An Approach Using Concept Lattice Structure for Data Mining and Information Retrieval

  • Tran Lam Quan Center for Research and Implementation, Vietnam Airlines
  • Vu Tat Thang Institute of Information Technology (IOIT), Vietnamese Academy of Science and Technology (VAST)


Since the 1980s, the concept lattice was studied and applied to the problems of text mining, frequent itemset, classification, etc. The formal concept analysis - FCA is one of the main techniques applied in the concept lattice. FCA is a mathematical theory which is applied to the data mining by setting a table with rows describing objects and columns describing attributes, with relationships between them, and then sets up the concept lattice structure. In the area of information retrieval, FCA considers the correlation of objects-attributes the same as those of documents-terms. In the process of setting up the lattice, FCA defines each node in the lattice as a concept. The algorithm for the construction of concept lattice will install a couple on each node, including a set of documents with common terms, and a set of terms which co-occurs in documents. In a larger scale, each concept in the lattice could be recognized as a couple of questions - answers. In the lattice, the action of browsing up or down of nodes will allow approaching more general concepts or more detail concepts, respectively.


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How to Cite
QUAN, Tran Lam; THANG, Vu Tat. An Approach Using Concept Lattice Structure for Data Mining and Information Retrieval. Journal of Science and Technology: Issue on Information and Communications Technology, [S.l.], v. 1, p. 1-7, aug. 2015. ISSN 1859-1531. Available at: <>. Date accessed: 24 mar. 2023. doi: