CAJ | 학술논문

为了充分利用和整合词义消歧不同的知识库和语义资源，本文提出了一种基于语义关联图的方法。该方法以语义关系作为边，以词语的概念作为节点建立语义关联图，然后通过计算词义与上下文词语在语义关联图中的关联强度来确定歧义词的词义。语义关联图能够将多种消歧知识源比如词典、标注语料和生语料中的知识整合在一起，扩大了消歧知识的来源。本文方法在Senseval-3汉语词汇样本消歧任务中选择两个词，与一种基于知识的方法和有指导的方法进行了对比实验，实验结果验证了本文方法的有效性。
위료충분이용화정합사의소기불동적지식고화어의자원，본문제출료일충기우어의관련도적방법。해방법이어의관계작위변，이사어적개념작위절점건립어의관련도，연후통과계산사의여상하문사어재어의관련도중적관련강도래학정기의사적사의。어의관련도능구장다충소기지식원비여사전、표주어료화생어료중적지식정합재일기，확대료소기지식적래원。본문방법재Senseval-3한어사회양본소기임무중선택량개사，여일충기우지식적방법화유지도적방법진행료대비실험，실험결과험증료본문방법적유효성。
In order to fully utilize and integrate different knowledge and semantic resources of Word Sense Disambiguation (WSD), this paper proposes a WSD method based on semantic relationship graph.The method constructs the semantic relationship graph using semantic relationship as side and taking word sense as a node,and then determines the sense of ambiguous by calculating the strength of the relationship in semantic relationship graph between the word sense and its context. Semantic relationship graph can integrate a variety of disambiguation knowledge resources such as dictionaries, tagged corpus and raw corpus to expand the sources of disambiguation knowledge.We perform WSD experiment on two words of Chinese lexicon sample task of Senseval-3 comparing with the method based on knowledge and the supervised method. The experiment result conifrms the effectiveness of our method.