Constrained concept lattice and its construction method
Jifu Zhang · Caai Transactions on Intelligent Systems · 2006
Concept lattice is an effective formal tool for data analysis and knowledge mining.However,with the increase of data volume,the node number of the constructed concept lattice from the original formal context usually increases enormously,and large storage is required accordingly.Meantime,users are not interested in all intensions of attributes set,and more computational time is unnecessarily consumed as a result.In order to reduce time and storage complexity and improve the utility and pertinence to the concept lattice construction,predicate logic is used to describe the user interested background knowledge,and a new concept lattice structure-constrained concept lattice is presented.Then based on the background knowledge,a construction algorithm(CCLA)is also provided.Through some theoretical analysis,it is shown that the proposed algorithm can reduce the storage and time complexity of concept lattice construction process.Finally,the experiments with celestial body spectra as the formal context validate the proposed algorithm.