Tag line generating system using knowledge extracted from statistical analyses

Hiroaki Yamane, Masafumi Hagiwara

研究成果: Article査読

2 被引用数 (Scopus)


This paper proposes a tag line generating system based on knowledge obtained by tag line analyses. Using a tag line corpus, two features of tag line—part-of-speech N-gram and word usage—are obtained as knowledge. Based on these features, the tag line generating system generates tag line candidates. More specifically, for a given theme, a keyword is entered into the proposed system. For each keyword, the system selects related terms unique to the theme. And enormous number of candidates is generated by using a large-scale N-gram corpus. The proposed system subsequently selects candidates based on the degree of similarity, grammatical structures, and mutual information volume. The highest scored candidates are selected as final output. The performance of the proposed system has been evaluated by subjects in terms of sentence quality, category appropriateness, keyword appropriateness, and overall quality. The experimental results show that the proposed system is able to generate suitable tag lines for a given theme and keywords, indicating a potential online tag line generator in the future.

ジャーナルAI and Society
出版ステータスPublished - 2013 2月

ASJC Scopus subject areas

  • 哲学
  • 人間とコンピュータの相互作用
  • 人工知能


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