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Abstract Datasets can be provided in different formats, including binary, multi-valued, or numerical. They are represented by diverse algebraic structures such as lattices, concept lattices, and bi concept lattices. The present thesis deals with data analysis using different lattices structures. They have been applied widely in data mining, web documentary retrieval, machine learning, knowledge discovery and software engineering and so on. The process of building a concept lattice from data set is virtually a process of conceptual clustering. Hass diagram of concept lattice represents the association between objects and attributes and reflects the relationship of generalization and specialization among concepts. So it can be regarded as an efficient method for data analysis and knowledge acquisitioN. |