LiveBot: Generating Live Video Comments Based on Visual and Textual Contexts
Table 3: The average similarity between two comments at different intervals (Edit distance: lower is more similar; Tf-idf: higher is more similar; Human: higher is more similar).
['[BOLD] Interval', '[BOLD] Edit Distance', '[BOLD] TF-IDF', '[BOLD] Human']
We also validate the correlation between the neighboring comments. For each comment, we select its 20 neighboring comments to form 20 comment pairs. Then, we calculate the sentence similarities of these pairs in terms of three metrics, which are edit distance, tf-idf, and human scoring. For human scoring, we ask three annotators to score the semantic relevance between two comments, and the score ranges from 1 to 5. We group the comment pairs according to their time intervals: 0 -1s, 1-3s, 3-5s, 5-10s, and more than 10s. It shows that the comments with a larger interval are less similar both literally and semantically. Therefore, it concludes that the neighboring comments have higher correlation than the non-neighboring ones.