A Proposed Arabic Text and Text Image Classification Technique Using a URL Address

Abstract

Sentiment analysis is examined within natural language processing. It is instrumental in finding the sentiment (feeling) or opinion (idea) hidden within a text. This research focuses on finding sentiments in a “text image” and then classifying them whether they are desirable or not. These phrases and words refer to the perspectives of people about anything they think about it, such as services, products, governments, and social media events. In this study, the optical character recognition (OCR) algorithm was used, which is considered as a classification procedure of visual patterns that appear in the form of a digital image. Moreover, the Naïve Bayes machine learning algorithm was employed to classify these texts. These two algorithms form a hybrid system that supports our needs, especially in this day of technological advances and frequent use of websites and sharing of text images through the internet. Finally, the new vision in this work involves dealing with Arabic language texts that are transformed into images, which are extracted from a URL address and then classified into desirable and undesirable content.

Online Multilingual Plagiarism Detection System Using Multi Search Engines

“…It is used to detect multilingual text plagiarism online using three popular search engines: Google, Bing, and Yandex APIs. It accepts as input a text with a plagiarism threshold and outputs each sentence with a score that tells you if the sentence is unique or plagiarized, along with additional information such as URL and the percentage of similarity in case of the online existence of the test sentence [26].…”