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Automatic extraction of glossary terms from natural language requirements

机译:从自然语言要求中自动提取词汇表术语

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We present a method for the automatic extraction of glossary terms from unconstrained natural language requirements. The glossary terms are identified in two steps — a) compute units (which are candidates for glossary terms) b) disambiguate between the mutually exclusive units to identify terms. We introduce novel linguistic techniques to identify process nouns, abstract nouns and auxiliary verbs. The identification of units also handles co-ordinating conjunctions and adjectival modifiers. This requires solving co-ordination ambiguity and adjectival modifier ambiguity. The identification of terms among the units adapts an in-document statistical metric. We present an evaluation of our method over a real-life set of software requirements' documents and compare our results with that of a base algorithm. The intricate linguistic classification and the tackling of ambiguity result in superior performance of our approach over the base algorithm.
机译:我们提出了一种从不受约束的自然语言要求中自动提取词汇表术语的方法。词汇表术语分为两个步骤-a)计算单元(它们是词汇表术语的候选者)b)消除互斥单元之间的歧义以识别术语。我们介绍了新颖的语言技术来识别过程名词,抽象名词和辅助动词。单位的识别还处理协调连词和形容词修饰语。这需要解决协调歧义和形容词修饰语歧义。单元之间的术语识别采用文档内统计度量。我们对一组真实的软件需求文档进行了评估,并将我们的结果与基本算法进行了比较。复杂的语言分类和歧义的解决导致我们的方法优于基本算法。

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