An important component of question answering systems is question classification. The task of question classification is to predict the entity type of the answer of a natural language ques… Más…
An important component of question answering systems is question classification. The task of question classification is to predict the entity type of the answer of a natural language question. For example for the given question of "what is the capital of the Netherlands?", the task of question classification is to classify this question to the category "city" since the answer type of this question is of type "city". Question classification is typically done using machine learning techniques. Different lexical, syntactical and semantic features can be extracted from a question. In this work we introduce two new semantic features which improve the accuracy of classification. Furthermore, we developed a weighed approach to optimally combine different features. We also applied Latent Semantic Analysis (LSA) technique to reduce the large feature space of questions to a much smaller and efficient feature space. Our experimental results show that our approach is successful. Buch / Mathematik, Naturwissenschaft & Technik / Informatik & EDV / Informatik<
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An important component of question answering systems is question classification. The task of question classification is to predict the entity type of the answer of a natural language ques… Más…
An important component of question answering systems is question classification. The task of question classification is to predict the entity type of the answer of a natural language question. For example for the given question of "what is the capital of the Netherlands?", the task of question classification is to classify this question to the category "city" since the answer type of this question is of type "city". Question classification is typically done using machine learning techniques. Different lexical, syntactical and semantic features can be extracted from a question. In this work we introduce two new semantic features which improve the accuracy of classification. Furthermore, we developed a weighed approach to optimally combine different features. We also applied Latent Semantic Analysis (LSA) technique to reduce the large feature space of questions to a much smaller and efficient feature space. Our experimental results show that our approach is successful. Bücher / Naturwissenschaften, Medizin, Informatik & Technik / Informatik & EDV / Informatik<
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Babak Loni,Paperback, English-language edition,Pub by AV Akademikerverlag GmbH & Co. KG. Books Books ~~ Computers~~ Information Technology Enhanced-Question-Classification-with-Optimal-Co… Más…
Babak Loni,Paperback, English-language edition,Pub by AV Akademikerverlag GmbH & Co. KG. Books Books ~~ Computers~~ Information Technology Enhanced-Question-Classification-with-Optimal-Combination-of-Features~~Babak-Loni AV Akademikerverlag GmbH & Co. KG.<
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A new approach on automated question answering systems - Buch, gebundene Ausgabe, 88 S., Beilagen: Paperback, Erschienen: 2012 LAP Lambert Academic Publishing
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(*) Libro agotado significa que este título no está disponible por el momento en alguna de las plataformas asociadas que buscamos.
An important component of question answering systems is question classification. The task of question classification is to predict the entity type of the answer of a natural language ques… Más…
An important component of question answering systems is question classification. The task of question classification is to predict the entity type of the answer of a natural language question. For example for the given question of "what is the capital of the Netherlands?", the task of question classification is to classify this question to the category "city" since the answer type of this question is of type "city". Question classification is typically done using machine learning techniques. Different lexical, syntactical and semantic features can be extracted from a question. In this work we introduce two new semantic features which improve the accuracy of classification. Furthermore, we developed a weighed approach to optimally combine different features. We also applied Latent Semantic Analysis (LSA) technique to reduce the large feature space of questions to a much smaller and efficient feature space. Our experimental results show that our approach is successful. Buch / Mathematik, Naturwissenschaft & Technik / Informatik & EDV / Informatik<
- Nr. 35910234 Gastos de envío:, , zzgl. Versandkosten, más gastos de envío
An important component of question answering systems is question classification. The task of question classification is to predict the entity type of the answer of a natural language ques… Más…
An important component of question answering systems is question classification. The task of question classification is to predict the entity type of the answer of a natural language question. For example for the given question of "what is the capital of the Netherlands?", the task of question classification is to classify this question to the category "city" since the answer type of this question is of type "city". Question classification is typically done using machine learning techniques. Different lexical, syntactical and semantic features can be extracted from a question. In this work we introduce two new semantic features which improve the accuracy of classification. Furthermore, we developed a weighed approach to optimally combine different features. We also applied Latent Semantic Analysis (LSA) technique to reduce the large feature space of questions to a much smaller and efficient feature space. Our experimental results show that our approach is successful. Bücher / Naturwissenschaften, Medizin, Informatik & Technik / Informatik & EDV / Informatik<
Nr. Gastos de envío:, Lieferzeit: 11 Tage, DE. (EUR 0.00)
Babak Loni,Paperback, English-language edition,Pub by AV Akademikerverlag GmbH & Co. KG. Books Books ~~ Computers~~ Information Technology Enhanced-Question-Classification-with-Optimal-Co… Más…
Babak Loni,Paperback, English-language edition,Pub by AV Akademikerverlag GmbH & Co. KG. Books Books ~~ Computers~~ Information Technology Enhanced-Question-Classification-with-Optimal-Combination-of-Features~~Babak-Loni AV Akademikerverlag GmbH & Co. KG.<
Free Shipping on eligible orders over $25 Gastos de envío:más gastos de envío
A new approach on automated question answering systems - Buch, gebundene Ausgabe, 88 S., Beilagen: Paperback, Erschienen: 2012 LAP Lambert Academic Publishing
Gastos de envío:Versandkostenfrei innerhalb der BRD, más gastos de envío
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Detalles del libro - Enhanced Question Classification with Optimal Combination of Features
EAN (ISBN-13): 9783847331346 ISBN (ISBN-10): 3847331345 Tapa dura Tapa blanda Editorial: AV Akademikerverlag GmbH & Co. KG.
Libro en la base de datos desde 2007-09-22T20:29:12-05:00 (Mexico City) Página de detalles modificada por última vez el 2019-04-25T03:10:12-05:00 (Mexico City) ISBN/EAN: 3847331345
ISBN - escritura alterna: 3-8473-3134-5, 978-3-8473-3134-6