Large-scale name disambiguation of Chinese patent inventors (1985–2016)

Yin, Deyun; Motohashi, Kazuyuki; Dang, Jianwei

doi:10.1007/s11192-019-03310-w

Cited by 15 publications

(12 citation statements)

References 39 publications

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“…This equilibration is the origin of the previously observed onomastic profusion. It generates a new set of homonyms that can confound clustering or manual (supervised) disambiguation processes [15], similarly to the prevalence of certain names among Chinese authors [10].…”

Section: Names and Marketing Strategymentioning

confidence: 99%

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Deterministic Bibliometric Disambiguation Challenges in Company Names

et al. 2023

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Section: Names and Marketing Strategymentioning

confidence: 99%

“…Two key considerations are the appearance of synonyms, a single name in multiple forms, and homonyms, a name shared by different entities [10]. The latter issue is the principal concern of this study.…”

Section: Introductionmentioning

confidence: 98%

Deterministic Bibliometric Disambiguation Challenges in Company Names

et al. 2023

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“…Secondly, names are not unique and are stored and written differently, and they contain misspellings, initials, given names or family names missing, and given names and family names which are are swapped. Finally, different people can share the same name-especially Chinese authors [28]. For that reason, we built an algorithm that uses fuzzy similarities between names, compares abstracts of patents and papers, and compares subject areas (disciplines/domains) of patent inventors and authors of papers.…”

Section: Record Linkage Algorithmmentioning

confidence: 99%

“…Moreover, the majority of records describe authors of Chinese origin with short and simple names. Thus, multiple authors share the same name [28]. Affiliations could not be used because the patent database does not store them.…”

Section: Introductionmentioning

confidence: 99%

Record Linkage of Chinese Patent Inventors and Authors of Scientific Articles

Nowak

Franus

Zhang³

et al. 2021

Applied Sciences

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We present an algorithm to find corresponding authors of patents and scientific articles. The authors are given as records in Scopus and the Chinese Patents Database. This issue is known as the record linkage problem, defined as finding and linking individual records from separate databases that refer to the same real-world entity. The presented solution is based on a record linkage framework combined with text feature extraction and machine learning techniques. The main challenges were low data quality, lack of common record identifiers, and a limited number of other attributes shared by both data sources. Matching based solely on an exact comparison of authors’ names does not solve the records linking problem because many Chinese authors share the same full name. Moreover, the English spelling of Chinese names is not standardized in the analyzed data. Three ideas on how to extend attribute sets and improve record linkage quality were proposed: (1) fuzzy matching of names, (2) comparison of abstracts of patents and articles, (3) comparison of scientists’ main research areas calculated using all metadata available. The presented solution was evaluated in terms of matching quality and complexity on ≈250,000 record pairs linked by human experts. The results of numerical experiments show that the proposed strategies increase the quality of record linkage compared to typical solutions.

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“…Kim, Kim and Kim (2021) shows that disambiguation of the names of Chinese authors of English language publications is easier if their name in Chinese characters is available alongside their phoneticized names. Yin, Motohashi and Dang (2020) presents the results of an effort to disambiguate the names of inventors listed on Chinese patents between 1985 and 2016. They use supervised learning approach that begins with hand-labelled data for training.…”

Section: Introductionmentioning

confidence: 99%

Nominative Linkage of Records of Officials in the China Government Employee Dataset-Qing (CGED-Q)

Campbell

Chen

2022

hlcs

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We introduce our approach to the nominative linkage of records of Qing officials who were included in the China Government Employee Datasets-Qing (CGED-Q) Jinshenlu (JSL) and Examination Records (ER). We constructed these datasets by transcription of quarterly rosters of civil and military officials produced by the government and by commercial presses, and records of examination degree holders. We assess each of the primary attributes available in the original sources in terms of their usefulness for disambiguation, focusing on their diversity and potential for inconsistent recording. For officials who were not affiliated with the Eight Banners, these primary attributes include surname, given name, and province and county of origin. For the small subset of officials who were affiliated with the Bannermen, we assess the available data separately. We also assess secondary attributes available in the data that may be useful for adjudicating candidate matches. We then describe the approach that we developed that addresses the issues we identified with the primary and secondary attributes. The issues we have identified and the approach that we have developed will be of interest to researchers engaged in similar efforts to construct and link datasets based on elite males in historical China.

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Large-scale name disambiguation of Chinese patent inventors (1985–2016)

Cited by 15 publications

References 39 publications

Deterministic Bibliometric Disambiguation Challenges in Company Names

Deterministic Bibliometric Disambiguation Challenges in Company Names

Record Linkage of Chinese Patent Inventors and Authors of Scientific Articles

Nominative Linkage of Records of Officials in the China Government Employee Dataset-Qing (CGED-Q)

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