Mining Frequent Patterns in 2D+t Grid Graphs for Cellular Automata Analysis
نویسندگان
چکیده
A 2D grid is a particular geometric graph that may be used to represent any 2D regular structure such as, for example, pixel grids, game boards, or cellular automata. Pattern mining techniques may be used to automatically extract interesting substructures from these grids. 2D+t grids are temporal sequences of grids which model the evolution of grids through time. In this paper, we show how to extend a 2D grid mining algorithm to 2D+t grids, thus allowing us to efficiently find frequent patterns in 2D+t grids. We evaluate scale-up properties of this algorithm on 2D+t grids generated by a classical cellular automaton, i.e., the game of life, and we show that the extracted spatio-temporal patterns may be used to analyze this kind of cellular automata.
منابع مشابه
Tree pattern mining with tree automata constraints
Most work on pattern mining focuses on simple data structures such as itemsets and sequences of itemsets. However, a lot of recent applications dealing with complex data like chemical compounds, protein structures, XML and Web log databases and social networks, require much more sophisticated data structures such as trees and graphs. In these contexts, interesting patterns involve not only freq...
متن کاملConstraint-based Tree Pattern Mining
Most work on pattern mining focus on simple data structures like itemsets or sequences of itemsets. However, a lot of recent applications dealing with complex data like chemical compounds, protein structure, XML and Web Log databases, social network, require much more sophisticated data structures (trees or graphs) for their specification. Here, interesting patterns involve not only frequent ob...
متن کاملUsing Tree Automata for XML Mining and Web Mining with Constraints
Most work on pattern mining focus on simple data structures like itemsets or sequences of itemsets. However, a lot of recent applications dealing with complex data like chemical compounds, protein structure, XML and Web Log databases and social network, require much more sophisticated data structures (trees or graphs) for their specification. Here, interesting patterns involve not only frequent...
متن کاملOn Combined Approach for mining FSG in Transactionized Graph Datasets
Graph Data mining has ushered into new era with advanced data mining techniques. Mining Frequent Sub Graphs is the crucial area which appeals the ease of extracting the patterns in the graph. Typical graph data like Social Networks, Biological Networks (for metabolic pathways) and Computer Networks needs analysis of virtual networks of a category. Such graphs need be modeled as layered to disti...
متن کاملTime and Space Efficient Discovery of Maximal Geometric Graphs
A geometric graph is a labeled graph whose vertices are points in the 2D plane with an isomorphism invariant under geometric transformations such as translation, rotation, and scaling. While Kuramochi and Karypis (ICDM2002) extensively studied the frequent pattern mining problem for geometric subgraphs, the maximal graph mining has not been considered so far. In this paper, we study the maximal...
متن کامل