Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/1234
Title: WoKnack – A Professional Social Media Platform for Women Using Machine Learning Approach
Authors: Shanmugarajah, S.
Praisoody, A.
Rakib Uddin, M.D.
Keywords: Algorithms
clustering
Machine Learning
Natural Language Processing
Issue Date: 9-Dec-2021
Publisher: 2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT
Abstract: Today’s generation is heavily influenced by social media. However, most users decline to post their abilities on these platforms for a variety of reasons, including security, a lack of basic skills, and a lack of knowledge about the various skill sets. It's understandable that women face many security risks on these platforms. WoKnack is a professional social networking platform dedicated to women. This opens opportunities for women to demonstrate their abilities and teach other women. This paper targets onfunctionalities like registration limited to female users, skill categorization, post verification and privacy preservation. Facial image, identification document and Voice related gender verification done using machine learning approaches to identify thegender before registration. Accuracy of 91% gained during the process. Skills have been categorized using Natural language processing and post verification done based on these categories. Usage of the best accurate algorithm gives an accuracy of 94% during this process. In order to preserve the privacy of users Data anonymization, skill and location clustering have been added to the system.
URI: http://rda.sliit.lk/handle/123456789/1234
ISSN: 978-1-6654-0862-2/21
Appears in Collections:3rd International Conference on Advancements in Computing (ICAC) | 2021
Department of Computer Science and Software Engineering-Scopes
Research Papers - Dept of Computer Science and Software Engineering

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