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Improving Keyword Extraction from Movie Subtitles by Utilizing Temporal Properties

机译:利用时间属性改善电影字幕的关键词提取

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In our work we aim at keyword extraction from movie subtitles. Keywords and key phrases although missing the context can be found very helpful in finding, understanding, organizing and recommending the media content. Generally, they are used by search engines to help find the relevant information. Movies and video content are becoming massively available and widespread. The ability to automatically describe and classify videos has a vast domain of application. In our work we select movie subtitles as a source of information to process. We proposed a method for keyword extraction from movie subtitles by analysing their temporal properties and detecting conversations. We evaluated our method by conducting two experiments (a priori synthetic experiment and a posteriori user experiment) involving 200 movies and show that conversation analysis can improve traditional approaches based on automatic term extraction algorithms.
机译:在我们的工作中,我们的目标是从电影字幕中提取关键词。关键字和关键词短语虽然缺少上下文,但可以发现它们对查找,理解,组织和推荐媒体内容非常有帮助。通常,搜索引擎使用它们来帮助查找相关信息。电影和视频内容正变得大量可用和广泛传播。自动描述和分类视频的能力具有广泛的应用领域。在我们的工作中,我们选择电影字幕作为要处理的信息源。我们提出了一种通过分析电影字幕的时间特性和检测对话来从电影字幕中提取关键字的方法。我们通过进行涉及200部电影的两个实验(先验合成实验和后验用户实验)对我们的方法进行了评估,结果表明,会话分析可以改进基于自动术语提取算法的传统方法。

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