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Structural Summarization of Semantic Graphs
Published on Jul 10, 2018819 Views
RDF graphs comprise highly complex data, both from a structural and from a semantic perspective. This makes them hard to discover and learn, and hinders their usability. An elegant basis for summarizi
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Chapter list
Structural Summarization of Semantic Graphs00:00
Outline00:20
Part I Motivation: data discovery in RDF graphs02:12
Big Data needs semantics02:19
RDF graph discovery03:22
RDF summaries04:08
RDF summaries05:50
RDF graphs are often structurally heterogeneous06:42
RDF graphs are often structurally heterogeneous07:16
Our goal08:42
The Resource Description Framework (RDF)09:34
RDF Schema - 109:56
RDF Schema - 210:12
RDF Schema - 310:18
RDF Schema - 410:20
Open-world assumption and RDF entailment - 110:29
Open-world assumption and RDF entailment - 210:37
Open-world assumption and RDF entailment - 310:53
The semantics of an RDF graph G is its saturation G ∞11:14
Part III RDF summarization12:19
RDF summaries12:23
A summary of DBLP data13:43
A summary of geographic data14:32
Summarization principle: quotient graphs15:34
Common graph quotients: bisimilarity [HHK95]19:01
What about type and schema triples? - 123:06
What about type and schema triples? - 223:19
RDF equivalence relation and RDF summaries24:46
Summarization through an RDF equivalence relation27:06
Recap28:22
RDF node equivalence based on property cliques28:50
RDF node equivalence based on property cliques30:19
Weak clique-based summaries - 131:55
Weak clique-based summaries - 233:57
Weak clique-based summaries - 334:44
Strong clique-based summaries35:55
Which role should node types play in summarization? - 137:37
Adding types after data summarization38:42
Giving proeminence to types - 138:53
Giving proeminence to types - 240:11
RDF summaries outline - 140:13
RDF summaries outline - 240:29
Relations between RDF summaries [CGM17b]40:45
Summary size comparison (more in [CGM17b])40:52
Summarizing G ∞ - 141:49
Summarizing G ∞ - 243:06
Shortcut example: G/≡ W43:27
Shortcut counter-example: G/≡ TW43:31
Summarization algorithms45:13
Example: weak incremental summarization (1) - 146:10
Example: weak incremental summarization (1) - 246:25
Example: weak incremental summarization (1) - 346:27
Example: weak incremental summarization (1) - 447:23
Example: weak incremental summarization (2) 47:41
Example: weak incremental summarization (3)47:53
Example: weak incremental summarization (end)47:56
Algorithm scale-up48:34
Summary-enabled LOD cloud exploration [PGA+18]48:42
Conclusion - The need for RDF graph discovery tools49:11
Ongoing and future work50:16
thank you for attwntion and questions51:39