Identifying Similar Movie Characters Quickly but Effectively Using Non-exhaustive Pair-wise Attention

Identifying similar movie characters is a captivating task that can be our first step to understand the commonalities between human characteristics and experiences. Here, we seek to identify similar movie character descriptions and evaluate our findings based on whether they belong to a common fan-curated trope (theme). Rather than simply comparing the embedding representation of character description, we use a pair-wise attention model to make use of complex word/span-level relationships across the two character descriptions to predict the similarity of the two characters. Naively, such a model would require the exhaustive comparison of each character to all other characters, which is an O(n^2) operation with respect to the number of characters, making it unfeasible to be used in practice. We reduced this into an O(n) operation using a two-step approach that involves choosing only a tiny fraction of character-pairs to perform pairwise attention on while still being effective in this task. Our approach performs at least 9-27% better than methods based on state-of-the-art paragraph embedding representations.