Extraction of corporate performance factors from summaries of financial statements considering context

Abstract

In this paper, we proposed a method for automatically extracting sentences containing corporate performance factors from summaries of financial statements at high accuracy. More specifically, only sentences that can be determined to be corporate performance factors in the summaries of financial statements with high probability are extracted, and those sentences are used as training data. We trained the neural network by using the word representation of the training data. Furthermore, by using the appearance tendency of the corporate performance factor sentence specific to summaries of financial statements as a bias of model output, it became possible to extract with a higher f-measure than related work that performs filtering processing using corporate keywords.