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Abstract

In this article, we present a method to automatically build large labeled datasets for the author ambiguity problem in the academic world by leveraging the authoritative academic resources, ORCID and DOI. Using the method, we built LAGOS-AND, two large, gold-standard sub-datasets for author name disambiguation (AND), of which LAGOS-AND-BLOCK is created for clustering-based AND research and LAGOS-AND-PAIRWISE is created for classification-based AND research. Our LAGOS-AND datasets are substantially different from the existing ones. The initial versions of the datasets (v1.0, released in February 2021) include 7.5 M citations authored by 798 K unique authors (LAGOS-AND-BLOCK) and close to 1 M instances (LAGOS-AND-PAIRWISE). And both datasets show close similarities to the whole Microsoft Academic Graph (MAG) across validations of six facets. In building the datasets, we reveal the variation degrees of last names in three literature databases, PubMed, MAG, and Semantic Scholar, by comparing author names hosted to the authors' official last names shown on the ORCID pages. Furthermore, we evaluate several baseline disambiguation methods as well as the MAG's author IDs system on our datasets, and the evaluation helps identify several interesting findings. We hope the datasets and findings will bring new insights for future studies. The code and datasets are publicly available.

Date

22. 1.2023 18:40:36

Source

Journal of the Association for Information Science and Technology. 74(2023) no.2, S.168-185

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Abstract

By analyzing 63 English-speaking institutions that offer ALA-accredited master's programs in library and information studies, this research aims to explore the education for knowl­edge organization (KO) at different levels and across fields. This research examines the KO courses that are the required courses and elective courses in the MLIS programs, that are offered in other master's programs and graduate certificate programs, that are adapted to the undergraduate degree and certificate programs, and that are particularly developed for programs other than MLIS. The findings indicate that the great majority of MLIS programs still have a focus on or a significant component of knowl­edge organization as their required course and include the knowl­edge organization elective courses, particularly library cataloging and classification, on their curriculum. However, there is a variety of the offerings of KO related courses across the programs in an institution or in the same program across the institutions. It shows a promising trend that the traditional and new KO courses play an important role in many other programs, at different levels and across fields. With the conventional, adapted, or innovative content, these courses demonstrate that the principles and skills of knowl­edge organization are applicable to a wide variety of settings, can be integrated with other disciplinary knowl­edge and emerging technologies, and meet the needs of different career pathways and groups of learners.

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Source

Journal of the Association for Information Science and Technology. 73(2022) no.12, S.1741-1754

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Source

Journal of the Association for Information Science and Technology. 74(2023) no.13, S.1485-1497