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In recent years we have witnessed tremendous interest and substantial economic exploitation of search technologies. However, the representation of user queries and resource content in existing search appliances is still almost exclusively achieved by simple syntax-based descriptions of the resource content and the information need such as in the predominant keyword-centric paradigm.
On the other hand, recent advances in the field of semantic technologies have resulted in tools and standards that allow for the articulation of domain knowledge in a formal manner at a high level of expressiveness. At the same time, semantic repositories and reasoning engines have advanced to a state where querying and processing of this knowledge can scale to realistic IR scenarios.
As such, semantic technologies are now in a state to provide significant contributions to IR problems. In this context, several challenges arise for Semantic Search systems. These include, among others:
* How can semantic technologies be exploited to capture the information need of the user?
* How can the information need of the user be translated to expressive formal queries without enforcing the user to be capable of handling the difficult query syntax?
* How can expressive resource descriptions be extracted (acquired) from documents (users)?
* How can expressive resource descriptions be stored and queried efficiently on a large scale?
* How can vague information needs and incomplete resource descriptions be handled?
* How can semantic search systems be evaluated and compared with standard IR systems?
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