确定好的关系提取模式Identifying Good Patterns for Relation Extraction |
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课程网址: | http://videolectures.net/is2012_starc_relation_extraction/ |
主讲教师: | Janez Starc |
开课单位: | 约瑟夫·斯特凡学院 |
开课时间: | 2012-11-16 |
课程语种: | 英语 |
中文简介: | 在基于模式的关系提取中,优选具有高精度和回忆的模式产生语义上有用的关系。我们提出了一种类似于n gram提取的技术,它从大型文本语料库中提取模式,并计算统计数据,如频率,最小令牌频率和标准化期望,这些都是指导首选模式。模式将实例和/或一个可变长度间隙命名为参数。我们从大型新闻语料库中提取模式并将其转换为Cyc关系。我们关注四种模式,我们通过断言它们与Cyc知识库的翻译关系来评估。 |
课程简介: | In pattern based relation extraction, patterns that with high precision and recall produce semantically useful relations are preferred. We present a technique similar to n-gram extraction that extracts patterns from large text corpora and calculates statistics, like frequency, minimal token frequency and normalized expectation, which guide to preferred patterns. Patterns have named-instances and/or one variable length gap as arguments. We extracted patterns from a large news corpus and translated them to Cyc relations. We focused on four patterns, which we evaluate by asserting their translated relations to Cyc knowledge base. |
关 键 词: | 文本语料库; 文本语料库; 翻译关系 |
课程来源: | 视频讲座网 |
最后编审: | 2020-07-29:yumf |
阅读次数: | 44 |