基于潜在语义特性的语义双关语检测及双关词定位

Homographic Puns Detection and Puns Location Based on Latent Semantic Characteristics

语义双关语是幽默、笑话和喜剧等作品的来源之一,在人类写作的发展进程中具有重要的历史地位。由于语义双关语存在歧义难懂的特点,因此难以挖掘语义双关语的潜在语义信息,故目前语义双关语的检测和双关词的定位是自然语言处理任务中的一项困难和挑战。该文在语义双关语的理论基础上,挖掘了一系列的潜在语义特性,并构建了对应每个特性的特征集,用以检测语义双关语;同时从潜在语义特性出发,提出了一种基于词向量和同义词融合的语义相似度匹配算法实现语义双关词的定位。在SemEval 2017Task 7和Pun of the Day数据集上均取得了较好的实验结果,验证了该文所提出的检测算法和定位算法。

Homographic pun,as a common source of humor in jokes and other comedic word,is hard to detect and locate the homographic pun words.We design a series of latent semantic characteristics and corresponding features to detect homographic puns.Then,a semantic similarity matching algorithm is proposed to locate pun words based on the fusion of Word Embedding and Sysnet.Experiment results on SemEval 2017 Task 7 and Pun of the Day demonstrate the effectiveness of the proposed method.