Foundation and large language models: fundamentals, challenges, opportunities, and social impacts
D Myers, R Mohawesh, VI Chellaboina, AL Sathvik… - Cluster …, 2024 - Springer
Abstract Foundation and Large Language Models (FLLMs) are models that are trained using
a massive amount of data with the intent to perform a variety of downstream tasks. FLLMs …
a massive amount of data with the intent to perform a variety of downstream tasks. FLLMs …
Fake review detection techniques, issues, and future research directions: a literature review
Recently, the impact of product or service reviews on customers' purchasing decisions has
become increasingly significant in online businesses. Consequently, manipulating reviews …
become increasingly significant in online businesses. Consequently, manipulating reviews …
[HTML][HTML] Fake review detection using transformer-based enhanced LSTM and RoBERTa
Internet reviews significantly influence consumer purchase decisions across all types of
goods and services. However, fake reviews can mislead both customers and businesses …
goods and services. However, fake reviews can mislead both customers and businesses …
Node embedding approach for accurate detection of fake reviews: a graph-based machine learning approach with explainable AI
In recent years, online reviews have become increasingly important in promoting various
products and services. Unfortunately, writing deceptive reviews has also become a common …
products and services. Unfortunately, writing deceptive reviews has also become a common …
[PDF][PDF] 'The strategy of discriminating false comments on the internet by fusing probabilistic topic and word vector models
F Long - Int. Arab J. Inform. Technol, 2024 - iajit.org
With the acceleration of the social process of “Internet+”, e-commerce has entered an era of
rapid development. In response to the subjective judgments in current false information …
rapid development. In response to the subjective judgments in current false information …
Medicine Drug Name Detection Object Recognition using Deep Learning based OCR System
S Jasmine, R Ch, R Srikavya - 2023 International Conference …, 2023 - ieeexplore.ieee.org
In a digital picture, such as a photo, document, or any other image with tags or steps, OCR is
a system that can identify characters like letters, numbers, and symbols. Pre-processing is …
a system that can identify characters like letters, numbers, and symbols. Pre-processing is …
Monitoring AI-Based Processing for Predicting Poisonous Gas Emissions in Smart Cities Using Novel Temporal Dynamics Prediction Model
Smart cities, driven by technological advancements, face challenges related to
environmental pollution, including poisonous gas emissions. Existing systems often struggle …
environmental pollution, including poisonous gas emissions. Existing systems often struggle …
Confounds and overestimations in fake review detection: Experimentally controlling for product-ownership and data-origin
The popularity of online shop** is steadily increasing. At the same time, fake product
reviews are published widely and have the potential to affect consumer purchasing …
reviews are published widely and have the potential to affect consumer purchasing …
MAGAT-HOS: A Multi-Attention Graph Neural Network for Fake Review Detection by Incorporating High-Order Semantic Information
Y Yao, L Chen, D Zhang, L Qin - 2024 International Joint …, 2024 - ieeexplore.ieee.org
The proliferation of fake reviews on e-commerce platforms has seriously and negatively
affected consumers' purchase decisions. In recent years, some researchers have started …
affected consumers' purchase decisions. In recent years, some researchers have started …
K-means Clustering Powered Context Aware Food Recommender System
M Panwar, A Sharma, OP Mahela… - 2023 International …, 2023 - ieeexplore.ieee.org
This paper designed a K-means clustering powered context aware food recommender
system (CAFRS). The CAFRS is based on dividing the food data sets into clusters to …
system (CAFRS). The CAFRS is based on dividing the food data sets into clusters to …