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An Automatic Marking Approach for Subjective Questions Based on Short Text Similarity Computing
Received date: 2014-07-24
Revised date: 2014-09-16
Online published: 2014-10-05
The key technology of automatic marking of text subjective questions is to improve the accuracy of computing the short text similarity between the answer of a student and the standard answer. This paper proposes a short text similarity computing method combed with the manual standard of similarity judgment, sets of words, orders of words and synonyms designs and implements the corresponding automatic marking system for subjective questions. It develops a manual grading standard base of items, and the experiment data set is chosen from the 387 real test questions and answers in the bank training area. In the experiments, between the automatic marking results and the manual marking results, the identical rate reaches 58%, and the acceptable marking accuracy is about 80%.
Key words： short text; similarity; subjective question; automatic marking
Zhang Junsheng , Shi Chongde , Xu Hongjiao , Gao Yingfan , He Yanqing . An Automatic Marking Approach for Subjective Questions Based on Short Text Similarity Computing[J]. Library and Information Service, 2014 , 58(19) : 31 -38 . DOI: 10.13266/j.issn.0252-3116.2014.19.005
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