# Journal Name Extraction from Japanese Scientific News Articles

## TL;DR

This paper presents a character-based method for extracting journal names from Japanese scientific news articles, leveraging contextual features to improve identification accuracy.

## Contribution

It introduces a novel context-based extraction approach specifically designed for Japanese scientific news articles, focusing on the distribution hypothesis of journal names.

## Key findings

- The method effectively identifies journal names using context features.
- Context distribution plays a key role in journal name recognition.
- The approach demonstrates promising extraction accuracy.

## Abstract

In Japanese scientific news articles, although the research results are described clearly, the article's sources tend to be uncited. This makes it difficult for readers to know the details of the research. In this paper, we address the task of extracting journal names from Japanese scientific news articles. We hypothesize that a journal name is likely to occur in a specific context. To support the hypothesis, we construct a character-based method and extract journal names using this method. This method only uses the left and right context features of journal names. The results of the journal name extractions suggest that the distribution hypothesis plays an important role in identifying the journal names.