String vector based AHC for text clustering

In this research, we propose the string vector based version of AHC algorithm as the approach to the text clustering. Using the traditional version leads to the three main problems: huge dimensionality, sparse distribution, poor transparency, since texts need to be encoded into numerical vectors. In order to solve the problems, in this research, we encode texts into string vectors, define the similarity measure between them, and modify the AHC algorithm into the version where a string vector is given as its input. As the benefits from this research, we expect the better performance, the more compact representation, and the better transparency. Hence, this research is intended to improve the text clustering performance, by solving the problems.