Author:
Song M.,Yang H.,Siadat S.H.,Pechenizkiy M.
Subject
Artificial Intelligence,Computer Science Applications,General Engineering
Reference52 articles.
1. Database-friendly random projections: Johnson–Lindenstrauss with binary coins;Achlioptas;Journal of Computer and System Sciences,2003
2. Bartl, E., Rezanková, H. & Sobisek, L. (2011). Comparison of classical dimensionality reduction methods with Novel approach based on formal concept analysis. In J. Yao, S. Ramanna, G. Wang, & Z. Suraj, (Eds.), Rough sets and knowledge technology (RSKT 2011), October 9–12 2011, Banff, Canada. Lecture notes in computer science (Vol. 6954, pp. 26–35). Springer.
3. Improving the efficiency of multidimensional scaling in the analysis of high-dimensional data using singular value decomposition;Bécavin;Bioinformatics,2011
4. Bingham, E., & Mannila, H. (2001). Random projection in dimensionality reduction: applications to image and text data. In Proceedings of the seventh ACM SIGKDD international conference on knowledge discovery and data mining (KDD 2001), August 26–29 2001, ACM: San Francisco, CA, USA. pp. 245–250.
5. Jagadeesh Chandra Bose, R. P. & van der Aalst, W. M. P. (2009). Context Aware Trace Clustering: Towards Improving Process Mining Results. In Proceedings of the SIAM international conference on data mining (SDM 2009), April 30–May 2 2009. (pp. 401–412). Sparks, Nevada, USA.
Cited by
56 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献