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A novel discrete slash family of distributions with application to epidemiology informatics data
This study puts forward a new class of discrete distribution that can be used by the epidemiologists and medical scientists to model data relating to...
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Temporal analysis of topic modeling output by machine learning techniques
Topic modeling is widely recognized as one of the most effective and significant methods of unsupervised text analysis. This method facilitates...
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Evaluating collective action theory-based model to simulate mobs
A mob is an event that is organized via social media, email, SMS, or other forms of digital communication technologies in which a group of people...
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On a pyramid structure in social networks
This study introduces a hierarchical pyramid structure as a novel framework for social network analysis, differing fundamentally from traditional...
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Lyapunov-guided representation of recurrent neural network performance
Recurrent neural networks (RNN) are ubiquitous computing systems for sequences and multivariate time-series data. While several robust RNN...
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Ant Colony Optimization for solving Directed Chinese Postman Problem
The Chinese Postman Problem (CPP) is a well-known optimization problem involving determining the shortest route, modeling the system as an undirected...
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Res-MGCA-SE: a lightweight convolutional neural network based on vision transformer for medical image classification
This paper presents a lightweight and accurate convolution neural network (CNN) based on encoder in vision transformer structure, which uses...
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New custom rating for improving recommendation system performance
Recommendation system is currently attracting the interest of many explorers. Various new businesses have surfaced with the rise of online marketing...
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A targeted vaccination strategy based on dynamic community detection for epidemic networks
Vaccination is a vital strategy to prevent and control the spread of infectious diseases. In this paper, we propose a vaccination strategy that...
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A new feature selection algorithm based on fuzzy-pathfinder optimization
Data mining and machine learning require feature selection because features can dramatically improve model performance. In contrast, there are no...
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A review of sentiment analysis: tasks, applications, and deep learning techniques
Sentiment analysis, a transformative force in natural language processing, revolutionizes diverse fields such as business, social media, healthcare,...
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Deep learning for ultrasound medical images: artificial life variant
Segmentation of tumors in the ultrasound (US) images of the breast is a critical problem in medical imaging. Due to the poor quality of the US images...
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Improving incentive policies to salespeople cross-sells: a cost-sensitive uplift modeling approach
In this study, we present a novel cost-sensitive approach for uplift modeling in the context of cross-selling and workforce analytics. We leverage...
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ProxMetrics: modular proxemic similarity toolkit to generate domain-adaptable indicators from social media
In this paper, we introduce ProxMetrics , a novel toolkit designed to evaluate similarity among social media entities through proxemic dimensions....
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Search and Harvesting across NFDI Consortia – Gaps and Challenges
Search and harvesting use cases on harmonised metadata play an important role in several activities on National Research Data Infrastructures (NFDI)....
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A synthetic data generation system based on the variational-autoencoder technique and the linked data paradigm
Currently, the generation of synthetic data has become very fashionable, either due to the need to create data in certain specific contexts or to...
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Twit-CoFiD: a hybrid recommender system based on tweet sentiment analysis
Internet users are overwhelmed by the vast number of services and products to choose from. This data deluge has led to the need for recommender...
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Hybrid physics-infused 1D-CNN based deep learning framework for diesel engine fault diagnostics
Fault diagnosis is required to ensure the safe operation of various equipment and enables real-time monitoring of associated components. As a result,...
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DSPformer: discovering semantic parts with token growth and clustering for zero-shot learning
Transformers have achieved success in many computer vision tasks, but their potential in Zero-Shot Learning (ZSL) has yet to be fully explored. In...
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Injecting the score of the first-stage retriever as text improves BERT-based re-rankers
In this paper we propose a novel approach for combining first-stage lexical retrieval models and Transformer-based re-rankers: we inject the...
