원문정보
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
After constructing graph representations for a set of web documents, there are several techniques to determine the similarity between same-type objects. This is achieved by graph matching. The measure of similarity may be based on the size of the maximum common subgraph. In this paper, we are interested in the problem of maximum common subgraph(MCS) and median graph computation for the purpose of graph clustering using backtracking search. Median of a graph helps in the extension of prevalent term frequency based clustering algorithms to graph based clustering.
목차
Abstract
1. Introduction
2. Graph Distance
3. Steps for Extracting the MCS
4. Backtracking Scheme of AMCSI based on CSIA
5. The AMCSI Algorithm
6. Calculation of the Distance between the Two Graphs
7. Median of a Set of Graphs
8. Conclusion
Acknowledgments
References:
1. Introduction
2. Graph Distance
3. Steps for Extracting the MCS
4. Backtracking Scheme of AMCSI based on CSIA
5. The AMCSI Algorithm
6. Calculation of the Distance between the Two Graphs
7. Median of a Set of Graphs
8. Conclusion
Acknowledgments
References:
저자정보
참고문헌
자료제공 : 네이버학술정보