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Transfer Learning for Item Recommendations and Knowledge Graph Completion in Item Related Domains via A Co-Factorization Model
Published on Jul 10, 2018744 Views
With the popularity of Knowledge Graphs (KGs) in recent years, there have been many studies leveraging the abundant background knowledge available in KGs for the task of item recommendations. However,
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Transfer Learning for Item Recommendations and Knowledge Graph Completion in Item Related Domains via a Co-Factorization Model 00:00
Contents 00:21
Recommender Systems (RecSys) 00:44
RecSys Approaches 01:05
Linked Open Data (LOD) 02:12
Semantics-Aware RecSys - 103:01
Semantics-Aware RecSys - 204:45
Item rec. and KG completion tasks 06:09
Item rec. and KG completion approaches - 106:54
Item rec. and KG completion approaches - 208:55
Transfer Learning via Co-Factorization Model - 109:18
Transfer Learning via Co-Factorization Model - 210:08
Experiment - Datasets 11:08
Experiment - Training & Test Sets11:38
Experiment - Training & Test Sets11:40
Experiment - Evaluation Metrics12:31
Experiment - Compared Methods12:58
Results: Movielens - 114:08
Results: Movielens - 214:48
Results: Movielens - 315:17
Summary15:42
thank you for your attention! and questions17:53