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… mais…
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… mais…
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… mais…
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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(*) Livro esgotado significa que o livro não está disponível em qualquer uma das plataformas associadas 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… mais…
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… mais…
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. Custos de envio:, 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… mais…
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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Dados detalhados do livro - Enhanced Question Classification with Optimal Combination of Features
EAN (ISBN-13): 9783847331346 ISBN (ISBN-10): 3847331345 Livro de capa dura Livro de bolso Editor/Editora: AV Akademikerverlag GmbH & Co. KG.
Livro na base de dados desde 2007-09-23T02:29:12+01:00 (Lisbon) Página de detalhes modificada pela última vez em 2019-04-25T09:10:12+01:00 (Lisbon) Número ISBN/EAN: 9783847331346
Número ISBN - Ortografia alternativa: 3-8473-3134-5, 978-3-8473-3134-6
