Controllare lo stato dell'ordine

Entra a far parte di una comunità di amanti dei libri di tutto il mondo e ottieni numerosi vantaggi. Crea un account gratuito

Punto Poste 5.49 € Punto Poste 5.49 € Corriere DHL 6.99 € Corriere GLS 5.99 € Punto GLS 4.49 € Corriere Bartolini 4.49 € Punto Bartolini 3.49 €

Contatto

Come acquistare

Aiuto

Il mio account

▸ Vuoto :-(

Computational Trust Models and Machine Learning

Name: Computational Trust Models and Machine Learning
Brand: Apple Academic Press Inc.
SKU: 06677866
Price: 172.29 EUR
Availability: InStock
Author: Xin Liu
ISBN: 9781482226669

Xin Liu

Lingua

Inglese

Libro Rigido

Codice Libristo: 06677866

Casa editrice Apple Academic Press Inc., ottobre 2014

Computational Trust Models and Machine Learning provides a detailed introduction to the concept of t... Descrizione completa

Codice Libristo: 06677866

422 b

172.29 €

50% di possibilità Cercheremo nel mondo Quando riceverò il libro?

Fino a 30 giorni per il reso

I clienti hanno acquistato anche

Waffen-SS 1933–1945

In brossura

6.19 €

La caste des chastes - Les prêtres, le sexe et l'amour Marco Marzano

In brossura

20.59 €

AFA-SKALA Jak badać mowę dziecka afatycznego? Anna Paluch

In brossura

14.29 €

Adam in Koran, Koranexegese und syrischer Schatzhöhle Tugrul Kurt

Rigido

45.09 €

De passager à messager GRZESIAK

In brossura

21.59 €

Jak je to doopravdy s lidským tělem Monika Alžběta Svobodová

Rigido

7.59 €

Refutation de la doctrine de Hobbes sur le droit naturel de l'individu Auguste Walras

Adobe ePub DRM

9.49 €

Poemas Sobre Bellas Mariposas Juan Moises De La Serna

Adobe ePub DRM

3.09 €

Puccini-The Warner Classics Edition

CD audio

88.19 €

Tratamiento del Lupus Cutáneo con Talidomida José Ordi-Ros

In brossura

21.19 €

Ciele a meranie ekonomiky firmy Jozef Chajdiak

In brossura

1.99 €

Untersuchungen Zur Verbesserung Der Herstellungsverfahren Und Der Eigenschaften Technischer Leder Hans Herfeld

In brossura

52.49 €

Rolfing - Intégration structurale Hans Georg Brecklinghaus

In brossura

10.79 €

Briefe ibanios

Rigido

37.39 €

Voyage Pittoresque Et Sentimental Au Champ Du Repos Sous Montmartre Antoine Caillot

In brossura

17.99 €

Le Pauvre Diable Par Clemence Robert Robert-C

In brossura

26.39 €

Glückstage: Das Kalender-Tagebuch Nicole Neuberger

In brossura

11.59 €

Duguesclin: Connetable de France Et de Castille LAMBIN-E

In brossura

14.59 €

HANEMANN Stefan CHWIN Libro

In brossura

24.99 €

Das Recht Der Organisationen Im Neuen Deutschland Anonymous

In brossura

22.99 €

Enciclopedia Illustrata Dei Monumenti, Statue, Fontane Ed Opere Di Milano: Volume 02 Maurizio Om Ongaro

In brossura

92.99 €

NASH Lannes

In brossura

21.59 €

Specifique Aussi Rapide Qu'infaillible Pour La Guerison de la Maladie Des Moutons Charles-Gilbert Terray Morel de Vindé

In brossura

11.99 €

Aquarelles, Pastels Et Fusains Par Allonge Georges Meusnier

In brossura

11.99 €

Computational Trust Models and Machine Learning provides a detailed introduction to the concept of trust and its application in various computer science areas, including multi-agent systems, online social networks, and communication systems. Identifying trust modeling challenges that cannot be addressed by traditional approaches, this book:

Explains how reputation-based systems are used to determine trust in diverse online communities
Describes how machine learning techniques are employed to build robust reputation systems
Explores two distinctive approaches to determining credibility of resourcesone where the human role is implicit, and one that leverages human input explicitly
Shows how decision support can be facilitated by computational trust models
Discusses collaborative filtering-based trust aware recommendation systems
Defines a framework for translating a trust modeling problem into a learning problem
Investigates the objectivity of human feedback, emphasizing the need to filter out outlying opinions

Computational Trust Models and Machine Learning effectively demonstrates how novel machine learning techniques can improve the accuracy of trust assessment.