FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4295709332> ?p ?o ?g. }

• W4295709332 endingPage "e0274253" @default.
• W4295709332 startingPage "e0274253" @default.
• W4295709332 abstract "Identifying promising research as early as possible is vital to determine which research deserves investment. Additionally, developing a technology for automatically predicting future research trends is necessary because of increasing digital publications and research fragmentation. In previous studies, many researchers have performed the prediction of scientific indices using specially designed features for each index. However, this does not capture real research trends. It is necessary to develop a more integrated method to capture actual research trends from various directions. Recent deep learning technology integrates different individual models and makes it easier to construct more general-purpose models. The purpose of this paper is to show the possibility of integrating multiple prediction models for scientific indices by network-based representation learning. This paper will conduct predictive analysis of multiple future scientific impacts by embedding a heterogeneous network and showing that a network embedding method is a promising tool for capturing and expressing scientific trends. Experimental results show that the multiple heterogeneous network embedding improved 1.6 points than a single citation network embedding. Experimental results show better results than baseline for the number of indices, including the author h -index, the journal impact factor (JIF), and the Nature Index after three years from publication. These results suggest that distributed representations of a heterogeneous network for scientific papers are the basis for the automatic prediction of scientific trends." @default.
• W4295709332 created "2022-09-14" @default.
• W4295709332 creator A5014750522 @default.
• W4295709332 creator A5021614922 @default.
• W4295709332 creator A5061592017 @default.
• W4295709332 creator A5071470375 @default.
• W4295709332 date "2022-09-14" @default.
• W4295709332 modified "2023-09-30" @default.
• W4295709332 title "Predictive analysis of multiple future scientific impacts by embedding a heterogeneous network" @default.
• W4295709332 cites W1570098300 @default.
• W4295709332 cites W1968257888 @default.
• W4295709332 cites W1968900087 @default.
• W4295709332 cites W2019162166 @default.
• W4295709332 cites W2028442912 @default.
• W4295709332 cites W2035920177 @default.
• W4295709332 cites W2057327293 @default.
• W4295709332 cites W2066938000 @default.
• W4295709332 cites W2068452509 @default.
• W4295709332 cites W2073726416 @default.
• W4295709332 cites W2081640113 @default.
• W4295709332 cites W2096320304 @default.
• W4295709332 cites W2106448406 @default.
• W4295709332 cites W2114118829 @default.
• W4295709332 cites W2127371360 @default.
• W4295709332 cites W2128438887 @default.
• W4295709332 cites W2129970907 @default.
• W4295709332 cites W2144574847 @default.
• W4295709332 cites W2325034227 @default.
• W4295709332 cites W2513105786 @default.
• W4295709332 cites W2521855374 @default.
• W4295709332 cites W2570427954 @default.
• W4295709332 cites W2743104969 @default.
• W4295709332 cites W2775574671 @default.
• W4295709332 cites W2793071066 @default.
• W4295709332 cites W2799012401 @default.
• W4295709332 cites W2884014654 @default.
• W4295709332 cites W2889326414 @default.
• W4295709332 cites W2915262604 @default.
• W4295709332 cites W2915612428 @default.
• W4295709332 cites W2952059922 @default.
• W4295709332 cites W2962756421 @default.
• W4295709332 cites W2981120761 @default.
• W4295709332 cites W3100357929 @default.
• W4295709332 cites W3100660404 @default.
• W4295709332 cites W3103571870 @default.
• W4295709332 cites W3104097132 @default.
• W4295709332 cites W3104717349 @default.
• W4295709332 cites W3105705953 @default.
• W4295709332 cites W3126115821 @default.
• W4295709332 cites W767067438 @default.
• W4295709332 doi "https://doi.org/10.1371/journal.pone.0274253" @default.
• W4295709332 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36103497" @default.
• W4295709332 hasPublicationYear "2022" @default.
• W4295709332 type Work @default.
• W4295709332 citedByCount "0" @default.
• W4295709332 crossrefType "journal-article" @default.
• W4295709332 hasAuthorship W4295709332A5014750522 @default.
• W4295709332 hasAuthorship W4295709332A5021614922 @default.
• W4295709332 hasAuthorship W4295709332A5061592017 @default.
• W4295709332 hasAuthorship W4295709332A5071470375 @default.
• W4295709332 hasBestOaLocation W42957093321 @default.
• W4295709332 hasConcept C111919701 @default.
• W4295709332 hasConcept C119857082 @default.
• W4295709332 hasConcept C121332964 @default.
• W4295709332 hasConcept C124101348 @default.
• W4295709332 hasConcept C136764020 @default.
• W4295709332 hasConcept C154945302 @default.
• W4295709332 hasConcept C191015642 @default.
• W4295709332 hasConcept C199360897 @default.
• W4295709332 hasConcept C2522767166 @default.
• W4295709332 hasConcept C2777382242 @default.
• W4295709332 hasConcept C2778805511 @default.
• W4295709332 hasConcept C2780801425 @default.
• W4295709332 hasConcept C32946077 @default.
• W4295709332 hasConcept C41008148 @default.
• W4295709332 hasConcept C41608201 @default.
• W4295709332 hasConcept C62520636 @default.
• W4295709332 hasConceptScore W4295709332C111919701 @default.
• W4295709332 hasConceptScore W4295709332C119857082 @default.
• W4295709332 hasConceptScore W4295709332C121332964 @default.
• W4295709332 hasConceptScore W4295709332C124101348 @default.
• W4295709332 hasConceptScore W4295709332C136764020 @default.
• W4295709332 hasConceptScore W4295709332C154945302 @default.
• W4295709332 hasConceptScore W4295709332C191015642 @default.
• W4295709332 hasConceptScore W4295709332C199360897 @default.
• W4295709332 hasConceptScore W4295709332C2522767166 @default.
• W4295709332 hasConceptScore W4295709332C2777382242 @default.
• W4295709332 hasConceptScore W4295709332C2778805511 @default.
• W4295709332 hasConceptScore W4295709332C2780801425 @default.
• W4295709332 hasConceptScore W4295709332C32946077 @default.
• W4295709332 hasConceptScore W4295709332C41008148 @default.
• W4295709332 hasConceptScore W4295709332C41608201 @default.
• W4295709332 hasConceptScore W4295709332C62520636 @default.
• W4295709332 hasFunder F4320321034 @default.
• W4295709332 hasIssue "9" @default.
• W4295709332 hasLocation W42957093321 @default.
• W4295709332 hasLocation W42957093322 @default.
• W4295709332 hasLocation W42957093323 @default.

• next