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Predicting Information Retrieval Performance (Synthesis Lectures on Information Concepts, Retrieval, and Services) - Tapa blanda
Sinopsis
Information Retrieval performance measures are usually retrospective in nature, representing the effectiveness of an experimental process. However, in the sciences, phenomena may be predicted, given parameter values of the system. After developing a measure that can be applied retrospectively or can be predicted, performance of a system using a single term can be predicted given several different types of probabilistic distributions. Information Retrieval performance can be predicted with multiple terms, where statistical dependence between terms exists and is understood. These predictive models may be applied to realistic problems, and then the results may be used to validate the accuracy of the methods used. The application of metadata or index labels can be used to determine whether or not these features should be used in particular cases. Linguistic information, such as part-of-speech tag information, can increase the discrimination value of existing terminology and can be studied predictively.
This work provides methods for measuring performance that may be used predictively. Means of predicting these performance measures are provided, both for the simple case of a single term in the query and for multiple terms. Methods of applying these formulae are also suggested.
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Acerca del autor
Robert Losee has been a professor at the University of North Carolina at Chapel Hills School of Information and Library Science since 1986, after receiving a Ph.D. from the University of Chicago. He has taught courses in Information Retrieval, including an introductory graduate course, and an advanced Artificial Intelligence for Information Retrieval course. He has also taught courses in Information Theory, including a doctoral seminar in the area. His most recent monograph is Information from Processes: About the Nature of Information Creation, Use, and Representation (Springer, 2012).
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- EditorialSpringer
- Año de publicación2018
- ISBN 10 3031011899
- ISBN 13 9783031011894
- EncuadernaciónTapa blanda
- IdiomaInglés
- Número de páginas80
- Contacto del fabricanteno disponible
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Predicting Information Retrieval Performance (Synthesis Lectures on Information Concepts, Retrieval, and Services)
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Predicting Information Retrieval Performance
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Springer International Publishing Dez 2018, 2018
ISBN 10: 3031011899
ISBN 13: 9783031011894
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Information Retrieval performance measures are usually retrospective in nature, representing the effectiveness of an experimental process. However, in the sciences, phenomena may be predicted, given parameter values of the system. After developing a measure that can be applied retrospectively or can be predicted, performance of a system using a single term can be predicted given several different types of probabilistic distributions. Information Retrieval performance can be predicted with multiple terms, where statistical dependence between terms exists and is understood. These predictive models may be applied to realistic problems, and then the results may be used to validate the accuracy of the methods used. The application of metadata or index labels can be used to determine whether or not these features should be used in particular cases. Linguistic information, such as part-of-speech tag information, can increase the discrimination value of existing terminology and can be studied predictively.This work provides methods for measuring performance that may be used predictively. Means of predicting these performance measures are provided, both for the simple case of a single term in the query and for multiple terms. Methods of applying these formulae are also suggested. 80 pp. Englisch. Nº de ref. del artículo: 9783031011894
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Predicting Information Retrieval Performance
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Springer International Publishing, 2018
ISBN 10: 3031011899
ISBN 13: 9783031011894
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Information Retrieval performance measures are usually retrospective in nature, representing the effectiveness of an experimental process. However, in the sciences, phenomena may be predicted, given parameter values of the system. After developing a measure that can be applied retrospectively or can be predicted, performance of a system using a single term can be predicted given several different types of probabilistic distributions. Information Retrieval performance can be predicted with multiple terms, where statistical dependence between terms exists and is understood. These predictive models may be applied to realistic problems, and then the results may be used to validate the accuracy of the methods used. The application of metadata or index labels can be used to determine whether or not these features should be used in particular cases. Linguistic information, such as part-of-speech tag information, can increase the discrimination value of existing terminology and can be studied predictively.This work provides methods for measuring performance that may be used predictively. Means of predicting these performance measures are provided, both for the simple case of a single term in the query and for multiple terms. Methods of applying these formulae are also suggested. Nº de ref. del artículo: 9783031011894
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Predicting Information Retrieval Performance (Synthesis Lectures on Information Concepts, Retrieval, and Services)
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Predicting Information Retrieval Performance
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Predicting Information Retrieval Performance
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ISBN 10: 3031011899
ISBN 13: 9783031011894
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Information Retrieval performance measures are usually retrospective in nature, representing the effectiveness of an experimental process. However, in the sciences, phenomena may be predicted, given parameter values of the system. After developing a meas. Nº de ref. del artículo: 608129430
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Predicting Information Retrieval Performance
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Predicting Information Retrieval Performance
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Predicting Information Retrieval Performance (Synthesis Lectures on Information Concepts, Retrieval, and Services)
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