- Author:
- Guozhu Dong
Understanding sequence data, and the ability to utilize this hidden knowledge, creates a significant impact on many aspects of our society. Examples of sequence data include DNA, protein, customer purchase history, web surfing history, and more. Sequence Data Mining provides balanced coverage of the existing results on sequence data mining, as well as pattern types and associated pattern mining methods. While there are several books on data mining and sequence data analysis, currently there are no books that balance both of these topics. This professional volume fills in the gap, allowing readers to access state-of-the-art results in one place. Sequence Data Mining is designed for professionals working in bioinformatics, genomics, web services, and financial data analysis. This book is also suitable for advanced-level students in computer science and bioengineering. Forward by ProfessorJiawei Han,University of Illinois at Urbana-Champaign.
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- Wang L, Zhao X, Si Y, Cao L and Liu Y (2017). Context-Associative Hierarchical Memory Model for Human Activity Recognition and Prediction, IEEE Transactions on Multimedia, 19:3, (646-659), Online publication date: 1-Mar-2017.
Hemmati H, Arcuri A and Briand L (2013). Achieving scalable model-based testing through test case diversity, ACM Transactions on Software Engineering and Methodology (TOSEM), 22:1, (1-42), Online publication date: 1-Feb-2013.- Nin J, Carrera D and Villatoro D On the Use of Social Trajectory-Based Clustering Methods for Public Transport Optimization Second International Workshop on Citizen in Sensor Networks - Volume 8313, (59-70)
- Zou Y, Harumi K, Ohtsuki K and Kang M Development of Material Automatic Generation System Based on the Analysis of Phonemic Errors in English Vocabulary Listening Proceedings of the 12th International Conference on Advances in Web-Based Learning --- ICWL 2013 - Volume 8167, (340-349)
- Panigrahi L, Ranjan R, Das K and Mishra D Removal and interpolation of missing values using wavelet neural network for heterogeneous data sets Proceedings of the International Conference on Advances in Computing, Communications and Informatics, (1004-1009)
- Fang X, Hu P, Chau M, Hu H, Yang Z and Sheng O (2012). A Data-Driven Approach to Measure Web Site Navigability, Journal of Management Information Systems, 29:2, (173-212), Online publication date: 1-Oct-2012.
- Béchet N, Cellier P, Charnois T and Crémilleux B Discovering linguistic patterns using sequence mining Proceedings of the 13th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I, (154-165)
- Quiniou S, Cellier P, Charnois T and Legallois D What about sequential data mining techniques to identify linguistic patterns for stylistics? Proceedings of the 13th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I, (166-177)
- Leue S and Tabaei Befrouei M Counterexample explanation by anomaly detection Proceedings of the 19th international conference on Model Checking Software, (24-42)
- Fabregue M, Bringay S, Poncelet P, Teisseire M and Orsetti B (2011). Mining microarray data to predict the histological grade of a breast cancer, Journal of Biomedical Informatics, 44:S1, (S12-S16), Online publication date: 1-Dec-2011.
- Raïssi C and Pei J Towards bounding sequential patterns Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, (1379-1387)
- Fallahnezhad M, Moradi M and Zaferanlouei S (2011). A Hybrid Higher Order Neural Classifier for handling classification problems, Expert Systems with Applications: An International Journal, 38:1, (386-393), Online publication date: 1-Jan-2011.
- Chen N, Hoi S and Xiao X Software process evaluation Proceedings of the 26th IEEE/ACM International Conference on Automated Software Engineering, (333-342)
- Zaki M, Carothers C and Szymanski B (2010). VOGUE, ACM Transactions on Knowledge Discovery from Data, 4:1, (1-31), Online publication date: 1-Jan-2010.
- Fradkin D and Moerchen F Margin-closed frequent sequential pattern mining Proceedings of the ACM SIGKDD Workshop on Useful Patterns, (45-54)
- Xing Z, Pei J and Keogh E (2010). A brief survey on sequence classification, ACM SIGKDD Explorations Newsletter, 12:1, (40-48), Online publication date: 9-Nov-2010.
- García R, Llana L, Malagón C and Pancorbo J Event prediction in network monitoring systems Proceedings of the 10th industrial conference on Advances in data mining: applications and theoretical aspects, (632-642)
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