An Exact Graph Edit Distance Algorithm for Solving Pattern Recognition Problems

International audienceGraph edit distance is an error tolerant matching technique emerged as a powerful and flexible graph matching paradigm that can be used to address different tasks in pattern recognition, machine learning and data mining; it represents the minimum-cost sequence of basic edit operations to transform one graph into another by means of insertion, deletion and substitution of vertices and/or edges. A widely used method for exact graph edit distance computation is based on the A* algorithm. To overcome its high memory load while traversing the search tree for storing pending solutions to be explored, we propose a depth-first graph edit distance algorithm which requires less memory and searching time. An evaluation of all possible solutions is performed without explicitly enumerating them all. Candidates are discarded using an upper and lower bounds strategy. A solid experimental study is proposed; experiments on a publicly available database empirically demonstrated that our approach is better than the A* graph edit distance computation in terms of speed, accuracy and classification rate

Optimizing the Implementation of the Greedy Algorithm to Achieve Efficiency in Garbage Transportation Routes

Until now, the waste problem is still a crucial problem, including in the Banyumas Regency area. The uncontrolled accumulation of garbage at the TPS will of course greatly disturb the comfort of the community around the TPS. As is the case with the accumulation of garbage at TPS (Garbage Disposal Sites) in North Purwokerto District. When searching for this garbage transportation route, the Greedy Algorithm works by finding the smallest weight point by calculating the route passed and calculating the weight depending on the weight of the stages that have been passed and the weight at the stage itself. Based on the results of the system testing that has been made, the shortest route for transporting waste from the starting point of the Banyumas Environment Office is to go to the final disposal site in Tipar, and return to the starting point of the Banyumas Environmental Office. So that the total distance traveled to return to the starting point is 53 km long. Based on the findings and discussions of this research, the results obtained are the determination of the shortest route from node A back to node A. Specifically, the route involves traveling from the DLH Banyumas Regency to TPS Grendeng, TPS Karangwangkal, TPS Pabuwaran, TPS Sumampir, TPS Purwanegara, TPS Bobosan, to TPA Tipar, and then returning to DLH Banyumas Regency. These results have implementable implications in the context of waste management in this area, with a total distance traveled of 53 kilometers