1. Bit-Close: a fast incremental concept calculation method.
- Author
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Ke, Yunfeng, Li, Jinhai, and Li, Shen
- Subjects
COGNITIVE learning ,COMPUTER science ,CONCEPT learning ,DATA mining ,ALGORITHMS - Abstract
The theory of Formal Concept Analysis (FCA) finds diverse applications in fields like knowledge extraction, cognitive concept learning and data mining. The construction of a concept lattice significantly influences the effectiveness of formal concept analysis; hence, the development of high-performance algorithms for concept construction is crucial. In this paper, we introduce a novel algorithm called "Bit-Close" for formal concept construction. Bit-Close leverages bit representation and operations, fundamental to computer science, to enhance the In-Close algorithm. Furthermore, we explore the parallel method of Bit-Close. Our experimental results, obtained from multiple public and random datasets, demonstrate that Bit-Close outperforms In-Close by approximately 20% and is significantly better than other competing algorithms. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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