Paper same-named author disambiguation method based on high-confidence-degree characteristic attribute hierarchical-clustering method

Abstract

The invention relates to a paper same-named author disambiguation method based on a high-confidence-degree characteristic attribute hierarchical-clustering method. The paper same-named author disambiguation method mainly comprises the steps that 1, original data is firstly extracted from an academic search engine, characteristic attribute values are extracted, and normalized processing is conducted on the values; 2, another name groups are firstly formed according to rules, and homonymic author ambiguity groups are generated according to the another name groups;3, similarity calculation and disambiguation method selection is performed for characteristic attributes respectively; 4, the high-confidence-degree characteristic attribute hierarchical-clustering method is achieved through attribute confidence-degree assessment performed in the step 3. By applying the paper same-named author disambiguation method, the name disambiguation speed is ensured, and the disambiguation accuracy is also improved.

Description

technical field [0001] The invention relates to a disambiguation method for authors with the same name in papers, in particular to a method for disambiguation of authors with the same name in papers based on a hierarchical clustering method for feature attributes with high confidence. Background technique [0002] In today's society, people rely heavily on the Internet for academic activities, and one of the most important reasons is that the Internet has the advantages of resource sharing. Nowadays, the vast majority of academic papers are stored in network databases in the form of electronic resources. People only need to use some legitimate network channels to easily find, read and download the learning resources they need, especially academic papers. With the change of people's academic research habits, more and more academic search engines (DLs) are born and continue to develop. They provide users with the service of searching papers by author, and return the list of al...

AI Technical Summary

Problems solved by technology

However, the same-name ambiguity problem has been affecting the quality of the search

However, with the rapid increase of network resource data, these traditional methods have gradually shown some limitations and deficiencies in the face of the possible problems of lack of information, information errors and deep-seated ambiguity. It will lead to a large and disorganized number of papers returned to users when searching by author name, which will cause confusion or even mislead researchers, reduce the efficiency of academic activities, and even affect the final results of academic research in severe cases

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