Crossword puzzles have traditionally served not only as entertainment but
also as an educational tool that can be used to acquire vocabulary and language
proficiency. One strategy to enhance the educational purpose is
personalization, such as including more words on a particular topic. This paper
focuses on the case of encouraging people's interest in news and proposes a
framework for automatically generating news-centric crossword puzzles. We
designed possible scenarios and built a prototype as a constraint satisfaction
and optimization problem, that is, containing as many news-derived words as
possible. Our experiments reported the generation probabilities and time
required under several conditions. The results showed that news-centric
crossword puzzles can be generated even with few news-derived words. We
summarize the current issues and future research directions through a
qualitative evaluation of the prototype. This is the first proposal that a
formulation of a constraint satisfaction and optimization problem can be
beneficial as an educational application.

本研究提出了一个自动生成以新闻为中心的填字游戏的框架，通过包含尽可能多的新闻相关单词，来增加人们对新闻的兴趣，并通过对原型的定性评估总结了当前问题和未来研究方向。这是首个提出将约束满足和优化问题的形式化应用于教育领域的建议。