Review on reliable pattern recognition with machine learning techniques
D Bhamare, P Suryawanshi - Fuzzy Information and …, 2018 - ieeexplore.ieee.org
The primary goal of pattern recognition is supervised or unsupervised classification. Among
the various frameworks in which pattern recognition has been traditionally formulated, the …
the various frameworks in which pattern recognition has been traditionally formulated, the …
Exploring barriers to adoption of Virtual Reality through Social Media Analytics and Machine Learning–An assessment of technology, network, price and trialability
C Laurell, C Sandström, A Berthold… - Journal of Business …, 2019 - Elsevier
This paper aims to assess how diffusion of Virtual Reality (VR) technology is taking place
and identify potential barriers to increased adoption. This is done by utilising Social Media …
and identify potential barriers to increased adoption. This is done by utilising Social Media …
Natural language processing: History, evolution, application, and future work
It is quite hard to imagine a smart system like a voice assistant or a chat-bot or a
recommender system without natural language processing (NLP). It all starts with an initial …
recommender system without natural language processing (NLP). It all starts with an initial …
Analysis of Naïve Bayes algorithm for email spam filtering across multiple datasets
E-mail spam continues to become a problem on the Internet. Spammed e-mail may contain
many copies of the same message, commercial advertisement or other irrelevant posts like …
many copies of the same message, commercial advertisement or other irrelevant posts like …
Temporal burstiness and collaborative camouflage aware fraud detection
With the prosperity and development of the digital economy, many fraudsters have emerged
on e-commerce platforms to fabricate fraudulent reviews to mislead consumers' shopping …
on e-commerce platforms to fabricate fraudulent reviews to mislead consumers' shopping …
An improved transformer-based model for detecting phishing, spam, and ham: A large language model approach
Phishing and spam detection is long standing challenge that has been the subject of much
academic research. Large Language Models (LLM) have vast potential to transform society …
academic research. Large Language Models (LLM) have vast potential to transform society …
A SVM-based framework for fault detection in high-speed trains
Abstract High-Speed Trains (HSTs) demand high reliability, maintainability and availability
of their installed equipment. The braking system, in particular, is a safety-critical system in …
of their installed equipment. The braking system, in particular, is a safety-critical system in …
Finding rotten eggs: A review spam detection model using diverse feature sets
Social media enables customers to share their views, opinions and experiences as product
reviews. These product reviews facilitate customers in buying quality products. Due to the …
reviews. These product reviews facilitate customers in buying quality products. Due to the …
Machine learning with feature selection using principal component analysis for malware detection: a case study
J Zhang - arXiv preprint arXiv:1902.03639, 2019 - arxiv.org
Cyber security threats have been growing significantly in both volume and sophistication
over the past decade. This poses great challenges to malware detection without …
over the past decade. This poses great challenges to malware detection without …
Advances in spam detection for email spam, web spam, social network spam, and review spam: ML-based and nature-inspired-based techniques
AA Akinyelu - Journal of Computer Security, 2021 - content.iospress.com
Despite the great advances in spam detection, spam remains a major problem that has
affected the global economy enormously. Spam attacks are popularly perpetrated through …
affected the global economy enormously. Spam attacks are popularly perpetrated through …