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Gleaning Types for Literals in RDF Triples with Application to Entity Summarization
Published on Jul 28, 20161067 Views
Associating meaning with data in a machine-readable format is at the core of the Semantic Web vision, and typing is one such process. Typing (assigning a class selected from schema) information can be
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Chapter list
Gleaning Types for Literals in RDF Triples with Application to Entity Summarization00:00
Talk Overview00:53
Motivating Facts – Literals and Semantics01:41
Lets Focus on Entity Summarization now ...03:30
Importance of Entities and Summaries04:10
Diversity-Aware Entity Summaries (FACES approach) - Background04:47
Faceted Entity Summary - Example05:35
Information coming from literals???06:46
Typing Literals in RDF Triples for Entity Summarization07:49
Typing DatatypeProperty Values - Example08:43
Why is it Hard?10:31
Focus term identification11:51
Deriving type (class) from head word12:46
Process Flow15:36
Typing Literals Algorithm Outline16:21
Ranking Datatype Property Features16:32
Idea for Ranking17:41
Modified Ranking Equations18:55
Facet Ranking19:57
FACES-E Entity Summary Generation20:47
Type Computation Samples21:41
Evaluation - Type Generation Metrics23:10
Evaluation - Type Generation24:22
Evaluation – Summarization Metrics27:02
Evaluation – FACES-E Summary Generation28:26
Future Work29:59
Questions?32:15