Research status and collaboration analysis based on big data mining: an empirical study of Alzheimer's disease

Abstract

This paper employs text mining techniques that aimed to facilitate technology information. First, this paper used patent data to monitor technological development trends systematically to show the technology research status from perspectives of country, institution, technology fields, and subjects. Secondly, this study explores the cooperation network institutions and inventors by applying the data mining approaches, social network analysis,. Additionally, the sequence analysis is applied to reveal a more comprehensive and objective appearance of cooperative relationships, partners, and centrality. The empirical findings reveal four significant observations. (1) The R&D centres have been mainly influenced by the United States and other developed countries. (2) All technological fields in both B IPC and Derwent manual codes are concentrated around pharmaceutical activities. (3) 1-6c alkyl, pharmaceutical composition, and central nervous system et al. are traditional research and core subjects. 2-6c alkenyl, amino acid sequence, and 1-3c alkoxy et al. are the hot subjects. (4) The influential institutions are HOFFMANN LA ROCHE & CO AG F (degree centrality is 0.0872), ASTRAZENECA AB, MERCK SHARP & DOHME CORP, PFIZER INC and UNIV CALIFORNIA, INCYTE GENOMICS. (5) The influential inventors are WANG Y, BACHER G, and PETERS D.

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