Generating novel design concepts is a cornerstone for producing innovative products. Although many methods have been proposed for supporting the task, their performance depends on human ability. The ultimate goal of this research is to build a method supporting designers to generate novel design concepts with the knowledge of human creativity. Toward the goal, this research assumes that the more distant two function concepts chosen, the more novel idea would be come up with by the combination of the two concepts. Based on the assumption, this paper introduces a notion of novelty potential of the combination of two function concepts, and builds a method to assess it by the function similarity. Some alternative methods are proposed to calculate it with the integration of a lexical database for natural language called WordNet and a distributional semantics method called word2vec. They are verified with an evaluation experiment which performs correlation analysis between the human’s evaluation of the novelty potential and the proposed method’s assessment of function similarity. This paper discusses which method matches a human sense most, and its possibility for design concept generation based on the results of the experiment.