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By Gjergji Kasneci, Dean Prof, Dr. Joachim Weickert, Prof Dr. -ing, Gerhard Weikum, Second Reviewer, Prof Dr, Jens Dittrich and Dr. Ralf Schenkel

Abstract

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. In this realm, as a first contribution of this thesis, we present NAGA (Not Another Google Answer), a new semantic search engine. NAGA provides an expressive, graph-based query language that enables queries with entities and relationships. The results are retrieved based on subgraph matching techniques and ranked by means of a statistical ranking model. As a second contribution, we present STAR (Steiner Tree Approximation in Relationship Graphs), an efficient technique for finding “close ” relations (i.e., compact connections) between k( ≥ 2) entities of interest in large entity-relationship graphs. Our third contribution is MING (Mining Informative Graphs). MING is an efficient method for retrieving “informative ” subgraphs for k( ≥ 2) entities of interest from an entity-relationship graph. Intuitively, these would be subgraphs that ca

Year: 2014
OAI identifier: oai:CiteSeerX.psu:10.1.1.466.8445
Provided by: CiteSeerX
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