A Markov Chain Approach to Random Generation of Formal Concepts
نویسنده
چکیده
A Monte Carlo approach using Markov Chains for random generation of concepts of a finite context is proposed. An algorithm similar to CbO is used. We discuss three Markov chains: non-monotonic, monotonic, and coupling ones. The coupling algorithm terminates with probability 1. These algorithms can be used for solving various information retrieval tasks in large datasets.
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