Classifiers for Arabic NLP: survey

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Use of NLP Tools in CALL System for Arabic

This article focuses on the development of Natural Language Processing (NLP) tools for Computer Assisted Language Learning (CALL). First, we have developed some NLP tools: a labelled dictionary of Arabic (as complete as possible), a generator for morphological derivatives, a Conjugator and a morphological analyzer for Arabic. Second, we used these tools to create a number of educational applica...

متن کامل

Arabic Cross-Document NLP for the Hadith and Biography Literature

Recently cross-document integration and reconciliation of extracted information became of interest to researchers in Arabic natural language processing. Given a set of documents A, we use Arabic morphological analysis, finite state machines, and graph transformations to extract named entities Na and relations Ra expressed as edges in a graph G = 〈Na, Ra〉. We use the same techniques to extract e...

متن کامل

Hierarchical Classifiers for Multi-Way Sentiment Analysis of Arabic Reviews

Sentiment Analysis (SA) is one of hottest fields in data mining (DM) and natural language processing (NLP). The goal of SA is to extract the sentiment conveyed in a certain text based on its content. While most current works focus on the simple problem of determining whether the sentiment is positive or negative, Multi-Way Sentiment Analysis (MWSA) focuses on sentiments conveyed through a ratin...

متن کامل

Towards a Learning System Based on Arabic NLP Tools

rights, including translation into other languages reserved by the publisher. No part of this journal may be reproduced or used in any form or by any means without written permission from the publisher, except for noncommercial, educational use including classroom teaching purposes. Product or company names used in this journal are for identification purposes only. Inclusion of the names of the...

متن کامل

Explaining Predictions of Non-Linear Classifiers in NLP

Layer-wise relevance propagation (LRP) is a recently proposed technique for explaining predictions of complex non-linear classifiers in terms of input variables. In this paper, we apply LRP for the first time to natural language processing (NLP). More precisely, we use it to explain the predictions of a convolutional neural network (CNN) trained on a topic categorization task. Our analysis high...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: International Journal of Computational Complexity and Intelligent Algorithms

سال: 2020

ISSN: 2048-4720,2048-4739

DOI: 10.1504/ijccia.2020.105538