scholarly journals Automated Detection of Bilingual Obfuscated Abusive Words on Social Media Forums: A Case of Swahili and English Texts

2021 ◽  
Vol 47 (4) ◽  
pp. 1352-1361
Author(s):  
Geofrey Njovangwa ◽  
Godfrey Justo
Keyword(s):  
Social Media ◽  
Detection Rate ◽  
Automated Detection ◽  
Rule Based ◽  
Highly Effective ◽  
Rule Based Approach ◽  
Matching Techniques ◽  
Percentage Ratio

The usage of social media has exponentially grown in recent years leaving the users with no limitations on misusing the platforms through abusive contents as deemed fit to them. This exacerbates abusive words exposure to innocent users, especially in social media forums, including children. In an attempt to alleviate the problem of abusive words proliferation on social media, researchers have proposed different methods to help deal with variants of the abusive words; however, obfuscated abusive words detection still poses challenges. A method that utilizes a combination of rule based approach and character percentage matching techniques is proposed to improve the detection rate for obfuscated abusive words. The evaluation results achieved F1 score percentage ratio of 0.97 and accuracy percentage ratio of 0.96 which were above the significance ratio of 0.5. Hence, the proposed approach is highly effective for obfuscated abusive words detection and prevention. Keywords:     Rule based approach, Character percentage matching techniques, Obfuscated abuse, Abuse detection, Abusive words, Social media

A Brief Survey on Text Classification Using Various Machine Learning Techniques

2018 ◽  
Vol 8 (1) ◽  
pp. 14
Author(s):  
Padmavathi .S ◽  
M. Chidambaram
Keyword(s):  
Machine Learning ◽  
Text Classification ◽  
Fixed Number ◽  
Machine Learning Techniques ◽  
Online Information ◽  
Rule Based ◽  
Learning Techniques ◽  
Machine Learning Approach ◽  
Rule Based Approach

Text classification has grown into more significant in managing and organizing the text data due to tremendous growth of online information. It does classification of documents in to fixed number of predefined categories. Rule based approach and Machine learning approach are the two ways of text classification. In rule based approach, classification of documents is done based on manually defined rules. In Machine learning based approach, classification rules or classifier are defined automatically using example documents. It has higher recall and quick process. This paper shows an investigation on text classification utilizing different machine learning techniques.

MRI Brain Tumor Image Analysis Using Fuzzy Rule based Approach

2019 ◽  
Vol 50 (2) ◽  
pp. 98-112 ◽  
Author(s):  
KALYAN KUMAR JENA ◽  
SASMITA MISHRA ◽  
SAROJANANDA MISHRA ◽  
SOURAV KUMAR BHOI ◽  
SOUMYA RANJAN NAYAK
Keyword(s):  
Image Analysis ◽  
Brain Tumor ◽  
Fuzzy Rule ◽  
Rule Based ◽  
Mri Brain ◽  
Rule Based Approach

Rule-based Approach to Semantic Resolution of Chinese Addresses

2010 ◽  
Vol 12 (1) ◽  
pp. 9-16 ◽  
Author(s):  
Xueying ZHNAG ◽  
Guonian LV ◽  
Boqiu LI ◽  
Wenjun CHEN
Keyword(s):  
Rule Based ◽  
Semantic Resolution ◽  
Rule Based Approach

An Automatic Question Generation System using Rule-Based Approach in Bloom’s Taxonomy

2019 ◽  
Vol 13 ◽  
Author(s):  
G Deena ◽  
K Raja ◽  
K Kannan
Keyword(s):  
Language Processing ◽  
Learning Process ◽  
Question Generation ◽  
Test Question ◽  
Rule Based ◽  
Part Of Speech ◽  
Core Idea ◽  
Rule Based Approach ◽  
Teaching Learning ◽  
Automatic Question Generation

: In this competing world, education has become part of everyday life. The process of imparting the knowledge to the learner through education is the core idea in the Teaching-Learning Process (TLP). An assessment is one way to identify the learner’s weak spot of the area under discussion. An assessment question has higher preferences in judging the learner's skill. In manual preparation, the questions are not assured in excellence and fairness to assess the learner’s cognitive skill. Question generation is the most important part of the teaching-learning process. It is clearly understood that generating the test question is the toughest part. Methods: Proposed an Automatic Question Generation (AQG) system which automatically generates the assessment questions dynamically from the input file. Objective: The Proposed system is to generate the test questions that are mapped with blooms taxonomy to determine the learner’s cognitive level. The cloze type questions are generated using the tag part-of-speech and random function. Rule-based approaches and Natural Language Processing (NLP) techniques are implemented to generate the procedural question of the lowest blooms cognitive levels. Analysis: The outputs are dynamic in nature to create a different set of questions at each execution. Here, input paragraph is selected from computer science domain and their output efficiency are measured using the precision and recall.

Rule‐Based Approach for Botnet Behavior Analysis

2021 ◽  
pp. 161-179
Author(s):  
Supriya Raheja ◽  
Geetika Munjal ◽  
Jyoti Jangra ◽  
Rakesh Garg
Keyword(s):  
Behavior Analysis ◽  
Rule Based ◽  
Rule Based Approach

scholarly journals The Optimization Analysis for the Original and Manipulation Identification of Illegally Filmed Images

2021 ◽  
Vol 11 (11) ◽  
pp. 5220
Author(s):  
Soohyeon Choi ◽  
Dohoon Kim
Keyword(s):  
Social Media ◽  
Mobile Device ◽  
Detection Rate ◽  
Precise Measurement ◽  
Detection Method ◽  
Optimization Analysis ◽  
Storage Devices ◽  
Digital Forensic ◽  
Attribute Information ◽  
Measurement Approach

Illegally filmed images, the sharing of non-consensually filmed images over social media, and the secret recording and distribution of celebrity images are increasing. To catch distributors of illegally filmed images, many investigation techniques based on an analysis of the file attribute information of the original images have been introduced. As forensic science advances, various types of anti-forensic technologies are being produced, requiring investigators to open and analyze all videos from the suspect’s storage devices, raising the question of the invasion of privacy during the investigation. The suspect can even file a lawsuit, which makes issuing a warrant and conducting an investigation difficult. Thus, it is necessary to detect the original and manipulated images without needing to directly go through multiple videos. We propose an optimization analysis and detection method for extracting original and manipulated images from seized devices of suspects. In addition, to increase the detection rate of both original and manipulated images, we suggest a precise measurement approach for comparative thresholds. Thus, the proposed method is a new digital forensic methodology for comparing and identifying original and manipulated images accurately without the need for opening videos individually in a suspect’s mobile device.

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