the principle theoretical basis of this article is the concept of 'city text' and the textuality standards. the article explores city as a text and takes the textuality standards into consideration for analyzing the city. text is one of the main elements that play a significant role in communication. people communicating by language do not do so simply by means of individual words or ...

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For the last few years, text mining has been gaining significant importance. Since Knowledge is now available to users through variety of sources i.e. electronic media, digital media, print media, and many more. Due to huge availability of text in numerous forms, a lot of unstructured data has been recorded by research experts and have found numerous ways in literature to convert this scattered...

Text in natural images is an important source of information, which can be utilized for many real-world applications. This work focuses on a new problem: distinguishing images that contain text from a large volume of natural images. To address this problem, we propose a novel convolutional neural network variant, called Multi-scale Spatial Partition Network (MSP-Net). The network classifies ima...

intertextuality, is based on this idea that there is no independent text, and the text borrow from each other, there is a close and double relationship between them. according to this theory, each text is the brainchild of past or contemporary texts; so that new text (current) is summary of the text or several texts (absent). the purpose of this article is intertextual research of the bible in ...

The phenomenon of big data makes managing, processing, and extracting valuable information from the Web an increasingly challenging task. As such, the abundance of user-generated content with opinions about products or brands requires appropriate tools in order to be able to capture consumer sentiment. Such tools can be used to aggregate content by means of sentiment summarization techniques, e...

Classifying text data has been an active area of research for a long time. Text document is multifaceted object and often inherently ambiguous by nature. Multi-label learning deals with such ambiguous object. Classification of such ambiguous text objects often makes task of classifier difficult while assigning relevant classes to input document. Traditional single label and multi class text cla...

This work studies the use of deep learning methods to directly model glottal excitation waveforms from context dependent text features in a text-to-speech synthesis system. Glottal vocoding is integrated into a deep neural network-based text-to-speech framework where text and acoustic features can be flexibly used as both network inputs or outputs. Long short-term memory recurrent neural networ...

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 narrow window which is sliding a long that text line. It then injects the resulting feature vectors to the Hidden Markov Model Toolkit (HTK). HTK is a portable toolkit for speech recognition system. The proposed sys...