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Synopsis
Search has become ubiquitous mainly because of its usage simplicity. Search has made great strides in making information gathering relatively easy and without a learning curve. Question answering services/communities (termed CQA services or Q/A networks; e.g., Yahoo! Answers, Stack Overflow) have come about in the last decade as yet another way to search. Here the intent is to obtain good/high quality answers (from users with different levels of expertise) for a question when posed, or to retrieve answers from an archived Q/A repository. To make use of these services (and archives) effectively as an alternative to search, it is imperative that we develop a framework including techniques and algorithms for identifying quality of answers as well as the expertise of users answering questions. Finding answer quality is critical for archived data sets for accessing their value as stored repositories to answer questions. Meanwhile, determining the expertise of users is extremely important (and more challenging) for routing queries in real-time which is very important to these Q/A services – both paid and free.
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About the Author
Yuanzhe Cai received his Bachelor of Engineering degree in Computer Science and Engineering from Xidian university in 2005. He received his Masters of Science degree in Computer Science from Renmin University, in July 2008. He received his Doctor of Philosophy in Computer Science and Engineering from The University of Texas at Arlington in 2014.
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Inferring Answer and Answerer Expertise in Question Answer Community
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LAP LAMBERT Academic Publishing Jul 2014, 2014
ISBN 10: 3659576263
ISBN 13: 9783659576263
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Search has become ubiquitous mainly because of its usage simplicity. Search has made great strides in making information gathering relatively easy and without a learning curve. Question answering services/communities (termed CQA services or Q/A networks; e.g., Yahoo! Answers, Stack Overflow) have come about in the last decade as yet another way to search. Here the intent is to obtain good/high quality answers (from users with different levels of expertise) for a question when posed, or to retrieve answers from an archived Q/A repository. To make use of these services (and archives) effectively as an alternative to search, it is imperative that we develop a framework including techniques and algorithms for identifying quality of answers as well as the expertise of users answering questions. Finding answer quality is critical for archived data sets for accessing their value as stored repositories to answer questions. Meanwhile, determining the expertise of users is extremely important (and more challenging) for routing queries in real-time which is very important to these Q/A services - both paid and free. 192 pp. Englisch. Seller Inventory # 9783659576263
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Inferring Answer and Answerer Expertise in Question Answer Community
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LAP LAMBERT Academic Publishing, 2014
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Cai YuanzheYuanzhe Cai received his Bachelor of Engineering degree in Computer Science and Engineering from Xidian university in 2005. He received his Masters of Science degree in Computer Science from Renmin University, in July 2008. Seller Inventory # 5165965
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Inferring Answer and Answerer Expertise in Question Answer Community
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Inferring Answer and Answerer Expertise in Question Answer Community
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Inferring Answer and Answerer Expertise in Question Answer Community
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Inferring Answer and Answerer Expertise in Question Answer Community
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Taschenbuch. Condition: Neu. Inferring Answer and Answerer Expertise in Question Answer Community | Yuanzhe Cai | Taschenbuch | 192 S. | Englisch | 2014 | LAP LAMBERT Academic Publishing | EAN 9783659576263 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 105175951
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Inferring Answer and Answerer Expertise in Question Answer Community
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LAP LAMBERT Academic Publishing Jul 2014, 2014
ISBN 10: 3659576263
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Search has become ubiquitous mainly because of its usage simplicity. Search has made great strides in making information gathering relatively easy and without a learning curve. Question answering services/communities (termed CQA services or Q/A networks; e.g., Yahoo! Answers, Stack Overflow) have come about in the last decade as yet another way to search. Here the intent is to obtain good/high quality answers (from users with different levels of expertise) for a question when posed, or to retrieve answers from an archived Q/A repository. To make use of these services (and archives) effectively as an alternative to search, it is imperative that we develop a framework including techniques and algorithms for identifying quality of answers as well as the expertise of users answering questions. Finding answer quality is critical for archived data sets for accessing their value as stored repositories to answer questions. Meanwhile, determining the expertise of users is extremely important (and more challenging) for routing queries in real-time which is very important to these Q/A services - both paid and free.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 192 pp. Englisch. Seller Inventory # 9783659576263
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Inferring Answer and Answerer Expertise in Question Answer Community
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LAP LAMBERT Academic Publishing, 2014
ISBN 10: 3659576263
ISBN 13: 9783659576263
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Search has become ubiquitous mainly because of its usage simplicity. Search has made great strides in making information gathering relatively easy and without a learning curve. Question answering services/communities (termed CQA services or Q/A networks; e.g., Yahoo! Answers, Stack Overflow) have come about in the last decade as yet another way to search. Here the intent is to obtain good/high quality answers (from users with different levels of expertise) for a question when posed, or to retrieve answers from an archived Q/A repository. To make use of these services (and archives) effectively as an alternative to search, it is imperative that we develop a framework including techniques and algorithms for identifying quality of answers as well as the expertise of users answering questions. Finding answer quality is critical for archived data sets for accessing their value as stored repositories to answer questions. Meanwhile, determining the expertise of users is extremely important (and more challenging) for routing queries in real-time which is very important to these Q/A services - both paid and free. Seller Inventory # 9783659576263