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SPARQL Query Verbalization for Explaining Semantic Search Engine Queries
Published on Jul 30, 20142182 Views
In this paper we introduce Spartiqulation, a system that translates SPARQL queries into English text. Our aim is to allow casual end users of semantic applications with limited to no expertise in the
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Chapter list
SPARQL Query Verbalization for Explaining Semantic Search Engine Queries00:00
Overview00:20
Motivation (1/2)00:49
Motivation (2/2)02:00
Anatomy of a query verbalization (1/4) - 103:38
Anatomy of a query verbalization (1/4) - 204:41
Anatomy of a query verbalization (1/4) - 304:52
Anatomy of a query verbalization (2/4) - 105:00
Anatomy of a query verbalization (2/4) - 205:10
Anatomy of a query verbalization (2/4) - 305:26
Anatomy of a query verbalization (2/4) - 405:31
Anatomy of a query verbalization (3/4) - 105:49
Anatomy of a query verbalization (3/4) - 205:57
Anatomy of a query verbalization (3/4) - 306:03
Anatomy of a query verbalization (3/4) - 406:09
Anatomy of a query verbalization (4/4) - 106:11
Anatomy of a query verbalization (4/4) - 206:34
Anatomy of a query verbalization (4/4) - 306:39
Main idea06:48
Example – SPARQL query09:11
Example query – graph representation - 109:19
Example query – graph representation - 210:26
Example query – graph representation - 310:33
Example query – graph representation - 410:36
Example query – graph representation - 510:39
Example query – graph representation - 610:45
Example query – graph representation - 710:58
Example query – message rep.11:00
Example – Subject verbalization - 112:06
Example – Subject verbalization - 213:52
Example – Constraint verbalization (1/2)14:06
Example – Constraint verbalization (2/2)15:46
Example – verbalization result - 116:10
Example – verbalization result - 216:22
Evaluation (1/2)16:59
Evaluation (2/2)18:28
Conclusions19:43
Thank you!20:42