Name
Abstract | ||
|---|---|---|
Most previous approaches on comparing the results for software architecture recovery are designed to handle only flat decompositions. In this paper, we propose a novel distance called Split-Jaccard Distance of Hierarchical Decompositions. It extends the Jaccard coefficient and incorporates the concept of the splits of leaves in a hierarchical decomposition. We analyze the proposed distance and derive its properties, including the lower-bound and the metric space. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1587/transinf.2014EDL8113 | IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS |
Keywords | Field | DocType |
split, clustering, hierarchical, decomposition, distance, metric | Hierarchical clustering,Pattern recognition,Dendrogram,Computer science,Hierarchical clustering of networks,Artificial intelligence,Distance matrix,Jaccard index,Software architecture,Cluster analysis | Journal |
Volume | Issue | ISSN |
E98D | 3 | 1745-1361 |
Citations | PageRank | References |
0 | 0.34 | 9 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ki-Seong Lee | 1 | 9 | 3.28 |
| Byung-Woo Hong | 2 | 295 | 21.99 |
| Youngmin Kim | 3 | 7 | 1.88 |
| Jaeyeop Ahn | 4 | 0 | 0.34 |
| Chan-gun Lee | 5 | 99 | 29.51 |