SFr. 102.00
€ 110.16
BTC 0.002
LTC 1.623
ETH 0.0407


bestellen

Artikel-Nr. 33222284


Diesen Artikel in meine
Wunschliste
Diesen Artikel
weiterempfehlen
Diesen Preis
beobachten

Weitersagen:



Autor(en): 
  • Duncan Bell
  • Fathi Saad
  • Beatriz de la Iglesia
  • A Classification Method to Extract Knowledge from Text Documents: A novel Cluster-Classification Method for accurate classification of medical text re 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 7-14 Tagen versandfertig
    Veröffentlichung:  August 2012  
    Genre:  Ratgeber 
    ISBN:  9783659182044 
    EAN-Code: 
    9783659182044 
    Verlag:  LAP Lambert Academic Publishing 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 220 mm / B 150 mm / D 14 mm 
    Gewicht:  346 gr 
    Seiten:  220 
    Zus. Info:  Paperback 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    This book addresses the problem of text classification. The main motivation is the accurate classification of medical text reports. Such documents contain important information about patients, disease progression and management, but are difficult to analyse and query with conventional techniques due to their unstructured nature. We show how these medical reports can be classified automatically with a high degree of accuracy. A novel method is developed for accurate classification of medical reports. The method uses clustering as a pre-processing step to improve the final classification accuracy. The work requires the investigation of different methods for document representation, clustering and classification. In addition, it requires the use of Natural Language Processing tools. A new approach that requires minimal labelling effort, is found to be an effective classification tool for this task. Results show that the approach produces good classification performance on a real-world medical problem. Importantly, the addition of clustering features further improves the accuracy of the final classifier. Results are cross-checked using different medical classification tasks

      



    Wird aktuell angeschaut...
     

    Zurück zur letzten Ansicht


    AGB | Datenschutzerklärung | Mein Konto | Impressum | Partnerprogramm
    Newsletter | 1Advd.ch RSS News-Feed Newsfeed | 1Advd.ch Facebook-Page Facebook | 1Advd.ch Twitter-Page Twitter
    Forbidden Planet AG © 1999-2024
    Alle Angaben ohne Gewähr
     
    SUCHEN

     
     Kategorien
    Im Sortiment stöbern
    Genres
    Hörbücher
    Aktionen
     Infos
    Mein Konto
    Warenkorb
    Meine Wunschliste
     Kundenservice
    Recherchedienst
    Fragen / AGB / Kontakt
    Partnerprogramm
    Impressum
    © by Forbidden Planet AG 1999-2024