1. A method implemented in a computer system for discovering a relationship between entities comprising: receiving, at said computer system, input data W representing a word vector matrix and input data G representing a link graph matrix; computing a current log likelihood of the input data W and G, the current likelihood of the input data being a probability distribution function of parameters, the parameters representing topic similarity between unstructured texts of the entities and community similarity between the entities; comparing the current log likelihood of the input data and a previous log likelihood of the input data computed previously; updating values of the parameters, if the current log likelihood is larger than the previous log likelihood; or constructing at least one graph based on the updated values of the parameters, if the current log likelihood is less than or equal to the previous log likelihood, the at least one graph indicating the relationship between the entities, wherein a program using a processor unit executes one or more of said computing comparing, updating, and constructing.