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NEMO: Next career move prediction with contextual embedding
Liangyue Li
, Jaewon Yang
, How Jing
, Qi He
,
Hanghang Tong
, Bee Chung Chen
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Chapter in Book/Report/Conference proceeding
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Conference contribution
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Dive into the research topics of 'NEMO: Next career move prediction with contextual embedding'. Together they form a unique fingerprint.
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Keyphrases
Labor Mobility
100%
Contextual Embeddings
100%
Move Prediction
100%
Career Path
50%
Two-source
25%
Profile Information
25%
Human Resources
25%
Granularity
25%
Labor Market
25%
Job Titles
25%
Large-scale Experiments
25%
Macro Level
25%
New Norm
25%
Resource Reallocation
25%
Joint Learning
25%
Context Representation
25%
Digital Traces
25%
Long Short-term Memory Network
25%
Learning Latent Representations
25%
Context Matching
25%
Predictive Signals
25%
Employee Skills
25%
Long Short-term Memory Model
25%
Linkedln
25%
Signaling Profile
25%
Path Mining
25%
Social Sciences
Occupational Career
100%
Labor Mobility
80%
Micro Level
40%
Short-Term Memory
40%
Human Resources
20%
Labor Market
20%
Macro Level
20%
Memory Model
20%
Job Title
20%