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Using Ontology-based Data Summarization to Develop Semantics-aware Recommender Systems
Published on Jul 10, 2018730 Views
In the current information-centric era, recommender systems are gaining momentum as tools able to assist users in daily decision-making tasks. They may exploit users’ past behavior combined with side/
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Chapter list
Using Ontology-based Data Summarization to Develop Semantics-aware Recommender Systems 00:00
Outline - 100:22
Outline - 200:24
Recommender Systems00:47
Why do we need content? - 100:59
Why do we need content? - 201:23
Why do we need content? - 301:57
Why do we need content? - 402:17
Content-based Semantic Recommendations - 102:18
Content-based Semantic Recommendations - 202:45
The Feature Selection Problem04:49
Ontology-based Data Summarization vs. Statistical Technique07:10
Outline - 308:04
Ontology-driven Knowledge Graph Profiling with ABSTAT - 108:07
ABSTAT: Cardinality Descriptors09:41
Untitled10:01
ABSTAT: Cardinality Descriptors - 310:07
ABSTAT: Cardinality Descriptors - 410:14
ABSTAT: Cardinality Descriptors - 510:20
ABSTAT: Cardinality Descriptors - 610:29
ABSTAT: Cardinality Descriptors - 710:31
ABSTAT: Cardinality Descriptors - 810:32
Cardinality Descriptors for Feature Selection - 110:51
Cardinality Descriptors for Feature Selection - 211:04
Untitled11:48
Feature Selection with ABSTAT - 112:26
Feature Selection with ABSTAT - 213:14
Feature Selection with IG13:24
Feature Selection with IG: preprocessing14:07
Outline - 514:28
Experimental Settings: Recommendation Method - 114:28
Experimental Settings: Recommendation Method - 214:49
Experimental Setting: Datasets & Measures - 114:52
Experimental Settings: dbo vs. dbp properties15:29
Experimental Setting: Datasets & Measures - 216:39
MovieLens16:48
LastFM17:19
The library thing18:00
Outline - 618:44
Conclusion & future work18:45
Ontology-driven Knowledge Graph Profiling with ABSTAT - 220:51