Swoogle: a search and metadata engine for the semantic web
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Falcons: searching and browsing entities on the semantic web
Proceedings of the 17th international conference on World Wide Web
PANTO: A Portable Natural Language Interface to Ontologies
ESWC '07 Proceedings of the 4th European conference on The Semantic Web: Research and Applications
A Visual Approach to Semantic Query Design Using a Web-Based Graphical Query Designer
EKAW '08 Proceedings of the 16th international conference on Knowledge Engineering: Practice and Patterns
Query-by-example: a data base language
IBM Systems Journal
How useful are natural language interfaces to the semantic web for casual end-users?
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
Sindice.com: weaving the open linked data
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
PowerAqua: fishing the semantic web
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
ESWC'10 Proceedings of the 7th international conference on The Semantic Web: research and Applications - Volume Part I
Facet graphs: complex semantic querying made easy
ESWC'10 Proceedings of the 7th international conference on The Semantic Web: research and Applications - Volume Part I
Allowing end users to query graph-based knowledge bases
EKAW'12 Proceedings of the 18th international conference on Knowledge Engineering and Knowledge Management
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Most Semantic Web query interfaces let the user give an abstract specification of the desired results (perhaps using facets, or a natural language query.) We introduce the Smeagol visual query interface which, by contrast, guides the user from a specific example to a general result set. Users begin the query process with navigation and exploration activities, building a concrete subgraph of interest from the larger data set. They then generalize this subgraph to find other subgraphs similar in some way to the one identified. Among other advantages, this approach also lends itself quite naturally to querying on instance-based data; i.e., triples in which the predicate is not part of a defined ontology. We provide an analysis of this specific-to-general approach, contrasting it with existing systems. We also present the results of a usability experiment comparing novices' use of Smeagol with that of a standard Linked Data browser.