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Your search keyword '"Sankhavara, J."' showing total 6 results
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6 results on '"Sankhavara, J."'

1. Adapting support vector optimisation algorithms to textual gender classification.

Author

Gomez, Javier, Alfaro, Cesar, Ortega, Felipe, Moguerza, Javier M., Algar, Maria Jesus, and Moreno, Raul

Abstract

In this paper, we focus on the problem of determining the gender of the person described in a biographical text. Since support vector machine classifiers are well suited for text classification tasks, we present a new stopping criterion for support vector optimisation algorithms tailored to this problem. This new approach exploits the geometric properties of the vector representation of such content. An experiment on a set of English and Spanish biographical articles retrieved from Wikipedia illustrates this approach and compares it to other machine learning classification algorithms. The proposed method allows real-time classification algorithm training. Moreover, these results confirm the advantage of leveraging additional gender information in strongly inflected languages, like Spanish, for this task. [ABSTRACT FROM AUTHOR]

Published
2024
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5. Intelligent Systems Design and Applications : Deep Learning, Volume 2

Author

Ajith Abraham, Anu Bajaj, Thomas Hanne, Tzung-Pei Hong, Ajith Abraham, Anu Bajaj, Thomas Hanne, and Tzung-Pei Hong

Subjects
Computational intelligence, Artificial intelligence
Abstract

This book highlights recent research on intelligent systems and nature-inspired computing. It presents 47 selected papers focused on Deep Learning from the 23rd International Conference on Intelligent Systems Design and Applications (ISDA 2023), which was held in 5 different cities namely Olten, Switzerland; Porto, Portugal; Kaunas, Lithuania; Greater Noida, India; Kochi, India, and in online mode. The ISDA is a premier conference in the field of artificial intelligence, and the latest installment brought together researchers, engineers, and practitioners whose work involves intelligent systems and their applications in industry. ISDA 2023 had contributions by authors from 64 countries. This book offers a valuable reference guide for all scientists, academicians, researchers, students, and practitioners in the field of artificial intelligence and deep learning.

Published
2024

6. Text Mining Approaches for Biomedical Data

Author

Aditi Sharan, Nidhi Malik, Hazra Imran, Indira Ghosh, Aditi Sharan, Nidhi Malik, Hazra Imran, and Indira Ghosh

Subjects
Data mining, Application software
Abstract

The book'Text Mining Approaches for Biomedical Data'delves into the fascinating realm of text mining in healthcare. It provides an in-depth understanding of how Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing healthcare research and patient care. The book covers a wide range of topics such as mining textual data in biomedical and health databases, analyzing literature and clinical trials, and demonstrating various applications of text mining in healthcare. This book is a guide for effectively representing textual data using vectors, knowledge graphs, and other advanced techniques. It covers various text mining applications, building descriptive and predictive models, and evaluating them. Additionally, it includes building machine learning models using textual data, covering statistical and deep learning approaches. This book is designed to be a valuable reference for computer science professionals, researchers in the biomedical field, and clinicians. It provides practical guidance and promotes collaboration between different disciplines. Therefore, it is a must-read for anyone who is interested in the intersection of text mining and healthcare.

Published
2024

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