Journal Name Extraction from Japanese Scientific News Articles
This addresses a domain-specific issue for readers of Japanese scientific news who need to find research details, but it is incremental as it builds on existing extraction methods.
The paper tackled the problem of extracting journal names from Japanese scientific news articles, where sources are often uncited, by hypothesizing that journal names occur in specific contexts and using a character-based method with left and right context features, achieving results that support the distribution hypothesis.
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.