Predicting Information Retrieval Performance (Synthesis Lectures on Information Concepts, Retrieval, and Services)

Losee, Robert M.

ISBN 10: 3031011899 ISBN 13: 9783031011894

Editorial: Springer, 2018

Nuevos Encuadernaci�n de tapa blanda

Librer�a: Ria Christie Collections, Uxbridge, Reino Unido Calificaci�n del vendedor: 5 de 5 estrellas

Vendedor de AbeBooks desde 25 de marzo de 2015

Este art�culo en concreto ya no est� disponible.

Ver los art�culos de este vendedor Crear una petici�n para art�culos similares

Ver todos los ejemplares de este libro

Descripci�n

In English. N� de ref. del art�culo ria9783031011894_new

Denunciar este art�culo

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.

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).

"Sobre este t�tulo" puede pertenecer a otra edici�n de este libro.

Detalles bibliogr�ficos

T�tulo: Predicting Information Retrieval Performance...
Editorial: Springer
A�o de publicaci�n: 2018
Encuadernaci�n: Encuadernaci�n de tapa blanda
Condici�n: New

Los mejores resultados en AbeBooks

Imagen del vendedor

Predicting Information Retrieval Performance

Losee, Robert M.

Publicado por Springer, Berlin|Springer International Publishing|Morgan & Claypool|Springer, 2018

ISBN 10: 3031011899 ISBN 13: 9783031011894

Nuevo Tapa blanda

Impresi�n bajo demanda

Librería: moluna, Greven, Alemania

Calificaci�n del vendedor: 4 de 5 estrellas

Condici�n: 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. N� de ref. del art�culo: 608129430

Contactar al vendedor

Comprar nuevo

EUR 32,69

EUR 48,99 shipping
Se env�a de Alemania a Estados Unidos de America

Cantidad disponible: M�s de 20 disponibles

A�adir al carrito

Imagen del vendedor

M�s im�genes

Predicting Information Retrieval Performance

Robert M. Losee

Publicado por Springer International Publishing, 2018

ISBN 10: 3031011899 ISBN 13: 9783031011894

Nuevo Taschenbuch

Librería: preigu, Osnabr�ck, Alemania

Calificaci�n del vendedor: 5 de 5 estrellas

Contactar al vendedor

Comprar nuevo

EUR 34,10

EUR 70,00 shipping
Se env�a de Alemania a Estados Unidos de America

Cantidad disponible: 5 disponibles

A�adir al carrito

Imagen de archivo

Predicting Information Retrieval Performance

Losee, Robert M.

Publicado por Springer 2018-12, 2018

ISBN 10: 3031011899 ISBN 13: 9783031011894

Nuevo PF

Librería: Chiron Media, Wallingford, Reino Unido

Calificaci�n del vendedor: 5 de 5 estrellas

PF. Condici�n: New. N� de ref. del art�culo: 6666-IUK-9783031011894

Contactar al vendedor

Comprar nuevo

EUR 34,76

EUR 17,69 shipping
Se env�a de Reino Unido a Estados Unidos de America

Cantidad disponible: 10 disponibles

A�adir al carrito

Imagen del vendedor

Predicting Information Retrieval Performance

Robert M. Losee

Publicado por Springer International Publishing, 2018

ISBN 10: 3031011899 ISBN 13: 9783031011894

Nuevo Taschenbuch

Librería: AHA-BUCH GmbH, Einbeck, Alemania

Calificaci�n del vendedor: 5 de 5 estrellas

Taschenbuch. Condici�n: 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. N� de ref. del art�culo: 9783031011894

Contactar al vendedor

Comprar nuevo

EUR 35,30

EUR 60,85 shipping
Se env�a de Alemania a Estados Unidos de America

Cantidad disponible: 1 disponibles

A�adir al carrito

Imagen del vendedor

Predicting Information Retrieval Performance

Robert M. Losee

Publicado por Springer International Publishing, Springer International Publishing Dez 2018, 2018

ISBN 10: 3031011899 ISBN 13: 9783031011894

Nuevo Taschenbuch

Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania

Calificaci�n del vendedor: 5 de 5 estrellas

Taschenbuch. Condici�n: Neu. 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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 80 pp. Englisch. N� de ref. del art�culo: 9783031011894

Contactar al vendedor

Comprar nuevo

EUR 35,30

EUR 60,00 shipping
Se env�a de Alemania a Estados Unidos de America

Cantidad disponible: 2 disponibles

A�adir al carrito

Imagen del vendedor

Predicting Information Retrieval Performance

Robert M. Losee

Publicado por Springer International Publishing Dez 2018, 2018

ISBN 10: 3031011899 ISBN 13: 9783031011894

Nuevo Taschenbuch

Impresi�n bajo demanda

Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania

Calificaci�n del vendedor: 5 de 5 estrellas

Taschenbuch. Condici�n: 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. N� de ref. del art�culo: 9783031011894

Contactar al vendedor