Check order status

Become part of a community of book lovers from all over the world and get access to a whole bunch of benefits. Create an account for free

DPD courier 4.99 € GLS courier 11.49 €

Contact

How to shop

Help

My account

▸ Empty :-(

Multilingual Text Categorization

Name: Multilingual Text Categorization
Brand: Noor Publishing
SKU: 18181027
Price: 53.47 EUR
Availability: InStock
Author: Said Gadri
ISBN: 9786202343053

(Based on Machine Learning Algorithms and Ontologies)

Said Gadri

Language

English

Book Paperback

Libristo code: 18181027

Publishers Noor Publishing, November 2016

Text categorization is an important task in text mining process that consists in assigning a set of... Full description

Libristo code: 18181027

129 b

53.47 €

In stock at our supplier Shipping in 5-8 days

30-day return policy

Customers also purchased

Domínio do Scikit-Learn: Aprendizagem automática prática RUPESH KUMAR TIPU

Paperback

39.29 €

Castillos de carton Almudena Grandes

Paperback

11.03 €

Norden und Suden Elizabeth Gaskell

Paperback

18.02 €

Alkohol Hilfeschrei Burkhard Thom

Paperback

14.27 €

Tous ensemble 1

Sheet

13.26 €

Entwicklungshilfe Werner Lachmann

Paperback

37.87 €

Le loup qui avait un nouvel ami Lallemand

Paperback

10.22 €

Haarius und Zopftus

Paperback

7.89 €

Chronik von Guetenbach Joseph Fischer

Paperback

17.61 €

2016 Presidential Election (Edition Francaise) I D Oro

Paperback

10.32 €

Come prevenire la malattie transmesse da alimenti Alcides Troncoso

Paperback

44.55 €

Mujeres Catolicas Con Educacion Superior y Anticoncepcion Norma Angélica Sánchez Almaraz

Paperback

87.30 €

Fair Trade Ruben Quaas

Paperback

67.34 €

Actividad fisica en poblaciones especiales: Salud y calidad de vida Borja Sanudo Corrales

Paperback

23.89 €

Bioactividad de péptidos derivados de proteínas alimentarias Maira Segura-Campos

Paperback

19.84 €

God, Religion, Human (Kurdish Edition) Dara Mahmoud

Paperback

12.95 €

Text categorization is an important task in text mining process that consists in assigning a set of texts to a set of predefined categories based on learning algorithms. There exist two kinds of text categorization: monolingual and multilingual text categorization. The main problematic of this manuscript is how to exploit concepts and algorithms of machine learning in contextual categorization of multilingual texts. Our study on this subject allowed us to propose many solutions and provide many contributions, notably: (1) a simple, fast and effective algorithm to identify the language of a text in multilingual corpus. (2) An improved algorithm for Arabic stemming based on a statistical approach. Its main objective is to reduce the size of term vocabulary and thus increase the quality of the obtained categorization in TC and the effectiveness of search in IR. (3) A new multilingual stemmer which is general and completely independent of any language. (4) Application of new panoply of pseudo-distances to categorize texts of a big corpus such as Reuters21578 collection. All these solutions were the subject of many academic papers published in international conferences and journals.