Mannila H,Toivonen H,Verkamo A I.Discovering frequent episodesin sequences extended abstract[A].1st Conference on Knowledge Discovery and Data Mining[C].Montreal:CA.1995.210-215.
[2]
Koh Y S,Pears R.Efficient negative association rule mining based on chance thresholds[J].Intelligent Data Analysis,2014,18(2):243-260.
[3]
Lam H T,Calders T,Yang J,et al.Zips:mining compressing sequential patterns in streams[A].Proceedings of the ACM SIGKDD Workshop on Interactive Data Exploration and Analytics[C].New York:ACM,2013.54-62.
[4]
Van Der Aalst W.Process mining:Overview and opportunities[J].ACM Transactions on Management Information Systems,2012,3(2):1-17.
[5]
Laxman S,Tankasali V,White R W.Stream prediction using a generative model based on frequent episodes in event sequences[A].Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining[C].Las Vegas,NV:ACM,2008.453-461.
[6]
Cho C W,Zheng Y,Chen A L P.Continuously Matching Episode Rules for Predicting Future Events over Event Streams[M].Advances in Data and Web Management.2007.884-891.
[7]
Cho C W,Wu Y H,Yen S J,et al.On-line rule matching for event prediction[J].The VLDB Journal,2011,20(3):303-334.
[8]
Hatonen K,Klemettinen M,Mannila H,et al.Knowledge discovery from telecommunication network alarm databases[A].Proceedings of the Twelfth IEEE International Conference[C].Trois-Rivières:IEEE,1996.115-122.
[9]
Méger N,Rigotti C.Constraint-based mining of episode rules and optimal window sizes[A].Knowledge Discovery in Databases:PKDD 2004[C].Berlin Heidelberg:PKDD,2004.313-324.
[10]
Lo D,Khoo S C,Li J.Mining and ranking generators of sequential patterns[A].SIAM International Conference on Data Mining[C].Atlanta Georgia:SIAM,2008.553-564.
[11]
朱辉生,汪卫,施伯乐.基于频繁闭情节及其生成子的无冗余情节规则抽取[J].计算机学报,2012,35(1):53-64. Zhu Huisheng,Wang wei,Shi Bole.Extracting non-redundant episode rules based onfrequent closed episodes and their generators[J].Journal of Computers,2012,35(1):53-64.(in Chinese)
[12]
Fournier-Viger P,Tseng V S.Tns:mining top-k non-redundantsequential rules[A].Proceedings of the 28th Annual ACM Symposium on Applied Computing[C].Coimbra,Portugal:ACM,2013.164-166.
[13]
Zhang S,Wu X.Fundamentals of association rules in data mining and knowledge discovery[J].Wiley Interdisciplinary Reviews:Data Mining and Knowledge Discovery,2011,1(2):97-116.
[14]
Rudin C,Letham B,Madigan D.Learning theory analysis for association rules and sequential event prediction[J].The Journal of Machine Learning Research,2013,14(1):3441-3492.
[15]
Toon Calders,Bart Goethals.Non-derivable itemset mining[J].Data Mining and Knowledge Discovery,2007,14(1):171-206.
[16]
Ao F,Du J,Yan Y,et al.An efficient algorithm for mining closed frequent itemsets in data Streams[A].Computer and Information Technology Workshops of IEEE 8th International Conference 2008[C].Aizu-Wakamatsu:IEEE,2008.37-42.
[17]
Agrawal R,Srikant R.Fast algorithms for mining association rules[A].Proceedings of 20th International Conference on Very Large Data Bases[C].Santiago de Chile:ACM,1994.487-499.