Graph-Community Detection for Cross-Document Topic Segment Relationship Identification
Table 4: Results of the clustering algorithms in the AVL corpus. Best results are in bold.
['[BOLD] Clustering Algorithm', '[ITALIC]  [BOLD] A [BOLD] R [BOLD] I', '[ITALIC]  [BOLD] F [BOLD] 1', '[ITALIC]  [BOLD] A [BOLD] c [BOLD] c']
Results show that most of the techniques obtained low scores in all evaluation metrics. The only exceptions were the Agglomerative and Spectral clustering. It should be noted that not all evaluation metrics agree as to the best technique, since Spectral clustering had higher scores in ARI and F1, whereas Agglomerative clustering had the best Acc score. Also, there is not a strict correlation between the evaluation metrics. For example, Mean Shift obtained the lowest ARI, but would be considered as one of the best performing techniques in F1. In this context, we set as a baseline the Spectral clustering technique, since it was the best in two of evaluation metrics and still performed well on the third one.