DryadeParent, An Efficient and Robust Closed Attribute Tree Mining Algorithm
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Alexandre Termier | Michèle Sebag | Takashi Washio | Hiroshi Motoda | Kouzou Ohara | Marie-Christine Rousset | M. Sebag | T. Washio | H. Motoda | K. Ohara | A. Termier | M. Rousset
[1] Nicolas Pasquier,et al. Discovering Frequent Closed Itemsets for Association Rules , 1999, ICDT.
[2] Sean R Eddy,et al. What is dynamic programming? , 2004, Nature Biotechnology.
[3] Rakesh Agarwal,et al. Fast Algorithms for Mining Association Rules , 1994, VLDB 1994.
[4] Luc De Raedt,et al. Advances in Mining Graphs, Trees and Sequences , 2005, Fundam. Informaticae.
[5] Mohammed J. Zaki. Efficiently mining frequent trees in a forest , 2002, KDD.
[6] Mario Gerla,et al. Aggregated Multicast – A Comparative Study , 2002, Cluster Computing.
[7] Mohammed J. Zaki. Efficiently Mining Frequent Embedded Unordered Trees , 2004, Fundam. Informaticae.
[8] Sen Zhang,et al. Unordered tree mining with applications to phylogeny , 2004, Proceedings. 20th International Conference on Data Engineering.
[9] C. M. Sperberg-McQueen,et al. Extensible markup language , 1997 .
[10] Mohammed J. Zaki,et al. Efficient algorithms for mining closed itemsets and their lattice structure , 2005, IEEE Transactions on Knowledge and Data Engineering.
[11] Thomas H. Cormen,et al. Introduction to algorithms [2nd ed.] , 2001 .
[12] Yun Chi,et al. CMTreeMiner: Mining Both Closed and Maximal Frequent Subtrees , 2004, PAKDD.
[13] Joost N. Kok,et al. Efficient discovery of frequent unordered trees , 2003 .
[14] Mong-Li Lee,et al. Mining frequent query patterns from XML queries , 2003, Eighth International Conference on Database Systems for Advanced Applications, 2003. (DASFAA 2003). Proceedings..
[15] Hiroki Arimura,et al. An Output-Polynomial Time Algorithm for Mining Frequent Closed Attribute Trees , 2005, ILP.
[16] Alexandre Termier,et al. Dryade: a new approach for discovering closed frequent trees in heterogeneous tree databases , 2004, Fourth IEEE International Conference on Data Mining (ICDM'04).
[17] Mohammed J. Zaki. Efficiently mining frequent trees in a forest: algorithms and applications , 2005, IEEE Transactions on Knowledge and Data Engineering.
[18] E. Mark Gold,et al. Language Identification in the Limit , 1967, Inf. Control..
[19] C. M. Sperberg-McQueen,et al. Extensible Markup Language (XML) , 1997, World Wide Web J..
[20] Hiroki Arimura,et al. Efficient Substructure Discovery from Large Semi-Structured Data , 2001, IEICE Trans. Inf. Syst..
[21] Hiroki Arimura,et al. Discovering Frequent Substructures in Large Unordered Trees , 2003, Discovery Science.
[22] Charu C. Aggarwal,et al. XRules: an effective structural classifier for XML data , 2003, KDD '03.
[23] Ramakrishnan Srikant,et al. Mining sequential patterns , 1995, Proceedings of the Eleventh International Conference on Data Engineering.
[24] Pekka Kilpeläinen,et al. Tree Matching Problems with Applications to Structured Text Databases , 2022 .
[25] George Karypis,et al. An efficient algorithm for discovering frequent subgraphs , 2004, IEEE Transactions on Knowledge and Data Engineering.
[26] Kevin C. Almeroth,et al. Modeling the branching characteristics and efficiency gains in global multicast trees , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).
[27] Charu C. Aggarwal,et al. XRules: An effective algorithm for structural classification of XML data , 2006, Machine Learning.
[28] Hiroki Arimura,et al. LCM ver. 2: Efficient Mining Algorithms for Frequent/Closed/Maximal Itemsets , 2004, FIMI.
[29] Mohammed J. Zaki,et al. CHARM: An Efficient Algorithm for Closed Itemset Mining , 2002, SDM.
[30] R. Bellman. Dynamic programming. , 1957, Science.
[31] Yannis Papakonstantinou,et al. DTD inference for views of XML data , 2000, PODS.
[32] Heikki Mannila,et al. Levelwise Search and Borders of Theories in Knowledge Discovery , 1997, Data Mining and Knowledge Discovery.
[33] Heikki Mannila,et al. Discovery of Frequent Episodes in Event Sequences , 1997, Data Mining and Knowledge Discovery.
[34] Takashi Washio,et al. Complete Mining of Frequent Patterns from Graphs: Mining Graph Data , 2003, Machine Learning.
[35] Zhigang Li,et al. Efficient data mining for maximal frequent subtrees , 2003, Third IEEE International Conference on Data Mining.