ISBN: 9786200082763 - identification of significant keywords from gujarati text documents (5 resultados)

ISBN: 
Refinar con la Búsqueda avanzada

Filtrar la búsqueda

  • Libros (5)

  • Nuevo (5)

a

Intervalo de precios personalizado (EUR)

a

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2019

    6200082766 / 9786200082763

    • Tapa blanda

    Librería: preigu, Osnabrück, Alemaniapreigu

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 61,05

    Envío por EUR 70,00 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: 5 disponibles

    Taschenbuch. Condición: Neu. Identification of Significant Keywords from Gujarati Text Documents | Hardik Joshi | Taschenbuch | 164 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9786200082763 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Jun 2019, 2019

    6200082766 / 9786200082763

    • Tapa blanda
    • Impresión bajo demanda

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

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 71,90

    Envío por EUR 23,00 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: 2 disponibles

    Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Information Retrieval(IR) systems are gaining importance due to wide range of applications like recommender systems, search engines, etc., however, most of the IR systems use statistical methods built on top of bag-of-words approach for text retrieval. Graph-of-words approach is an alternative to bag-of-words approach that uses graph theoretic methods to rank keywords and related documents. We represent text documents as graphs whose vertices correspond to the unique terms belonging to the document. The edges represent co-occurrences between the terms. The underlying assumption is that the terms that co-occur have some sort of semantic relationship that can be harnessed for IR systems. The significant terms can be extracted using graph centrality measures. In this book, we have proposed a novel graph-of-words indexing technique using eigenvector scores that uses case separation for Gujarati language. We compared the performance of IR systems of our approach over the classical bag-of-words approach, mean average precision (MAP) values obtained in our experiments show that our approach has shown significant improvement over classical approaches. 164 pp. Englisch.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2019

    6200082766 / 9786200082763

    • Tapa blanda
    • Impresión bajo demanda

    Librería: moluna, Greven, Alemaniamoluna

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 58,12

    Envío por EUR 48,99 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: Más de 20 disponibles

    Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Joshi Dr. HardikDr. Hardik Joshi is an Assistant Professor with the Dept. of Computer Sc., Gujarat University, India. His research interests include Natural Language Processing and Information Retrieval.Information Retrieval(IR) .…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing, 2019

    6200082766 / 9786200082763

    • Tapa blanda
    • Impresión bajo demanda

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

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 79,37

    Envío por EUR 35,00 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: 1 disponible

    Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Information Retrieval(IR) systems are gaining importance due to wide range of applications like recommender systems, search engines, etc., however, most of the IR systems use statistical methods built on top of bag-of-words approach for text retrieval. Graph-of-words approach is an alternative to bag-of-words approach that uses graph theoretic methods to rank keywords and related documents. We represent text documents as graphs whose vertices correspond to the unique terms belonging to the document. The edges represent co-occurrences between the terms. The underlying assumption is that the terms that co-occur have some sort of semantic relationship that can be harnessed for IR systems. The significant terms can be extracted using graph centrality measures. In this book, we have proposed a novel graph-of-words indexing technique using eigenvector scores that uses case separation for Gujarati language. We compared the performance of IR systems of our approach over the classical bag-of-words approach, mean average precision (MAP) values obtained in our experiments show that our approach has shown significant improvement over classical approaches.…

  • Idioma: Inglés

    Editorial: LAP LAMBERT Academic Publishing Jun 2019, 2019

    6200082766 / 9786200082763

    • Tapa blanda
    • Impresión bajo demanda

    Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 71,90

    Envío por EUR 60,00 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: 1 disponible

    Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Information Retrieval(IR) systems are gaining importance due to wide range of applications like recommender systems, search engines, etc., however, most of the IR systems use statistical methods built on top of bag-of-words approach for text retrieval. Graph-of-words approach is an alternative to bag-of-words approach that uses graph theoretic methods to rank keywords and related documents. We represent text documents as graphs whose vertices correspond to the unique terms belonging to the document. The edges represent co-occurrences between the terms. The underlying assumption is that the terms that co-occur have some sort of semantic relationship that can be harnessed for IR systems. The significant terms can be extracted using graph centrality measures. In this book, we have proposed a novel graph-of-words indexing technique using eigenvector scores that uses case separation for Gujarati language. We compared the performance of IR systems of our approach over the classical bag-of-words approach, mean average precision (MAP) values obtained in our experiments show that our approach has shown significant improvement over classical approaches.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 164 pp. Englisch.…