WOLVES: Achieving Correct Provenance Analysis by Detecting and Resolving Unsound Workflow Views. - Peng Sun; Ziyang Liu 001; Sivaramakrishnan Natarajan; Susan B. Davidson; Yi Chen 001 (Proc. VLDB Endow., 2009)

CODS: Evolving Data Efficiently and Scalably in Column Oriented Databases. - Ziyang Liu 001; Sivaramakrishnan Natarajan; Bin He 001; Hui-I Hsiao; Yi Chen 001 (Proc. VLDB Endow., 2010)

XSACT: A Comparison Tool for Structured Search Results. - Ziyang Liu 001; Sivaramakrishnan Natarajan; Peng Sun; Stephen Booher; Tim Meehan; Robert Winkler; Yi Chen 001 (Proc. VLDB Endow., 2010)

Query Expansion Based on Clustered Results. - Ziyang Liu 001; Sivaramakrishnan Natarajan; Yi Chen 001 (Proc. VLDB Endow., 2011)

Optimized fuzzy-based group recommendation with parallel computation. - Sivaramakrishnan Natarajan; Subramaniyaswamy Vairavasundaram; Logesh Ravi (J. Intell. Fuzzy Syst., 2019)

Resolving data sparsity and cold start problem in collaborative filtering recommender system using Linked Open Data. - Senthilselvan Natarajan; Subramaniyaswamy Vairavasundaram; Sivaramakrishnan Natarajan; Amir H. Gandomi (Expert Syst. Appl., 2020)

An effective user clustering-based collaborative filtering recommender system with grey wolf optimisation. - Sivaramakrishnan Natarajan; V. Subramaniyaswamy 001; Logesh Ravi; Varadarajan Vijayakumar 001; Xiao-Zhi Gao 001; S. L. Rakshana Sri (Int. J. Bio Inspired Comput., 2020)

Enhancing recommendation stability of collaborative filtering recommender system through bio-inspired clustering ensemble method. - Logesh Ravi; V. Subramaniyaswamy 001; Malathi Devarajan; Sivaramakrishnan Natarajan; Varadarajan Vijayakumar 001 (Neural Comput. Appl., 2020)

A deep learning-based hybrid model for recommendation generation and ranking. - Sivaramakrishnan Natarajan; V. Subramaniyaswamy 001; Amelec Viloria; V. Vijayakumar 002; Senthilselvan Natarajan (Neural Comput. Appl., 2021)