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Emotion Recognition in Text Using PPM
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In this paper we investigate the automatic recognition of emotion in text. We propose a new method for emotion recognition based on the PPM (PPM is short for Prediction by Partial Matching) character-based text compression scheme in order to recognize Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method is very effective when compared with traditional word-based text classification methods. We have also found that our method works best if the sizes of text in all classes used for training are similar, and that performance significantly improves with increased data.

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Publication Date
Fri Jul 01 2011
Journal Name
Engineering And Technology Journal
Off-Line Arabic Signature Recognition Based on Invariant Moments Properties
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Publication Date
Thu Jun 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
An optimized deep learning model for optical character recognition applications
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The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

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Publication Date
Fri May 16 2014
Journal Name
International Journal Of Computer Applications
Design and Implementation of Real Time Face Recognition System (RTFRS)
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Publication Date
Sat Jan 01 2022
Journal Name
Ieee Access
Hand Gesture Recognition With Acoustic Myography and Wavelet Scattering Transform
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Publication Date
Mon Aug 01 2022
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
Dorsal hand veins features extraction and recognition by correlation coefficient
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Publication Date
Mon Dec 01 2014
Journal Name
2014 Ieee Student Conference On Research And Development
Feature extraction for co-occurrence-based cosine similarity score of text documents
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Publication Date
Thu Jun 29 2017
Journal Name
College Of Islamic Sciences
Textual jurisprudence and jurisprudence of the science of the text: Linguistic study
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The modern textual study researched the textuality of the texts and specified for that seven well-known standards, relying in all of that on the main elements of the text (the speaker, the text, and the recipient). This study was to investigate the textuality of philology, and the jurisprudence of the science of the text.

 

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Publication Date
Wed Jun 01 2011
Journal Name
Journal Of Al-nahrain University Science
A Lexical and Syntax Checker Tool for the Hyper Text Markup Language
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Publication Date
Thu Nov 17 2022
Journal Name
Journal Of Information And Optimization Sciences
Hybrid deep learning model for Arabic text classification based on mutual information
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Publication Date
Wed Oct 07 2026
Journal Name
International Journal Of Data And Network Science
Multi-objective of wind-driven optimization as feature selection and clustering to enhance text clustering
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Text Clustering consists of grouping objects of similar categories. The initial centroids influence operation of the system with the potential to become trapped in local optima. The second issue pertains to the impact of a huge number of features on the determination of optimal initial centroids. The problem of dimensionality may be reduced by feature selection. Therefore, Wind Driven Optimization (WDO) was employed as Feature Selection to reduce the unimportant words from the text. In addition, the current study has integrated a novel clustering optimization technique called the WDO (Wasp Swarm Optimization) to effectively determine the most suitable initial centroids. The result showed the new meta-heuristic which is WDO was employed as t

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