STM Journals Peer-reviewed research from Consortium e-Learning Network

2 publications

  • Published Subscription Review Article

    Using Machine Learning for Key phrase Extraction in Digital Libraries

    By Neha Sahu, Rizwan Arif

    Abstract: Machine learning has revolutionized various aspects of information retrieval, including key phrase extraction in digital libraries. Key phrase extraction is crucial for summarizing and categorizing vast amounts of textual data, enabling efficient search and retrieval processes. This study explores the application of machine learning techniques for automatic key phrase extraction in digital libraries. We review various supervised and unsupervised learning algorithms, including deep learning models, that are employed to identify …

    Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 8–13 Read article

  • Published Subscription Review Article

    Revolutionizing Anti-Allergy Medications: A Comprehensive Review of Target Discovery and Medicinal Chemistry

    By Neha Sahu, Rizwan Arif

    Abstract: Above the past few decades, the prevalence of allergy illnesses has been steadily rising, impacting 20–30% of the world's population. Multiple targets are involved in allergic reactions to infections of the skin, digestive tract, and respiratory system. Developing medications with a good curative efficacy and minimal side effects while utilizing novel multi-targets and processes in accordance with the clinical features of various allergic populations and allergens is the primary challenge …

    Published in International Journal of Advance in Molecular Engineering · Vol. 1, Issue 1, 2023 · pp. 49–54 Read article

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