Z
Zuraini Zainol
Researcher at National Defence University of Malaysia
Publications - 46
Citations - 208
Zuraini Zainol is an academic researcher from National Defence University of Malaysia. The author has contributed to research in topics: Tacit knowledge & Ontology (information science). The author has an hindex of 7, co-authored 42 publications receiving 153 citations. Previous affiliations of Zuraini Zainol include National Defense University & National Defence University, Pakistan.
Papers
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Proceedings ArticleDOI
Generic context ontology modelling: A review and framework
Zuraini Zainol,Keiichi Nakata +1 more
TL;DR: The goal of the proposed framework is to represent context information in general, which can be implemented to facilitate common context representation, context matching, and context reasoning.
Journal ArticleDOI
A survey on presentation attack detection for automatic speaker verification systems: State-of-the-art, taxonomy, issues and future direction
Choon Beng Tan,Mohd Hanafi Ahmad Hijazi,Norazlina Khamis,Puteri N. E. Nohuddin,Zuraini Zainol,Frans Coenen,Abdullah Gani +6 more
TL;DR: A systematic analysis of the state-of-the-art voice PAD systems to promote further advancement in this area and to identify areas that require additional research.
Journal ArticleDOI
VisualUrText: A Text Analytics Tool for Unstructured Textual Data
TL;DR: This paper discusses the development of text analytics tool that is proficient in extracting, processing, analyzing the unstructured text data and visualizing cleaned text data into multiple forms such as Document Term Matrix (DTM), Frequency Graph, Network Analysis Graph, Word Cloud and Dendogram.
Text analytics of unstructured textual data: A study on military peacekeeping document using R text mining package
TL;DR: A technique of text analytics on peacekeeping documents to discover significant text patterns exist in the documents to found a framework that consists of 3 stages: data collection, document preprocessing and text analytics and visualization.
Book ChapterDOI
Association Rule Mining Using Time Series Data for Malaysia Climate Variability Prediction
TL;DR: The proposed framework is developed to provide a better approach in understanding how ARM can be used to find meaningful patterns in the climate data and generate rules that can be use to build a prediction model.