Is this you? As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
Claim your profile
Articles by Noah SAM
Review of predictive techniques for detecting mental disorders from user-generated content on social media
Mental health is a crucial concern in health research and, as of late, receives more attention than physical health. It refers to a ‘state of well-being that enables everyone to maximise their potential, cope with obstacles, be proactive in working, and contribute to the development of a pleasant society (World Health Organization, 2018).
Popularity bias reduction in multi-criteria recommender systems: the RelPref and PriRelPref approaches
Popularity bias reduction in multi-criteria recommender systems: the RelPref and PriRelPref approaches 1Department of Advanced Technologies, Ardahan University, Ardahan, Turkey 2Computer Engineering Department, Ardahan University, Ardahan, Turkey DOI 10.7717/peerj-cs.3658 Academic Editor Giovanni Angiulli Subject Areas Data Mining and Machine Learning, Data Science Keywords Multi-criteria recommender systems, Popularity bias, User priority, Preference model, Tendency Copyright © Licence This...
Feature-based enhanced boosting algorithm for depression detection
Depression, a prevalent mental health condition, involves irregularity in individuals’ behavior (Stein et al., 2020), and poses a significant public health problem around the globe, approximately 280 million people worldwide have depression (WHO, 2023). It is characterized by persistent feelings of sadness, hopelessness, and loss of interest in activities.
Data augmentation for Arabic text classification: a review of current methods, challenges and prospective directions
Data augmentation for Arabic text classification: a review of current methods, challenges and prospective directions 1Center for Artificial Intelligence Technology, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia 2Faculty of Computers and Information Technology, Hadhramout University, Almukalla, Hadhramout, Yemen DOI 10.7717/peerj-cs.2685 Academic Editor Arkaitz Zubiaga Subject Areas Algorithms and Analysis of Algorithms, Artificial...
A majority voting framework for reliable sentiment analysis of product reviews
Businesses increasingly rely on sentiment analysis to understand customer preferences, perform market analysis, monitor brand reputation, and gauge customer experiences, making it a powerful tool for decision-making in competitive markets (Geetha & Karthika Renuka, 2021). While originally intended as a feedback tool to help companies improve, product reviews now also influence consumer perception and drive sales rankings (Catelli et al., 2022; Kim, 2024).
Evolving techniques in sentiment analysis: a comprehensive review
Sentiment analysis, a branch of natural language processing (NLP), concentrates on automatically recognizing and classifying emotions and attitudes conveyed in written language. In other words, sentiment analysis emphasis is on detecting emotions and viewpoints articulated in written texts or sentiment analysis involves identifying, assessing, and categorizing emotions expressed in text data (positive, neutral and negative).
Natural language processing for analyzing online customer reviews: a survey, taxonomy, and open research challenges
In the digital era, online customer reviews influence consumer choices. Customers seek peer reviews for assurance and guidance in a global market with alternatives. Reviews offer real-world insights into product and service pros and cons, going beyond marketing narratives (Dwivedi et al., 2021). Online reviews affect e-commerce sites like Amazon and Flipkart and hospitality platforms like TripAdvisor and Yelp. The influence of online customer reviews goes beyond consumers.
Enhancing traditional Chinese medical named entity recognition with Dyn-Att Net: a dynamic attention approach
Enhancing traditional Chinese medical named entity recognition with Dyn-Att Net: a dynamic attention approach Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia DOI 10.7717/peerj-cs.2022 Academic Editor Xiangjie Kong Subject Areas Algorithms and Analysis of Algorithms, Artificial Intelligence, Computational Linguistics, Natural Language and Speech, Neural Networks Keywords Traditional Chinese medical, Named entity recognition, Dynamic...
An experimental study on the performance of collaborative filtering based on user reviews for large-scale datasets
This study presented four methods for calculating ratings based on user reviews which are then evaluated in terms of their accuracy in different CF rating prediction algorithms. The first method sums all the sentiment scores/ratings for the sentiment terms mentioned in the review. The second method calculates implicit ratings based on a weighted aggregate of the user’s opinions regarding different aspects of an item.
Requests classification in the customer service area for software companies using machine learning and natural language processing
Introduction Artificial intelligence (AI) allows the simulation of intelligent human behaviors such as learning and decision making. It is possible due to computational algorithms in the machine learning (ML) field (Da Xu, Lu & Li, 2021). In particular, one of the applications of AI is automatic text classification (TC), which is very useful for characterizing large sets of words from their content (Al-Salemi, Noah & Ab Aziz, 2016).
Show More
loading
Actions
Is this you?
As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.Get in touch with Noah
Contact Noah, search articles and posts on X, monitor coverage, and track replies from one place.
Learn more about Muck Rack