Skip to main content

Annals of Data Science OnlineFirst articles

Identifying the Intents Behind Website Visits by Employing Unsupervised Machine Learning Models

  • Open Access
  • Review Article

With digitisation globally on the rise, corporates are compelled to better understand the usage of their websites. In doing so, corporates will be empowered to better understand consumers, and make necessary adjustments to ultimately improve the …

The Use of Data Mining in the Management of the Career Guidance Work of the University

  • Original Article

This study explores the application of data mining techniques to analyse factors influencing university choice and predict enrolment trends in Kazakhstan. For this purpose, methods of analysis (multiple correlation and regression analysis, factor …

Sentiment-Based Hierarchical Deep Learning Framework Using Hybrid Optimization for Course Recommendation in E-learning

  • Original Article

Course recommendation (CD) is essential for success in a student’s educational journey. Due to the variations in student’s knowledge system, it might be difficult to select the course content from online educational platforms. This problem is …

Generalized Alpha Power Inverted Weibull Distribution: Application of Air Pollution in Kathmandu, Nepal

  • Original Article

A novel probability distribution, the Generalized Alpha Power Inverted Weibull (GAPIW) distribution, is derived from the generalization of the $$\alpha$$ α -power family and compounded with the inverted Weibull distribution. The researchers looked …

On the xgamma k-record values and associated inference

  • Original Article

The xgamma distribution was first introduced by Sen et al. [1] as an alternative distribution to the exponential model. The xgamma distribution exhibits a bathtub-shaped hazard rate function, so it is suitable for many lifetime phenomena. In this …

Deep Enhancement in Supplychain Management with Adaptive Serial Cascaded Autoencoder with Long Short Term Memory and Multi-layered Perceptron Framework

  • Original Article

Recognizing and reducing risk is a major part of Supply Chain Management (SCM). Several companies are invested in Supply Chain Risk Management (SCRM) and they have the knowledge about the procurement occupancies within their companies and take …

Statistical Data-Driven Modelling and Forecasting: An Application to COVID-19 Pandemic

  • Original Article

One of the key objectives of statistics is to provide a model compatible with the data generated by an unknown random process. Often, it happens that the unknown process is intractable, and no prior data or information associated with the unknown …

Sentiment Analysis of Hate Speech on Women in Social Media Platform Using Multi Label Classification

  • Original Article

We live in a world where everything is connected to online social media platforms, and the person uses social media networks like Face book, Twitter, Instagram, Whatsapp, etc. In the present scenario, working women, celebrities, sports persons …

Beyond Regular SPC: Bridging the Capability Index for (a)Symmetric Data

  • Original Article

The advancement of technology has increased competitiveness, especially in the manufacturing industry. Alongside Statistical Process Control (SPC), capacity indices are tools used to measure the quality of processes and are useful for establishing …

Modeling and Analysis of Trading Volume and Stock Return Data Using Bivariate q-Gaussian Distribution

  • Original Article

Two known characteristics of the distribution of stock returns (price fluctuations) and, more recently, the distribution of financial asset volumes are power laws and scaling. These power laws can be viewed as the asymptotic behaviour of …

A Novel Finite Mixture Model Based on the Generalized t Distributions with Two-Sided Censored Data

In light of the rapid technological advancements witnessed in recent decades, numerous disciplines have been inundated with voluminous datasets characterized by multimodality, heavy-tailed distributions, and prevalent missing information.

Exploring the Potential of the Kumaraswamy Discrete Half-Logistic Distribution in Data Science Scanning and Decision-Making

Data science often employs discrete probability distributions to model and analyze various phenomena. These distributions are particularly useful when dealing with data that can be categorized into distinct outcomes or events. This study presents …

Determining the Correlation among the Users' Satisfaction and Familiarity with Malay Entrepreneurs Food Delivery Mobile Applications in Malaysia

The rise of mobile technology has significantly transformed numerous aspects of our everyday lives, especially within food delivery services. The investigation aims to explore the food delivery mobile apps (FDMA) satisfaction (SAT) and the …

Designing Supply Chain Management Pattern in Small Scale Integrated Commercial Agriculture

This paper has investigated an empirical study to consider the impact of supply chain management on small scale integrated commercial agriculture by focusing on the moderator role of impediments and obligations to offer solutions for agricultural …

The Modified Lindley Distribution Through Convex Combination with Applications in Engineering

This paper introduces a Modified Lindley distribution using a convex combination of exponential and gamma distribution. The fundamental properties of the proposed distribution such as the shapes of the distribution, moments, mean, variance …

Gated Graph Attention-based Crossover Snake (GGA-CS) Algorithm for Hyperspectral Image Classification

Hyperspectral image classification involves assigning pixels or regions within a hyperspectral image to specific classes or categories based on the spectral information captured across multiple bands. Traditional method faces several challenges …

Kernel-free Reduced Quadratic Surface Support Vector Machine with 0-1 Loss Function and L-norm Regularization

This paper presents a novel nonlinear binary classification method, namely the kernel-free reduced quadratic surface support vector machine with 0-1 loss function and L $$_{p}$$ p -norm regularization (L $$_p$$ p -RQSSVM $$_{0/1}$$ 0 / 1 ). It …

An Empirical Study of Nature-Inspired Algorithms for Feature Selection in Medical Applications

Nature-inspired algorithms (NIA) are proven to be the potential tool for solving intricate optimization problems and aid in the development of better computational techniques. In recent years, these algorithms have raised considerable interest to …

Comparative Analysis of Machine Learning Techniques for Imbalanced Genetic Data

Advancements in genome sequencing technologies have significantly increased the availability of genomic data. The use of machine learning models to predict the pathogenicity or clinical significance of genetic mutations is crucial. However …

Non-negative Sparse Matrix Factorization for Soft Clustering of Territory Risk Analysis

Developing effective methodologies for territory design and relativity estimation is crucial in auto insurance rate filings and reviews. This study introduces a novel approach utilizing fuzzy clustering to enhance the design process of territories …