A Graph Combination With Edge Pruning‐Based Approach for Author Name Disambiguation

Abstract

Author name disambiguation (AND) is a challenging problem due to several issues such as missing key identifiers, same name corresponding to multiple authors, along with inconsistent representation. Several techniques have been proposed but maintaining consistent accuracy levels over all data sets is still a major challenge. We identify two major issues associated with the AND problem. First, the namesake problem in which two or more authors with the same name publishes in a similar domain. Second, the diverse topic problem in which one author publishes in diverse topical domains with a different set of coauthors. In this work, we initially propose a method named ATGEP for AND that addresses the namesake issue. We evaluate the performance of ATGEP using various ambiguous name references collected from the Arnetminer Citation (AC) and Web of Science (WoS) data set. We empirically show that the two aforementioned problems are crucial to address the AND problem that are difficult to handle using state‐of‐the‐art techniques. To handle the diverse topic issue, we extend ATGEP to a new variant named ATGEP‐web that considers external web information of the authors. Experiments show that with enough information available from external web sources ATGEP‐web can significantly improve the results further compared with ATGEP.