Host: The Japanese Society for Artificial Intelligence
Name : The 32nd Annual Conference of the Japanese Society for Artificial Intelligence, 2018
Number : 32
Location : [in Japanese]
Date : June 05, 2018 - June 08, 2018
In this paper, I proposed a framework of estimating invention task and means using Rough Set Theory. It is important to check exists patents before submitting own patents or sailing new products. However, it is take long time to check a lot of patents. In order to support this task, I propose a framework which estimates decision rules from labeled patent journal using Rough Set Theory and predicts invention task and means from unlabeled patents using them. First, this framework extracts terms from abstracts of patents which experts identified invention task and means in advance. Secondly, it selects terms based on document frequency and makes a Document Term Matrix. Thirdly, it makes decision rules by Rough Set Theory. Finally, it predicts invention task and means using these rules. In order to evaluate this system, I am doing experiments with an expert. I will tell the experimental results and evaluation results about this method on the conference.
