Papers by Takeshi Masuyama

2 papers
A Case Study on Neural Headline Generation for Editing Support (N19-2)

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Challenge: a news-aggregator is a website or mobile application that aggregates web content . dozens of professional editors manually create their headlines, which are much shorter than the original headlines.
Approach: They propose a neural headline generation model that automatically generates short headlines from news articles.
Outcome: The proposed model is deployed to an editing support tool and compares editors' behavior before and after the release.
Extractive Headline Generation Based on Learning to Rank for Community Question Answering (C18-1)

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Challenge: Community question answering (CQA) forums do not always have appropriate headlines because of user-generated content.
Approach: They propose an extractive headline generation method that extracts the most informative substring from each question as its headline.
Outcome: The proposed method outperforms baselines including a prefix-based method . it uses the prefix of a question as its headline to create the most informative substring .

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