Mining Precise-Positioning Episode Rules from Event Sequences
暂无分享,去创建一个
Fuzhen Zhuang | Ping Luo | Jin Wang | Qing He | Xiang Ao | Fuzhen Zhuang | Ping Luo | Qing He | Xiang Ao | Jin Wang
[1] Gemma Casas-Garriga. Discovering Unbounded Episodes in Sequential Data , 2003 .
[2] Longbing Cao,et al. Mining Partially-Ordered Sequential Rules Common to Multiple Sequences , 2015, IEEE Trans. Knowl. Data Eng..
[3] Jiadong Ren,et al. Mining sequential patterns with periodic wildcard gaps , 2014, Applied Intelligence.
[4] P. S. Sastry,et al. Discovering Frequent Generalized Episodes When Events Persist for Different Durations , 2007, IEEE Transactions on Knowledge and Data Engineering.
[5] Christophe Rigotti,et al. Mining episode rules in STULONG dataset , 2004 .
[6] Avinash Achar,et al. Pattern-growth based frequent serial episode discovery , 2013, Data Knowl. Eng..
[7] Ada Wai-Chee Fu,et al. Mining Frequent Episodes for Relating Financial Events and Stock Trends , 2003, PAKDD.
[8] Chia-Hui Chang,et al. Efficient mining of frequent episodes from complex sequences , 2008, Inf. Syst..
[9] Boris Cule,et al. Mining Closed Strict Episodes , 2010, ICDM.
[10] Vincent S. Tseng,et al. Discovering utility-based episode rules in complex event sequences , 2015, Expert Syst. Appl..
[11] Christophe Rigotti,et al. Constraint-Based Mining of Episode Rules and Optimal Window Sizes , 2004, PKDD.
[12] Heikki Mannila,et al. Discovering Generalized Episodes Using Minimal Occurrences , 1996, KDD.
[13] Raajay Viswanathan,et al. Discovering injective episodes with general partial orders , 2011, Data Mining and Knowledge Discovery.
[14] Ryen W. White,et al. Stream prediction using a generative model based on frequent episodes in event sequences , 2008, KDD.
[15] Fuzhen Zhuang,et al. Online Frequent Episode Mining , 2015, 2015 IEEE 31st International Conference on Data Engineering.
[16] Boris Cule,et al. Mining closed episodes with simultaneous events , 2011, KDD.
[17] Fuzhen Zhuang,et al. Discovering and learning sensational episodes of news events , 2014, WWW.
[18] Heikki Mannila,et al. Discovery of Frequent Episodes in Event Sequences , 1997, Data Mining and Knowledge Discovery.
[19] Philip S. Yu,et al. Discovering Frequent Closed Partial Orders from Strings , 2006, IEEE Transactions on Knowledge and Data Engineering.
[20] Avinash Achar,et al. A unified view of Automata-based algorithms for Frequent Episode Discovery , 2010, ArXiv.
[21] Ramakrishnan Srikant,et al. Fast Algorithms for Mining Association Rules in Large Databases , 1994, VLDB.
[22] Philip S. Yu,et al. Mining high utility episodes in complex event sequences , 2013, KDD.
[23] Jian Pei,et al. Mining frequent patterns without candidate generation , 2000, SIGMOD '00.
[24] Kian-Lee Tan,et al. Finding constrained frequent episodes using minimal occurrences , 2004, Fourth IEEE International Conference on Data Mining (ICDM'04).
[25] Aris Floratos,et al. Combinatorial pattern discovery in biological sequences: The TEIRESIAS algorithm [published erratum appears in Bioinformatics 1998;14(2): 229] , 1998, Bioinform..
[26] Klaus Berberich,et al. Mind the gap: large-scale frequent sequence mining , 2013, SIGMOD '13.
[27] Chengqi Zhang,et al. Mining Dependent Frequent Serial Episodes from Uncertain Sequence Data , 2013, 2013 IEEE 13th International Conference on Data Mining.
[28] Ming Li,et al. Efficient Mining of Gap-Constrained Subsequences and Its Various Applications , 2012, TKDD.
[29] Avinash Achar,et al. A unified view of the apriori-based algorithms for frequent episode discovery , 2011, Knowledge and Information Systems.
[30] Shivakumar Sastry,et al. Discovering compressing serial episodes from event sequences , 2015, Knowledge and Information Systems.