Claudia Exeler

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This paper presents two approaches to semantic search by incorporating Linked Data annotations of documents into a Generalized Vector Space Model. One model exploits taxonomic relationships among entities in documents and queries, while the other model computes term weights based on semantic relationships within a document. We publish an evaluation dataset(More)
Search engines traditionally suffer drawbacks from ambiguities of natural language, which users often solve via query refinement. In contrast to web search, querying document collections of limited size (e.g. blogs, multimedia collections, or libraries) can quickly lead to empty result sets because the wrong choice of keywords may eliminate the only(More)
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