Roman Galperin (Carey Business School)

Marshall Shuler (Neuroscience, School of Medicine)

How do people learn to search for information in unfamiliar domains? What is the role of peers and social context? We aim to improve our understanding of these questions by studying human search behavior in examining innovations. We will apply the insights developed in neuroscience and social sciences to develop a model of social learning of search, using data on hundreds of millions of searches conducted by patent examiners while evaluating inventions. We propose that the examiners’ task of finding specific, relevant knowledge in unfamiliar fields under time constraints represents a general problem of efficient search in knowledge space. We expect that examiners learn to search more efficiently over time and rely on peers for the learning. Our study will contribute to current theories of learning and search for knowledge, produce specific suggestions for improving the patent examination process, and create a dataset for the larger researcher community.