Researcher Name Disambiguation: Feature Learning and Affinity Propagation Clustering

Yu, Zhizhi; Yang, Bo

doi:10.1007/978-3-030-01851-1_22

Cited by 1 publication

(1 citation statement)

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“…Xu et al [3] utilized a network embedding-based technique to disambiguate the author name, in which networks are created from papers that have a target ambiguous author name. Yu and Yang [4] solved the challenging task under the circumstances of inadequate data sources. A feature learning means and an affinity propagation clustering were taken into account.…”

Section: Related Workmentioning

confidence: 99%

Chinese Personal Name Disambiguation Based on Clustering

Fan

Liu

2021

Wireless Communications and Mobile Computing

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Personal name disambiguation is a significant issue in natural language processing, which is the basis for many tasks in automatic information processing. This research explores the Chinese personal name disambiguation based on clustering technique. Preprocessing is applied to transform raw corpus into standardized format at the beginning. And then, Chinese word segmentation, part-of-speech tagging, and named entity recognition are accomplished by lexical analysis. Furthermore, we make an effort to extract features that can better disambiguate Chinese personal names. Some rules for identifying target personal names are created to improve the experimental effect. Additionally, many calculation methods of feature weights are implemented such as bool weight, absolute frequency weight, tf-idf weight, and entropy weight. As for clustering algorithm, an agglomerative hierarchical clustering is selected by comparison with other clustering methods. Finally, a labeling approach is employed to bring forward feature words that can represent each cluster. The experiment achieves a good result for five groups of Chinese personal names.

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Section: Related Workmentioning

confidence: 99%