. Discovery of Frequent Substructures , 2006 .
[28] Ravi Kumar,et al. Discovering Large Dense Subgraphs in Massive Graphs , 2005, VLDB.
[29] Srinivasan Parthasarathy,et al. Discovering frequent topological structures from graph datasets , 2005, KDD '05.
[30] Jiawei Han,et al. Mining closed relational graphs with connectivity constraints , 2005, 21st International Conference on Data Engineering (ICDE'05).
[31] Yun Chi,et al. Mining closed and maximal frequent subtrees from databases of labeled rooted trees , 2005, IEEE Transactions on Knowledge and Data Engineering.
[32] George Karypis,et al. Frequent substructure-based approaches for classifying chemical compounds , 2003, IEEE Transactions on Knowledge and Data Engineering.
[33] Yuji Matsumoto,et al. An Application of Boosting to Graph Classification , 2004, NIPS.
[34] Jiong Yang,et al. SPIN: mining maximal frequent subgraphs from graph databases , 2004, KDD.
[35] Joost N. Kok,et al. A quickstart in frequent structure mining can make a difference , 2004, KDD.
[36] Chen Wang,et al. Scalable mining of large disk-based graph databases , 2004, KDD.
[37] Philip S. Yu,et al. Graph indexing: a frequent structure-based approach , 2004, SIGMOD '04.
[38] Hiroki Arimura,et al. Efficient Substructure Discovery from Large Semi-Structured Data , 2001, IEICE Trans. Inf. Syst..
[39] Wojciech Szpankowski,et al. An efficient algorithm for detecting frequent subgraphs in biological networks , 2004, ISMB/ECCB.
[40] Wei Wang,et al. Efficient mining of frequent subgraphs in the presence of isomorphism , 2003, Third IEEE International Conference on Data Mining.
[41] Jiawei Han,et al. CloseGraph: mining closed frequent graph patterns , 2003, KDD '03.
[42] Takashi Washio,et al. State of the art of graph-based data mining , 2003, SKDD.
[43] J. Snoeyink,et al. Mining Spatial Motifs from Protein Structure Graphs , 2003 .
[44] Christian Borgelt,et al. Mining molecular fragments: finding relevant substructures of molecules , 2002, 2002 IEEE International Conference on Data Mining, 2002. Proceedings..
[45] Jiawei Han,et al. gSpan: graph-based substructure pattern mining , 2002, 2002 IEEE International Conference on Data Mining, 2002. Proceedings..
[46] Ehud Gudes,et al. Computing frequent graph patterns from semistructured data , 2002, 2002 IEEE International Conference on Data Mining, 2002. Proceedings..
[47] Mohammed J. Zaki. Efficiently mining frequent trees in a forest , 2002, KDD.
[48] George Karypis,et al. Frequent subgraph discovery , 2001, Proceedings 2001 IEEE International Conference on Data Mining.
[49] Qiming Chen,et al. PrefixSpan,: mining sequential patterns efficiently by prefix-projected pattern growth , 2001, Proceedings 17th International Conference on Data Engineering.
[50] Takashi Washio,et al. An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data , 2000, PKDD.
[51] Hannu Toivonen,et al. Finding Frequent Substructures in Chemical Compounds , 1998, KDD.
[52] Yoav Freund,et al. A decision-theoretic generalization of on-line learning and an application to boosting , 1997, EuroCOLT.
[53] Lawrence B. Holder,et al. Substucture Discovery in the SUBDUE System , 1994, KDD Workshop.