Abstract: The word is processed for electronic homework to generate semantic unit sequences.  The sequence’s longest common subsequence is calculated by dynamic programming method. A new concept: vacancy degree of longest common subsequence is introduced. Building a similarity degree model based on an intuitionistic fuzzy number which is inducted by longest common subsequence’s length and vacancy degree, the model is natural and reasonable. Based on intuitionistic fuzzy transitive closure clustering analysis algorithm, the electronic homewors are clustered. By discussing the electronic homework plagiarism detection based on intuitionistic fuzzy set cluster analysis algorithm’s complexity, and then gives an application example of the algorithm, the results show that the algorithm is reasonable and efficient.

Key words: similarity degree, vacancy degree, intuitionistic fuzzy set, plagiarism detection