Novel Triple Extraction: Unterschied zwischen den Versionen
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He9318 (Diskussion | Beiträge) (Die Seite wurde neu angelegt: „{{DataOrTool |Forschungsgruppe=Web Science und Wissensmanagement |name=Novel Triple Extraction |contact persons=Michael Färber; |long description EN=In media mo…“) |
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|Forschungsgruppe=Web Science und Wissensmanagement | |Forschungsgruppe=Web Science und Wissensmanagement | ||
|name=Novel Triple Extraction | |name=Novel Triple Extraction | ||
| − | |contact persons=Michael Färber; | + | |contact persons=Michael Färber; |
|long description EN=In media monitoring users have a clearly defined information need to find so far unknown statements regarding certain entities or relations mentioned in natural-language text. However, commonly used keyword-based search technologies are focused on finding relevant documents and cannot judge the novelty of statements contained in the text. In this work, we propose a new semantic novelty measure that allows to retrieve statements, which are both novel and relevant, from natural-language sentences in news articles. Relevance is defined by a semantic query of the user, while novelty is ensured by checking whether the extracted statements are related, but non-existing in a knowledge base containing the currently known facts. Our evaluation performed on English news texts and on CrunchBase as the knowledge base demonstrates the effectiveness, unique capabilities and future challenges of this novel approach to novelty. | |long description EN=In media monitoring users have a clearly defined information need to find so far unknown statements regarding certain entities or relations mentioned in natural-language text. However, commonly used keyword-based search technologies are focused on finding relevant documents and cannot judge the novelty of statements contained in the text. In this work, we propose a new semantic novelty measure that allows to retrieve statements, which are both novel and relevant, from natural-language sentences in news articles. Relevance is defined by a semantic query of the user, while novelty is ensured by checking whether the extracted statements are related, but non-existing in a knowledge base containing the currently known facts. Our evaluation performed on English news texts and on CrunchBase as the knowledge base demonstrates the effectiveness, unique capabilities and future challenges of this novel approach to novelty. | ||
| − | |projects=SUITE;SyncTech; | + | |projects=SUITE;SyncTech; |
|dataOrTool=Tool | |dataOrTool=Tool | ||
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| − | See http://people.aifb.kit.edu/mfa/novel-triple-extraction | + | See http://people.aifb.kit.edu/mfa/novel-triple-extraction/. |
Version vom 20. Januar 2017, 16:40 Uhr
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Novel Triple Extraction |
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See http://people.aifb.kit.edu/mfa/novel-triple-extraction/.