Tacit knowledge mining algorithm based on linguistic truth-valued concept lattice
This work provides a mathematical tool for mining tacit knowledge, but it appears incremental as it builds on prior research about linguistic truth-valued concept lattices.
The authors tackled the problem of mining tacit knowledge by establishing a 6-ary linguistic truth-valued concept lattice model and developing an algorithm based on structure consistency, resulting in the formulation of necessary and sufficient conditions for tacit knowledge formation.
This paper is the continuation of our research work about linguistic truth-valued concept lattice. In order to provide a mathematical tool for mining tacit knowledge, we establish a concrete model of 6-ary linguistic truth-valued concept lattice and introduce a mining algorithm through the structure consistency. Specifically, we utilize the attributes to depict knowledge, propose the 6-ary linguistic truth-valued attribute extended context and congener context to characterize tacit knowledge, and research the necessary and sufficient conditions of forming tacit knowledge. We respectively give the algorithms of generating the linguistic truth-valued congener context and constructing the linguistic truth-valued concept lattice.