A Collective Approach to Scholar Name Disambiguation (Extended Abstract)
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| Title: | A Collective Approach to Scholar Name Disambiguation (Extended Abstract) |
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| Authors: | Jinpeng Huai, Dongsheng Luo, Xiang Zhang, Shuai Ma, Yaowei Yan, Chunmin Hu |
| Source: | 2021 IEEE 37th International Conference on Data Engineering (ICDE). :2317-2318 |
| Publisher Information: | IEEE, 2021. |
| Publication Year: | 2021 |
| Subject Terms: | 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology |
| Description: | This study investigates name disambiguation for scholarly data. We propose a collective approach, which considers the connections of different ambiguous names, such that it initially treats each author reference as a unique author entity and reformulates the bibliography data as a heterogeneous multipartite network. Disambiguation results of one author name propagate to the others in the network. To further deal with the sparsity problem caused by limited available information, we also introduce word-word and venue-venue similarities and measure author similarities by assembling similarities from multiple perspectives. Using three real-life datasets, we experimentally show that our approach is both effective and efficient. |
| Document Type: | Article |
| DOI: | 10.1109/icde51399.2021.00244 |
| Access URL: | https://dblp.uni-trier.de/db/conf/icde/icde2021.html#Luo0YHZH21 https://www.computer.org/csdl/proceedings-article/icde/2021/918400c317/1uGXsnGDirC https://pennstate.pure.elsevier.com/en/publications/a-collective-approach-to-scholar-name-disambiguation-extended-abs http://doi.org/10.1109/ICDE51399.2021.00244 https://ieeexplore.ieee.org/document/9458707/ https://doi.org/10.1109/ICDE51399.2021.00244 |
| Rights: | IEEE Copyright |
| Accession Number: | edsair.doi.dedup.....155e0f5284844b842fba6a3f408a4ca5 |
| Database: | OpenAIRE |
Nájsť tento článok vo Web of Science | Abstract: | This study investigates name disambiguation for scholarly data. We propose a collective approach, which considers the connections of different ambiguous names, such that it initially treats each author reference as a unique author entity and reformulates the bibliography data as a heterogeneous multipartite network. Disambiguation results of one author name propagate to the others in the network. To further deal with the sparsity problem caused by limited available information, we also introduce word-word and venue-venue similarities and measure author similarities by assembling similarities from multiple perspectives. Using three real-life datasets, we experimentally show that our approach is both effective and efficient. |
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| DOI: | 10.1109/icde51399.2021.00244 |