Linked Data usage is still heavily dependent on 1) the familiarity of end users with the RDF data model and its query language, SPARQL, and (2) knowledge about available datasets and their contents. Intelligent keyword search over Linked Data is currently being investigated as a means to overcome these barriers to entry in a number of different approaches, including semantic search engines and the automatic conversion of natural language questions into structured queries. This paper addresses the specific challenge of mapping keywords to Linked Data resources, and proposes exploiting the graph
structure within Linked Data in order to determine which properties between resources are useful to discover, or directly express, semantic similarity.

Keywords: Natural language queries, Automatic query expansion, Information Retrieval (IR), Keyword expansion, Semantic similarity
Author: Augenstein, Isabelle
Date created: 2013-01-01 05:00:00.000
Time required: P25M
Educational use: instruction
Educational audience: student
Interactivity type: expositive

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