Text Similarity Computing Based on HowNet Sememe Space
Xiao Zhi-ju · Science Technology and Engineering · 2013
For the shortcomings of pairwise orthogonal terms assumption and lacking of sematic meaning in vector space model,a new method is proposed basing on general vector space model and using the similarity of HowNet sememes to calculate text similarity. According to TF-IDF weight of text terms,texts are transformed into vectors of HowNet sememe space. The included angles of text vectors are used to calculate the text similarity. By text clustering contrast experiment with VSM and GVSM to verify the proposed method,the result shows that the proposed method has achieved a better performance at text sematic similarity computing.