Discovering Research Teams from Scientific Papers and Patents

Most existing team discovery methods are based on collaboration networks using papers or patents data. They usually have low efficiency because they have to create the whole network containing all researchers. In addition, these methods can't immediately output research topics for each discovered team. A novel team discovery method is presented to solve these problems. The method extracts institutional names from papers and patents to build the institution base, and extracts authors and inventors to build the researcher base after name disambiguation. Then, the method exploits Author Topic model to mine distributions of topics and researchers in papers and patents and builds research topic base. The component analysis technique is used to discover teams under each research topic by analyzing its collaboration network. Experiments show the proposed method can identify teams without establishing a whole network by integrating papers and patent data. Meanwhile, the method can provide research topics for found teams.