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Feature selection based multiviewpoint de singh neelam (5 resultados)

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  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2022

    6204740520 / 9786204740522

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    Librería: preigu, Osnabrück, Alemaniapreigu

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    Condición: Nuevo

    EUR 39,45

    Envío por EUR 70,00 
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    Cantidad disponible: 5 disponibles

    Taschenbuch. Condición: Neu. Feature Selection Based on Multiviewpoint And Link Similarity Measure | Document Clustering | Neelam Singh | Taschenbuch | Englisch | 2022 | LAP LAMBERT Academic Publishing | EAN 9786204740522 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Jan 2022, 2022

    6204740520 / 9786204740522

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

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    Condición: Nuevo

    EUR 43,90

    Envío por EUR 23,00 
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    Cantidad disponible: 2 disponibles

    Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -To explore and utilize huge amount of text documents is a major question in the area of information retrieval and text mining. All the methods aiming to find groups of entities utilizes similarity or dissimilarity measure. It is necessary to analyse how similarity measure behave on text documents before developing or modifying a good similarity measure for document clustering to understand the effectiveness of the technique. A similarity function embedded in a criterion function is to a large extent is responsible to analyze the intrinsic structure of the data. If appropriate similarity measures are used with specific clustering technique the efficiency and accuracy of the information discovery task can be enhanced. Use of appropriate measures not only improves the provenance and credit-ability of the retrieved information but also helps to overcome the time and cost complexity of the process. This book focuses on identifying the various similarity measure for Clustering. An imperative method for measuring similarity between text documents is illustrated to cluster the documents using hierarchical clustering and feature selection method using Matlab. 60 pp. Englisch.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2022

    6204740520 / 9786204740522

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    Condición: Nuevo

    EUR 49,63

    Envío por EUR 35,00 
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    Cantidad disponible: 1 disponible

    Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - To explore and utilize huge amount of text documents is a major question in the area of information retrieval and text mining. All the methods aiming to find groups of entities utilizes similarity or dissimilarity measure. It is necessary to analyse how similarity measure behave on text documents before developing or modifying a good similarity measure for document clustering to understand the effectiveness of the technique. A similarity function embedded in a criterion function is to a large extent is responsible to analyze the intrinsic structure of the data. If appropriate similarity measures are used with specific clustering technique the efficiency and accuracy of the information discovery task can be enhanced. Use of appropriate measures not only improves the provenance and credit-ability of the retrieved information but also helps to overcome the time and cost complexity of the process. This book focuses on identifying the various similarity measure for Clustering. An imperative method for measuring similarity between text documents is illustrated to cluster the documents using hierarchical clustering and feature selection method using Matlab.…

  • Idioma: Inglés

    Editorial: LAP Lambert Academic Publishing, 2022

    6204740520 / 9786204740522

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    Librería: moluna, Greven, Alemaniamoluna

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    Condición: Nuevo

    EUR 37,23

    Envío por EUR 48,99 
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    Cantidad disponible: Más de 20 disponibles

    Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. To explore and utilize huge amount of text documents is a major question in the area of information retrieval and text mining. All the methods aiming to find groups of entities utilizes similarity or dissimilarity measure. It is necessary to analyse how sim.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Jan 2022, 2022

    6204740520 / 9786204740522

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    Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

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    Condición: Nuevo

    EUR 43,90

    Envío por EUR 60,00 
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    Cantidad disponible: 1 disponible

    Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -To explore and utilize huge amount of text documents is a major question in the area of information retrieval and text mining. All the methods aiming to find groups of entities utilizes similarity or dissimilarity measure. It is necessary to analyse how similarity measure behave on text documents before developing or modifying a good similarity measure for document clustering to understand the effectiveness of the technique. A similarity function embedded in a criterion function is to a large extent is responsible to analyze the intrinsic structure of the data. If appropriate similarity measures are used with specific clustering technique the efficiency and accuracy of the information discovery task can be enhanced. Use of appropriate measures not only improves the provenance and credit-ability of the retrieved information but also helps to overcome the time and cost complexity of the process. This book focuses on identifying the various similarity measure for Clustering. An imperative method for measuring similarity between text documents is illustrated to cluster the documents using hierarchical clustering and feature selection method using Matlab.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 60 pp. Englisch.…