S3K: seeking statement-supporting top-K witnesses

Traditional information retrieval techniques based on keyword search help to identify a ranked set of relevant documents, which often contains many documents in the top ranks that do not meet the user’s intention. By considering the semantics of the keywords and their relationships, both precision and recall can be improved. Using an ontology and mapping keywords to entities/concepts and identifying the relationship between them that the user is interested in, allows for retrieving documents that actually meet the user’s intention. In this paper, we present a framework that enables semantic-aware document retrieval. User queries are mapped to semantic statements based on entities and their relationships. The framework searches for documents expressing these statements in different variations, e.g., synonymous names for entities or different textual expressions for relations between them. The size of potential result sets makes ranking documents according to their relevance to the ...

• Type: Journal
• Year: 2011
• Where: CIKM
• Authors: Steffen Metzger, Shady Elbassuoni, Katja Hose, Ralf Schenkel
• Keywords: CIKM 2011, Information Retrieval Techniques, Information Technology, Statistical Language Models, Traditional Information Retrieval