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A Blended Deep Learning Approach for Predicting User Intended Actions
Fei Tan
,
Zhi Wei
, Jun He
, Xiang Wu
, Bo Peng
, Haoran Liu
, Zhenyu Yan
Research output
:
Chapter in Book/Report/Conference proceeding
›
Conference contribution
17
Scopus citations
Overview
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Dive into the research topics of 'A Blended Deep Learning Approach for Predicting User Intended Actions'. Together they form a unique fingerprint.
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Keyphrases
Deep Learning Methods
100%
Attrition
100%
Intended Action
100%
Predictive Modeling
50%
User Log
50%
Modeling Strategy
25%
Proactive Measures
25%
Popular
25%
User Intention
25%
User Profile
25%
Typical User
25%
Business Practices
25%
User Usage
25%
Inherent Drawbacks
25%
Adobe
25%
Subsequent Learning
25%
Interpretation Strategies
25%
Public Data Repositories
25%
Business Outcomes
25%
SNaPshot Method
25%
Business Growth
25%
Multi-path Learning
25%
Visualization Strategy
25%
End-to-end Learning Scheme
25%
Learning Procedure
25%
Computer Science
Deep Learning
100%
Learning Approach
100%
Intended Action
100%
Activity Log
50%
Data Repository
25%
Multipath
25%
Conventional Method
25%
Learning Scheme
25%
Business Growth
25%
Business Practice
25%