Abstract: The increase in data size has caused the difficulty of obtaining information. How to get accurate information from a large amount of data is a hot topic. Inspired by the Hidden Markov Model, a multi-truth discovery algorithm (Graph Truth Discovery, GraphTD) based on the graph model is proposed. With the help of the credibility transition matrix described in each data source, the probability that the data value is true is calculated. Meanwhile, an improved method for determining the initial true value is proposed, which can effectively improve the accuracy of GraphTD and avoid many shortcomings in the multi-truth discovery of the voting method. Experimental results on the book author dataset show that GraphTD can effectively improve the recognition accuracy of truth value, and CVote can significantly improve the discovery accuracy of truth value through the optimized selection strategy of initial truth value.

Key words: hidden Markov model, GraphTD truth discovery algorithm, graph model, CVote algorithm