Project evaluation method using non-formatted text information based on multi-granular linguistic labels

We propose a novel project evaluation method for non-formatted Chinese text evaluation information. First, the non-formatted Chinese text evaluation information is determined and expressed using extensible markup language and a hypertext preprocessor. Then, the evaluation problem is transformed into a multiple-criteria decision-analysis problem based on multi-granular linguistic labels, including a comprehensive evaluation score for alternatives and an evaluation criteria point score for incomplete items. Next, we propose a weighting model for the criteria based on the minimal difference between the comprehensive evaluation score and the evaluation criterion point score of decision-makers. We establish an estimation model for incomplete evaluation items with the minimal evidence distance of Dempster–Shafer theory using maximal group consistency. In addition, we calculate a weighting for the decision-makers using the similarity of the group. Finally, we present a score modification method for alternatives based on weights of the criteria and the decision-maker. We use a soft science project evaluation and selection to illustrate the application process and feasibility of the proposed method.