Research and industry are more and more focusing in finding automatically the polarity of an opinion regarding a specific subject or entity. Paragraph vector has been recently proposed to learn embeddings which are leveraged for English sentiment analysis. This paper focuses on Arabic sentiment analysis and investigates the use of paragraph vector within a machine learning techniques to determi...

on this paper, we proposed a new text line segmentation of handwritten and typewriting Arabic document images that uses the Outer Isothetic Cover (OIC) algorithm of a digital object. In the first step, we use this method to segment the composed document into text blocs. In the second step, for each text bloc we will extract the text lines. Finally, line text will be segmented into words or into...

When text is translated from one language into another, sentiment is preserved to varying degrees. In this paper, we use Arabic social media posts as stand-in for source language text, and determine loss in sentiment predictability when they are translated into English, manually and automatically. As benchmarks, we use manually and automatically determined sentiment labels of the Arabic texts. ...

Text classification is the task of assigning a document to one or more of pre-defined categories based on its contents. This paper presents the results of classifying Arabic language documents by applying the KNN classifier, one time by using N-Gram namely unigrams and bigrams in documents indexing, and another time by using traditional single terms indexing method (bag of words) which supposes...

Segmentation of clitics has been shown to improve accuracy on a variety of Arabic NLP tasks. However, state-of-the-art Arabic word segmenters are either limited to formal Modern Standard Arabic, performing poorly on Arabic text featuring dialectal vocabulary and grammar, or rely on linguistic knowledge that is hand-tuned for each dialect. We extend an existing MSA segmenter with a simple domain...

The automatic recognition of text on scanned images has several applications such as automatic postal mail sorting and searching in large volume of documents. Although Arabic handwritten text recognition has been addressed by many researchers, it remains a challenging task due to several factors. This paper presents an overview of off-line handwritten Arabic character recognition and summarizes...

This paper presents a cursive Arabic text recognition system. The system decomposes the document image into text line images and extracts a set of simple statistical features from a one-pixel width window which is sliding a cross that text line. It then injects the resulting feature vectors to Hidden Markov Models. The proposed system is applied to a data corpus which includes Arabic text of mo...

Arabic language is one of the most popular languages in the world. Hundreds of millions of people in many countries around the world speak Arabic as their native speaking. However, due to complexity of Arabic language, recognition of printed and handwritten Arabic text remained untouched for a very long time compared with English and Chinese. Although, in the last few years, significant number ...

Morphological analysis of Arabic words allows decreasing the storage requirements of the Arabic dictionaries, more efficient encoding of diacritical Arabic text, faster spelling and efficient Optical character recognition. All these factors allow efficient storage and archival of multilingual digital libraries that include Arabic texts. This paper presents a lossless compression algorithm based...

Many Natural Language Processing and Information Retrieval methods are based on the extensive use of text corpora. The credibility of the results can be heavily influenced by the underlying corpus quality. Much research has been utilizing Arabic corpora into various tasks of Arabic Information Processing. In this paper we discuss a suite of metrics that can be used to ascertain the quality of A...