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Ananta Charan Ojha
Researcher at Centurion University of Technology and Management
Publications - 13
Citations - 32
Ananta Charan Ojha is an academic researcher from Centurion University of Technology and Management. The author has contributed to research in topics: Engineering & Knowledge extraction. The author has an hindex of 3, co-authored 10 publications receiving 30 citations. Previous affiliations of Ananta Charan Ojha include Jain University & Institute of Chartered Financial Analysts of India.
Papers
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Book ChapterDOI
Data Science and Big Data Analytics
TL;DR: Data science is an interdisciplinary field that deals with a methodical approach to process large volumes of data both structured and unstructured in nature as mentioned in this paper, the very objective is to analyze the data to uncover hidden patterns and extract actionable insights from the data for better managerial decision-making in an organization.
Proceedings ArticleDOI
Distributed Multi-agent System Architecture for Mobile Traders
TL;DR: A multi-agent system architecture for mobile traders is presented and it is claimed that it improves their mobility, intelligence and capability in agent-based e-commerce.
Book ChapterDOI
Data Leakage Detection and Prevention: Review and Research Directions
TL;DR: A systematic literature review considering a decade of the existing research efforts and makes a critical analysis thereof to highlight the issues and research gaps therein are made and important research directions in the field of data leakage detection and prevention are proposed.
Journal ArticleDOI
Prediction by Soft Computing, Planning, and Strategy Building of Aquatic Catch: Chilika Lagoon, Odisha, India
TL;DR: Mishra et al. as mentioned in this paper used linear regression, Multi Linear Perception (ANN), SMOorg (SVM), and the Random Forest algorithms (Weka Software) to predict the fish catch data of the Chilika lagoon for coming decade from 2020 to 2030.
Proceedings ArticleDOI
Fuzzy Linguistic Approach to Matchmaking in E-Commerce
TL;DR: A linguistic approach to compare and rank products based on fuzzy preferences, thus making e-commerce more pleasurable for both the buyer and the seller in a marketplace is presented.