A Comparative Study of Formal Concept Analysis and Rough Set Theory in Data Analysis

By Yiyu Yao. Rough Sets and Current Trends in Computing, 2004

341 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Information Systems, Signal Processing

View Paper: https://www.semanticscholar.org/paper/95e5fd7fb122c862392ac862b22b0d45b9b12537

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

1. Weizhi Wu
2. Y. Qian
3. Jusheng Mi
4. Weihua Xu
5. Yee Leung
6. Jinhai Li
7. Changlin Mei
8. Qinghua Hu

In Information Systems

1. Weizhi Wu
2. Y. Qian
3. Weihua Xu
4. Yee Leung
5. Jusheng Mi
6. Jinhai Li

In Signal Processing

1. Yee Leung
2. Jusheng Mi
3. Y. Qian
4. Weizhi Wu

Citations in the corpus

• Concept learning via granular computing: A cognitive viewpoint (2014, background): “Up to now, for meeting the requirements of data analysis and knowledge manipulation, all kinds of concepts which carry certain meanings have been proposed such as abstract concepts [37], Wille’s concepts [42], object-oriented concepts [48,49] and property-oriented concepts [9].”
• Granular Computing and Knowledge Reduction in Formal Contexts (2009, result): “Studies have been made in recent years to compare and combine the two theories [21], [35], [52], [55].”