• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2011, Vol. 33 ›› Issue (7): 172-177.

• 论文 • 上一篇    下一篇

改进型单向贴近度主观题自动评分算法的研究

郭扉扉,尹文生   

  1. (华中科技大学机械科学与工程学院,湖北 武汉 430074)
  • 收稿日期:2010-07-05 修回日期:2010-11-20 出版日期:2011-07-21 发布日期:2011-07-25
  • 作者简介:郭扉扉(1985),女,辽宁辽阳人,硕士生,研究方向为人工智能和自然语言处理。尹文生(1964),男,湖南常宁人,博士,副教授,CCF会员(E200011026M),研究方向为CAD、人工智能和自然语言处理。

Research on an Improved Automatic Assessment  Algorithm for Subjective Examination Questions Based on the Single Similar Degree

GUO Feifei,YIN Wensheng   

  1. (School of Mechanical Science and  Engineering,
    Huazhong University of Science and  Technology,Wuhan 430074,China)
  • Received:2010-07-05 Revised:2010-11-20 Online:2011-07-21 Published:2011-07-25

摘要:

本文介绍和分析了主观题自动评分的国内外研究现状,在基于模糊数学中贴近度理论和单向贴近度字符串匹配方法的基础上,结合动态规划算法思想,设计并实现了基于语义脉络的自动评分算法。该算法以句子作为基本语义单元,将标准答案分解为代表得分点的词串,并为这些词串加入同义词链去匹配学生答案语句,使语义表达更加完善和准确;同时利用动态规划算法使匹配按照词的顺序进行,避免仅仅按照字的出现次数匹配所造成的机械式匹配错误;最后根据文本中句子与关键词的匹配程度给出得分。在给出基本算法的主要思想以及程序流程图的基础上,结合实例分析证明了该算法的可行性。

关键词: 主观题, 自然语言理解, 语义脉络, 单向贴近度, 动态规划

Abstract:

The present research status both at home and abroad are introduced and analyzed. By using the string matching method of the single similar degree which is based on the closeness theory of fuzzy mathematics, and combining with dynamic programming algorithms, a subjective automatic assessment algorithm based on a semantic skeleton is designed and implemented. Taking sentence as the basic semantic unit, this approach separates standard answers into some keywords representing the points for score, adds a synonym chain for the keywords to match the students’ answers which can make expression much more complete and accurate, and then calculates the score according to the matching degree. The string matching is conducted in accordance with the order of words by using dynamic programming algorithms to avoid the mistakes caused by mechanical matching, which is carried out only according to words. Then the main idea and the flow of the algorithm are given. Finally, the feasibility of this algorithm is proved through the analysis of an example.

Key words: subjective;natural language understanding;semantic skeleton;single similar degree;dynamic programming