Searching and Ranking in Entity-Relationship Graphs
From Web Pages to Knowledge
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The Web bears the potential to become the world's most comprehensive knowledge base. Organizing information from the Web into entity-relationship graph structures could be a first step towards unleashing this potential. In a second step, the inherent semantics of such structures would have to be exploited by expressive search techniques that go beyond today's keyword search paradigm. This work proposes a wide variety of novel search and ranking strategies over data that is organized in entity-relationship graphs. All presented techniques have been implemented as components of the NAGA search e...
The Web bears the potential to become the world's most comprehensive knowledge base. Organizing information from the Web into entity-relationship graph structures could be a first step towards unleashing this potential. In a second step, the inherent semantics of such structures would have to be exploited by expressive search techniques that go beyond today's keyword search paradigm. This work proposes a wide variety of novel search and ranking strategies over data that is organized in entity-relationship graphs. All presented techniques have been implemented as components of the NAGA search engine and published in renowned international conferences. NAGA itself is a fully implemented prototype system and is part of the YAGO-NAGA project.
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