Finding Top-N Pseudo Formal Concepts with Core Intents

  • Authors:

  • Yoshiaki Okubo;Makoto Haraguchi

  • Affiliations:

  • Division of Computer Science Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan 060-0814;Division of Computer Science Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan 060-0814

  • Venue:
  • MLDM '09 Proceedings of the 6th International Conference on Machine Learning and Data Mining in Pattern Recognition
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

We discuss in this paper a method for finding Top-N Pseudo Formal Concepts . A pseudo formal concept (pseudo FC in short) can be viewed as a natural approximation of formal concepts. It covers several formal concepts as its majorities and can work as a representative of them. In a word, such a pseudo FC is defined as a triple (X , Y , S ), where X is a closed set of objects, Y a set of primary features , S a set of secondary features . Then, the concept tells us that 1) all of the objects in X are associated with the primary features Y and 2) for each secondary feature y *** S , a majority of X is also associated with y . Therefore, X can be characterized not only exactly by Y but also naturally and flexibly by Y *** { y } for each secondary feature y . Our task is formalized as a problem of finding Top-N ***-Valid ( *** , ρ )-Pseudo Formal Concepts . The targets can be extracted based on clique search . We show several pruning and elimination rules are available in our search. A depth-first branch-and-bound algorithm with the rules is designed. Our experimental result shows that a pseudo FC with a natural conceptual meaning can be efficiently extracted.