Graph-Community Detection for Cross-Document Topic Segment Relationship Identification
Table 3: AVL corpus used in the experiments.
['[BOLD] Topic', '[BOLD] Segments', '[BOLD] #Words', '[BOLD] #Vocab']
The segmented AVL corpus was then annotated with equivalence relationships. This annotation was done in the same spirit as the 4S corpus, using a user-centered approach. The difficulty in this task is in the presence of multiple topics in a single segment. The annotation process consisted of going through each document individually. In the case of the first document, the segments were tagged with the topic they discussed. On subsequent documents, it was assessed if the segments should be assigned with an existed tag or if a new tag should be created. After the annotation process, a total of 15 different relationships were found in the set of 86 segments. The experiments only used the topics that appeared in the majority of the documents (49 segments).