Special Issues

Data Analytics for Business Intelligence: Trends and Applications

Submission Deadline: 15 March 2022 (closed) View: 3

Guest Editors

Dr. Mohammad Tabrez Quasim, University of Bisha, Saudi Arabia.
Dr. Surbhi Bhatia, King Faisal University, Saudi Arabia.
Dr. Parul Agarwal, Jamia Hamdard, New Delhi-62, India.
Dr. Asadullah Shaikh, Najran University, Saudi Arabia.

Summary

We are living in an era, where every task of ours is tracked, monitored, and supported using computing techniques and applications Organizations have always strived for obtaining maximum profit. But, the advent of techniques like Data Mining, and Data Analytics has served as a catalyst for intelligent ways of obtaining insight into the data and benefitting not only the consumer but also the producer. These also drive business intelligence, knowledge discovery, problem-solving, and have improved computing efficiency. The changes in the market are volatile yet predictable owing to the efficiency of computing techniques. The decision-making process of consumers for a product is characterized by past purchases and current trends. This overloaded data if effectively captured and analyzed can be a great insight for any business organization. Identifying the needs of a customer, strategic planning, and its implementation from major players. Methods, models, algorithms, and, systems process data (structured and unstructured), and extract knowledge with an ultimate goal to support effective decision making.

This special issue solicits trends and applications of data analytical techniques in our day-to-day lives. New models/ algorithms that shall enhance a user’s experience while providing the maximum benefit to the business and their processes are also welcome.



Keywords

• Data mining
• Data analytics and its applications for predictive modelling
• Recommender systems
• Artificial intelligence
• Data science theories and techniques
• Data visualisation
• Innovation and trends in data analytics
• Next-generation data-driven techniques for business processes

Published Papers


  • Open Access

    ARTICLE

    News Modeling and Retrieving Information: Data-Driven Approach

    Elias Hossain, Abdullah Alshahrani, Wahidur Rahman
    Intelligent Automation & Soft Computing, Vol.38, No.2, pp. 109-123, 2023, DOI:10.32604/iasc.2022.029511
    (This article belongs to the Special Issue: Data Analytics for Business Intelligence: Trends and Applications)
    Abstract This paper aims to develop Machine Learning algorithms to classify electronic articles related to this phenomenon by retrieving information and topic modelling. The Methodology of this study is categorized into three phases: the Text Classification Approach (TCA), the Proposed Algorithms Interpretation (PAI), and finally, Information Retrieval Approach (IRA). The TCA reflects the text preprocessing pipeline called a clean corpus. The Global Vectors for Word Representation (Glove) pre-trained model, FastText, Term Frequency-Inverse Document Frequency (TF-IDF), and Bag-of-Words (BOW) for extracting the features have been interpreted in this research. The PAI manifests the Bidirectional Long Short-Term Memory (Bi-LSTM)… More >

Share Link