The current sentence similarity calculation method does not consider the multi-attributes of the keywords in the sentence and cannot better measure the sentence similarity. Therefore, this study proposes a sentence similarity calculation method based on multi-attribute fusion, considering the sentence structure and the attributes contained. First, this method extracts the attributes of the sentence including the word frequency, word order, part of speech, and sentence length. Next, the analytic hierarchy process (AHP) is used to calculate the weight of each attribute and verify the rationality of the weight, and then the weighted fusion of the similarity of the four attributes is conducted. This proposed calculation method for multi-attribute sentence similarity is tested on the constructed dataset to verify its reliability and feasibility, and it is compared with other traditional methods in recall rates, accuracy rates, and normalized F-metric values.The results show that this method has balanced recall and accuracy rates and a high F-measure value of 83.57%.