基于多层次术语集的双语术语抽取
Bilingual Terminology Extraction Using Multi-level Termhood
摘要：
目的：术语是在特定语境中使用的技术词汇或表达方式的集合，是一门形式化学科的核心概念，通常应用于机器翻译、信息检索、信息抽取和文本分类等领域。双语术语抽取在双语词典编纂、双语本体构建、机器翻译和跨语言信息检索等领域的研究。本文研究了基于多层次术语集的单语术语抽取和双语术语对齐问题。设计/方法/途径：提出了一种基于多层术语的方法。该方法通过对语料库的比较，计算候选术语的术语度以及包含该术语的句子。由于术语和通用词在语料库中的分布不同，在平行语料库上进行术语对齐时，术语集也可以用来约束和提高术语对齐的性能。本文提出了一种基于词组约束的双语词对齐方法。研究结果：实验结果表明，多层次的术语可以得到更好的性能比现有的术语提取方法。如果将术语类别作为约束因素，则可以提高双语术语对齐的性能。
英文摘要：
Purpose: Terminology is the set of technical words or expressions used in specific contexts, which denotes the core concept in a formal discipline and is usually applied in the fields of machine translation, information retrieval, information extraction and text categorization, etc. Bilingual terminology extraction plays an important role in the application of bilingual dictionary compilation, bilingual Ontology construction, machine translation and cross-language information retrieval etc. This paper addresses the issues of monolingual terminology extraction and bilingual term alignment based on multi-level termhood. Design/methodology/approach: A method based on multi-level termhood is proposed. The new method computes the termhood of the terminology candidate as well as the sentence that includes the terminology by the comparison of the corpus. Since terminologies and general words usually have differently distribution in the corpus, termhood can also be used to constrain and enhance the performance of term alignment when aligning bilingual terms on the parallel corpus. In this paper, bilingual term alignment based on termhood constraints is presented. Findings: Experiment results show multi-level termhood can get better performance than existing method for terminology extraction. If termhood is used as constrain factor, the performance of bilingual term alignment can be improved.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
