Author disambiguation method based on paper key attribute network

Abstract

The invention discloses an author disambiguation method based on a paper key attribute network. The key attribute relationship network is a relationship network which is formed by collecting key attributes in papers and through correlations between the key attributes, a relationship network of the same institution and a relationship network of the same field are respectively formed, and finally, the relationship network of the key attributes of the papers is formed. According to the method, a paper name, an author institution and an author field in a paper are extracted, and a relationship network is established around the author name; when the paper authors are disambiguated, the names of the paper authors are matched, author institutions in the relationship network are combined, and theauthor field can effectively solve the problem that the names of the paper authors are the same but correspond to different actual authors. In addition, by combining the paper name with the coauthor of the current author to be disambiguated and matched again, the situation that the same actual author has different name writing methods can be effectively solved.

Description

Technical field [0001] The invention belongs to the technical field of disambiguation of authors of the same name and different authors of a paper, and specifically relates to an author disambiguation method based on a key attribute network of a paper. Background technique: [0002] In recent years, with the development of the Internet, all aspects of people's lives have been closely related to the Internet, as are academic activities. Most of today's academic achievements can be inquired through the Internet. But in the face of massive data, how to accurately query the data we need is particularly important. At present, most paper platforms can search through authors and retrieve the information of papers published by the inquired author. In this case, the accuracy of the author's name is particularly important. But in reality, the following two situations usually occur. [0003] One is that the name of the author of a paper published by the same author may be presented in dif...

AI Technical Summary

Problems solved by technology

[0005] The above two situations have caused great difficulties for paper retrieval. In the existing system, many paper search engines directly search for string matching. As the amount of data increases, the retrieved results are very large. To a certain extent, its accuracy cannot be guaranteed, and in most cases, it is necessary to manually screen the results

With the improvement of the accuracy requirements for the author of the p

Images