2026-10-12T19:57:00Z https://www.scidb.cn/oai

10.11922/sciencedb.j00104.00100 2022-04-06T13:48:50Z

2022-04-06 Datasets for NLPCC2022.SharedTask5.Track1 doi:10.11922/sciencedb.j00104.00100 en In recent years, the indexing for scientific research literature is becoming more and more important with the increasing number of such literature in various fields. According to incomplete statistics, about 2.5 million research papers published from about 28100 journals every year. Search engines, digital libraries and citation indexes are widely used to search these documents and publications. The intelligent classification of scientific research literature is helpful to improve the retrieval efficiency and quality of users. Hierarchical multi-label classification is a common method for indexing scientific research literature. For example, both arXiv and Microsoft Academic adopt this method. Moreover, hierarchical multi-label classification is also a challenging task in text classification. Multi-label Classification; Hierarchical multi-labels; English Scientific Literature CNPIEC KEXIN LTD PUBLIC https://creativecommons.org/licenses/by-nc-nd/4.0/ dataset Science Data Bank