@inproceedings{2d373a7240b64c678e8c69e68f7de2de,
title = "NDFMF: An Author Name Disambiguation Algorithm Based on the Fusion of Multiple Features",
abstract = "Author name disambiguation is a very important and complex research topic. During the retrieval and research of literature the quality of the investigation results has been reduced because of the high probability of different authors sharing the same name, which lengthens the whole cycle of the scientific research. Therefore, it is necessary to find a reasonable and efficient method to distinguish the different authors who share the same name. In this paper, an author name disambiguation algorithm based on the fusion of multiple features (NDFMF) is proposed. First we proposed a single feature similarity detection algorithm (SFSD). SFSD is used to compute the degree of similarity between two features of a paper and to assess the threshold value. Then, SFSD is used to realize the preliminary SFSD-based disambiguation algorithm (SFSDD). Furthermore, different features are evaluated according to the disambiguation results of author names and the evaluation metrics, including precision, recall and F-measure with SFSDD. The evaluation parameter of weight (W) is introduced to express each feature's influence in disambiguation. NDFMF can disambiguate author names more efficiently based on the fusion of multiple features. Experiments were implemented to test the performance of NDFMF. Experimental results show that NDFMF was effective in the disambiguation precision, recall and F-measure.",
keywords = "Fusion, Multiple features, Name disambiguation, Single feature",
author = "Xiaolong Xu and Yongping Li and Mark Liptrott and Nik Bessis",
note = "Funding Information: This work is supported by the National Natural Science Foundation of China under Grant 61472192, the National Key Research and Development Program of China under Grant 2018YFB1003702, the Scientific and Technological Support Project (Society) of Jiangsu Province under Grant BE2016776, and the “333” project of Jiangsu Province under Grant BRA2017228. Funding Information: ACKNOWLEDGEMENTS This work is supported by the National Natural Science Foundation of China under Grant 61472192, the National Key Research and Development Program of China under Grant 2018YFB1003702, the Scientific and Technological Support Project of Jiangsu Province under Grant BE2016776, and the “333” project of Jiangsu Province under Grant BRA2017228. Publisher Copyright: {\textcopyright} 2018 IEEE.; 42nd IEEE Computer Software and Applications Conference, COMPSAC 2018 ; Conference date: 23-07-2018 Through 27-07-2018",
year = "2018",
month = jun,
day = "8",
doi = "10.1109/COMPSAC.2018.10226",
language = "English",
isbn = "9781538626665",
series = "Proceedings - International Computer Software and Applications Conference",
publisher = "IEEE Computer Society",
pages = "187--190",
editor = "Claudio Demartini and Sorel Reisman and Ling Liu and Edmundo Tovar and Hiroki Takakura and Ji-Jiang Yang and Chung-Horng Lung and Ahamed, {Sheikh Iqbal} and Kamrul Hasan and Thomas Conte and Motonori Nakamura and Zhiyong Zhang and Toyokazu Akiyama and William Claycomb and Stelvio Cimato",
booktitle = "Proceedings - 2018 IEEE 42nd Annual Computer Software and Applications Conference, COMPSAC 2018",
address = "United States",
}