Inspiration discovery based on related domains

For academic scientists, it is not satisfy to meet their researches requirements only finding out the basic scientific research activities recent years. The future of research in this field, evolution of the hot spot and the research front of relevant fields has the same Ref. value for current field researching. To solve these problems, we use inspiration discovery method by mining and clustering analysis the hidden information of related literatures from the particular research areas´ classic journals and high-ranking conferences with a designed visual interface. The experiment results show the proposed method, on average, improved the detection precision to 92.86% and reduced false alarm rate of discussed candidate outliers to 0.0074%. Findings showed the proposed method could provide with valid depictions of future research cross different domains.