Noor Farizah Ibrahim
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View article: Contrastive learning on high-order noisy graphs for collaborative recommendation
Contrastive learning on high-order noisy graphs for collaborative recommendation Open
The graph-based collaborative filtering method has shown significant application value in recommendation systems, as it models user-item preferences by constructing a user-item interaction graph. However, existing methods face challenges r…
View article: Dual-level graph contrastive collaborative filtering
Dual-level graph contrastive collaborative filtering Open
View article: SentiEntityRec: Entity-level sentiment perception graph neural network for news recommendation
SentiEntityRec: Entity-level sentiment perception graph neural network for news recommendation Open
Precise news recommendations are critical in today’s digital landscape. However, conventional approaches overlook fine-grained sentiment nuances associated with individual entities in news content. This paper presents SentiEntityRec, a nov…
View article: Reinforcement Learning-Based Voting for Feature Drift-Aware Intrusion Detection: An Incremental Learning Framework
Reinforcement Learning-Based Voting for Feature Drift-Aware Intrusion Detection: An Incremental Learning Framework Open
In Intrusion Detection Systems (IDS), stream data classification faces significant challenges due to concept drifts and feature evolution, where traditional methods struggle to maintain accuracy over time. One critical challenge is feature…
View article: A Hybrid Improved IRSO–CNN Algorithm for Accurate Recognition of Dynamic Gestures in Malaysian Sign Language
A Hybrid Improved IRSO–CNN Algorithm for Accurate Recognition of Dynamic Gestures in Malaysian Sign Language Open
Hand gestures are a powerful means of communication, especially for people with limited or no hearing ability. They also play a critical role in human–computer interaction (HCI). Comprehending hand gestures is crucial to ensuring that list…
View article: Evolving cybersecurity frontiers: A comprehensive survey on concept drift and feature dynamics aware machine and deep learning in intrusion detection systems
Evolving cybersecurity frontiers: A comprehensive survey on concept drift and feature dynamics aware machine and deep learning in intrusion detection systems Open
View article: Evaluation of machine learning and deep learning methods for early detection of internet of things botnets
Evaluation of machine learning and deep learning methods for early detection of internet of things botnets Open
The internet of things (IoT) represents a rapidly expanding sector within computing, facilitating the interconnection of myriad smart devices autonomously. However, the complex interplay of IoT systems and their interdisciplinary nature ha…
View article: Group recommendation fueled by noise-based graph contrastive learning
Group recommendation fueled by noise-based graph contrastive learning Open
The ongoing advancement of social network platforms has increased the frequency of group activities. Due to the varied composition of group members, recommending items that align with the preferences of the entire group becomes a challenge…
View article: Alignment-Based Pseudo-Label Generation With Collaborative Filtering Mechanism for Enhanced Cross-Domain Aspect-Based Sentiment Analysis
Alignment-Based Pseudo-Label Generation With Collaborative Filtering Mechanism for Enhanced Cross-Domain Aspect-Based Sentiment Analysis Open
Aspect-based sentiment analysis (ABSA) in areas such as online shopping and restaurants can effectively facilitate specific service improvements. However, ABSA performance heavily relies on high-quality labeled data, posing a major challen…
View article: IoT Smart Devices Risk Assessment Model Using Fuzzy Logic and PSO
IoT Smart Devices Risk Assessment Model Using Fuzzy Logic and PSO Open
Increasing Internet of Things (IoT) device connectivity makes botnet attacks more dangerous, carrying catastrophic hazards.As IoT botnets evolve, their dynamic and multifaceted nature hampers conventional detection methods.This paper propo…
View article: Transforming urban mobility with internet of things: public bus fleet tracking using proximity-based bluetooth beacons
Transforming urban mobility with internet of things: public bus fleet tracking using proximity-based bluetooth beacons Open
In today’s fast-paced world, efficient and reliable public transportation systems are crucial for optimising time and reducing carbon dioxide emissions. However, developing countries face numerous challenges in their public transportation …
View article: Solving Complexity Dataset in e-Ticketing using Machine Learning to Determine Optimum Feature
Solving Complexity Dataset in e-Ticketing using Machine Learning to Determine Optimum Feature Open
e-ticketing is one of the common applications used in technical support in Information Technology (IT) and has been used worldwide in any field of company. The benefits of e-ticketing can reduce the human efforts, increase the sufficiency …
View article: COVID-19 Infodemic in Malaysia: Conceptualizing Fake News for Detection
COVID-19 Infodemic in Malaysia: Conceptualizing Fake News for Detection Open
There is an “Infodemic” of COVID-19 in which there are a lot of rumours and information disorders spreading rapidly, the purpose of the study is to build a predictive model for identifying whether the COVID-19 information in the Malay lang…
View article: SoLGR: Social Enhancement Group Recommendation via Light Graph Convolution Networks
SoLGR: Social Enhancement Group Recommendation via Light Graph Convolution Networks Open
With the rapid development of social networks, online and offline group activities are becoming more common and diverse. Considering the different interests of group members, the recommendation service for a group is more challenging than …
View article: Detecting Spam Email with Machine Learning Optimized with Harris Hawks optimizer (HHO) Algorithm
Detecting Spam Email with Machine Learning Optimized with Harris Hawks optimizer (HHO) Algorithm Open
Email spam has been a big issue in recent years. As the percentage of internet users grows, so does the number of spam emails. Technologies are being used for illegitimate and immoral activities, such as phishing and robbery. As a conseque…
View article: Exploring the Sentiment and Online Review of Multilevel Marketing (MLM) Company Products
Exploring the Sentiment and Online Review of Multilevel Marketing (MLM) Company Products Open
Reviews and tweets posted on social media and websites offer timely opinion and feedback for companies to learn about customers' concerns.As a seller or marketer, it is important to understand what customer thinks and feel about products o…
View article: A text analytics approach for online retailing service improvement: Evidence from Twitter
A text analytics approach for online retailing service improvement: Evidence from Twitter Open
View article: Decoding the sentiment dynamics of online retailing customers: Time series analysis of social media
Decoding the sentiment dynamics of online retailing customers: Time series analysis of social media Open
View article: Exploring the effect of user engagement in online brand communities: Evidence from Twitter
Exploring the effect of user engagement in online brand communities: Evidence from Twitter Open
View article: Designing Online Service: From State-of-the-Art to a Unified Framework
Designing Online Service: From State-of-the-Art to a Unified Framework Open
Online services are now extensively used all over the world in desktop and mobile applications.These services are driven by technologies that attempt to enhance how people manage their lives in more networked and interconnected ways.The ai…