Doc2vec-based link prediction approach using SAO structures
Application to patent network
Bibliographic Data
| ID | 21442929 |
|---|---|
| Authors | Byungun Yoon (0000-0002-1110-4011, Dongguk University), Songhee Kim (0000-0002-9327-7863, Dongguk University), Sunhye Kim (Dongguk University), Hyeonju Seol (0000-0001-6953-9766, Chungnam National University, corresponding author) |
| Year | 2022 |
| Volume | 127 |
| Issue | 9 |
| Pages | 5385-5414 |
| Publication date | 2022-09-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Scientometrics (JOURNAL) |
| Journal identifiers | ISSN: 0138-9130 • E-ISSN: 1588-2861 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s11192-021-04187-4 |
| OpenAlex | W3213121620 |
| Language | EN |
| Citations received | 7 |
| References cited | 27 |
Citation · Context (archaeology) · Data mining · Field (mathematics) · Information retrieval · Link (geometry) · Similarity (geometry) · The Internet · World Wide Web · Artificial Intelligence · Complex Network Analysis Techniques · Computational Drug Discovery Methods · Computer Science · Machine Learning in Materials Science · Mathematics
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Understanding scientific knowledge evolution patterns based on egocentric network perspective
Identification of emerging technology topics (ETTs) using Bert-based model and sematic analysis
Self-supervised scientific document recommendation based on contrastive learning
From technology opportunities to ideas generation via cross-cutting patent analysis
An exploration method for technology forecasting that combines link prediction with graph embedding
| Citations per year | 2.33 |
|---|---|
| Citation span | 2023 - 2025 (3) |
| Highly cited | No |