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|Abstract=In this paper, we propose a new approach to entity-based information retrieval by exploiting semantic annotations of documents. With the increased availability of structured knowledge bases and semantic annotation techniques, we can capture documents and queries at their semantic level to avoid the high semantic ambiguity of terms and to bridge the language barrier between queries and documents. Based on various semantic interpretations, users can refine the queries to match their intents. By exploiting the semantics of entities and their relations in knowledge bases, we propose a novel ranking scheme to address the information needs of users. | |Abstract=In this paper, we propose a new approach to entity-based information retrieval by exploiting semantic annotations of documents. With the increased availability of structured knowledge bases and semantic annotation techniques, we can capture documents and queries at their semantic level to avoid the high semantic ambiguity of terms and to bridge the language barrier between queries and documents. Based on various semantic interpretations, users can refine the queries to match their intents. By exploiting the semantics of entities and their relations in knowledge bases, we propose a novel ranking scheme to address the information needs of users. | ||
| + | |Download=Retrieval.pdf, | ||
|Projekt=Software Campus, SyncTech, XLiMe, XLike | |Projekt=Software Campus, SyncTech, XLiMe, XLike | ||
|Forschungsgruppe=Wissensmanagement | |Forschungsgruppe=Wissensmanagement | ||
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Version vom 16. März 2015, 02:07 Uhr
Exploiting Semantic Annotations for Entity-based Information Retrieval
Exploiting Semantic Annotations for Entity-based Information Retrieval
Published: 2014
Oktober
Buchtitel: Proceedings of the ISWC 2014 Posters & Demonstrations Track
Verlag: CEUR-WS
Referierte Veröffentlichung
BibTeX
Kurzfassung
In this paper, we propose a new approach to entity-based information retrieval by exploiting semantic annotations of documents. With the increased availability of structured knowledge bases and semantic annotation techniques, we can capture documents and queries at their semantic level to avoid the high semantic ambiguity of terms and to bridge the language barrier between queries and documents. Based on various semantic interpretations, users can refine the queries to match their intents. By exploiting the semantics of entities and their relations in knowledge bases, we propose a novel ranking scheme to address the information needs of users.
Download: Media:Retrieval.pdf
Software Campus, SyncTech, XLiMe, XLike