Rough sets provide a useful tool for data preprocessing during data mining. However, many
algorithms related to some problems in rough sets, such as attribute reduction, are greedy …

Rough sets are efficient for data pre-processing in data mining. However, some important
problems such as attribute reduction in rough sets are NP-hard, and the algorithms to solve …

Rough sets are efficient for attribute reduction and rule extraction in data mining. However,
many important problems including attribute reduction in rough sets are NP-hard, therefore …

Rough sets provide an efficient tool for attribute reduction and rule extraction. However,
many important problems in rough set theory, including attribute reduction, are NP-hard and …

Rough sets are efficient to extract rules from information systems. Matroids generalize the
linear independency in vector spaces and the cycle in graphs. Specifically, matroids provide …

Rough sets provide an efficient tool for dealing with the vagueness and granularity in
information systems. They are widely used in attribute reduction in data mining. There are …

As an important technique for granular computing, rough sets deal with vagueness and
granularity in information systems. Rough sets are usually used in attribute reduction …

Rough sets were proposed to deal with vagueness and incompleteness of knowledge in
information systems. In this field, there are many optimization issues such as attribute …

Rough set theory is an effective tool for dealing with vagueness or uncertainty in information
systems. It is efficient for data pre-process and widely used in attribute reduction in data …

Rough sets are efficient for data pre-processing during data mining. However, some
important problems such as attribute reduction in rough sets are NP-hard and the algorithms …