A recommendation approach of scientific non-patent literature on the basis of heterogeneous information network

Abstract

In the procedure of exploring science-technology linkages, non-patent literature (NPL) in patents, particularly scientific NPL, is considered to signal the relatedness between the developed technology and the cited science. However, many prior art search tools may not be powered with the cross-collection recommendation technique, or have limited cross-collection recommendation capabilities. In this paper, we present an approach to recommend scientific NPL for a focal patent on the basis of heterogeneous information network. This study views this cross-collection recommendation problem as a link prediction problem on the basis of meta-path counting approach. Extensive experiments on DrugBank dataset in the pharmaceutical field indicate that our approach is feasible and effective. This work provides a novel perspective on scientific NPL recommendation for a focal patent and opens up further possibilities for the linkages between science and technology. Nevertheless, more experiments in other fields are required to verify the recommended effects of the approach proposed in this study.