通过 web 挖掘实现连贯的关键短语提取

关键短语对于总结、索引、标记、分类、聚类、突出显示、浏览和搜索等各种 purpose 都很有用。自动关键短语提取的任务是从给定文档的文本中选择关键短语。自动关键短语提取使得为那些没有手动分配关键短语的大量文档生成关键短语变得可行。previous keyphrase extraction algorithms的局限性在于，所选关键短语偶尔是不可连贯的。也就是说，大多数输出关键短语可能彼此拟合良好，但也可能有少数 appear to be outliers, with no clear semantic relation to the majority or to each other. This paper presents enhancements to the Kea keyphrase extraction algorithm that are designed to increase the coherence of the extracted keyphrases. The approach is to use the degree of statistical association among candidate keyphrases as evidence that they may be semantically related. The statistical association is measured using web mining. Experiments demonstrate that the enhancements improve the quality of the extracted keyphrases. Furthermore, the enhancements are not domain-specific: the algorithm generalizes well when it is trained on one domain (computer science documents) and tested on another (physics documents).