基于HowNet的词汇语义倾向计算

在互联网技术快速发展、网络信息爆炸的今天,通过计算机自动分析大规模文本中的态度倾向信息的技术,在企业商业智能系统、政府舆情分析等诸多领域有着广阔的应用空间和发展前景。同时,语义褒贬倾向研究也为文本分类、自动文摘、文本过滤等自然语言处理的研究提供了新的思路和手段。篇章语义倾向研究的基础工作是对词汇的褒贬倾向判别。本文基于HowNet,提出了两种词汇语义倾向性计算的方法:基于语义相似度的方法和基于语义相关场的方法。实验表明,本文的方法在汉语常用词中的效果较好,词频加权后的判别准确率可达80%以上,具有一定的实用价值。

Semantic Orientation Computing Based on HowNet

Nowadays,with the development of Internet and information explosion,automated techniques for analyzing author's attitudes towards specific events will make great effort to business intelligence and public opinion survey.Semantic orientation inference has become a meaningful tool,which could provide useful information for text classification,summarization,filtering etc.Measuring the semantic orientation of words would greatly contribute to predicting the author's attitude in a passage.In this paper,a simple HowNet-based method for semantic orientation computation of Chinese words is introduced.Although this method requires only a few seed words,satisfactory results can still be obtained.And the performance is even better for frequently used words,with the frequency-weighted accuracy of above 80%.