Statistical Phrase Extraction Techniques In Natural Lang

在自然语言文本中定位重要短语的能力对于索引或放置文本中的超链接是有用的。在任何一种情况下，人们都寻求改善对文本材料的获取。在过去，最常用的短语定位方法是词性标记器。我们开发了一种新的方法，使用评分算法来对短语进行排名，以确定它们可能有多有用。已经开发和测试了许多不同的方法。这些方法与词干处理和寻找同义词的词尾变化变体的方法相结合，用于检索目的。UMLS系统还被用于查找用于索引的同义短语。这些方法正被应用于在NCBI的电子教科书项目中寻找有用的短语，该项目目前在网上，但仍在开发中。这些方法也开始应用于PubMedCentral生物和医学期刊论文数据库，以及通过扫描该数据库期刊的过刊而编制OCR材料的索引。目前的工作集中在为该系统添加复杂的缩写检测能力。

The ability to locate important phrases in natural language text is useful for the purposes of indexing or placing hyperlinks in text. In either case one seeks to improve access to the textual material. In the past the most common method used for the location of phrases has been a part of speech tagger. We have developed a new approach that uses scoring algorithms to rank phrases as to how useful they may be. A number of different methods have been developed and tested. These are being combined with methods of stemming and of finding inflectional variants of phrases that are synonymous for retrieval purposes. The UMLS system is also being used to find synonymous phrases for indexing. These methods are being applied to find useful phrases in NCBI's electronic textbook project that is currently online but still under development. The methods are also beginning to be applied to the PubMedCentral database of journal articles in biology and medicine and to the indexing of OCR material from the scanning of back issues of journals for this database. Current work is focused on adding a sophisticated abbreviation detection capability to this system.