Framework of Knowledge-Based System for United Nations Peacekeeping Operations Using Data Mining Technique

This paper presents the framework of “Knowledge-Based System” to assist the Malaysian United Nations Military Observers (UNMO) in conducting the United Nations (UN) peacekeeping operations at the deployment country. Further, a suitable data mining technique (e.g. clustering or association rule mining) will be applied to extract interesting and beneficial knowledge including hidden patterns from various sources related to the peacekeeping mission that is required by UNMO. The proposed system will be integrated into the rugged tablet or any pervasive equipment that is used for the peacekeeping operations. Here, the knowledge-based system can be used to assist the UNMO in decision-making when facing all possible scenarios while conducting the peacekeeping operations.

[1]  Jay R. Galbraith Organizational Design Challenges Resulting from Big Data , 2014 .

[2]  Hui Ning,et al.  Temporal Association Rules in Mining Method , 2006, First International Multi-Symposiums on Computer and Computational Sciences (IMSCCS'06).

[3]  Omar Zakaria,et al.  Text analytics of unstructured textual data: A study on military peacekeeping document using R text mining package , 2017 .

[4]  Kavitha Rani Balmuri,et al.  Hybrid Approach for Prediction of Cardiovascular Disease Using Class Association Rules and MLP , 2016 .

[5]  Deborah Ribeiro Carvalho,et al.  TEMPORAL ASSOCIATION RULES IN BREAST CANCER , 2016 .

[6]  Durga Toshniwal,et al.  A data mining framework to analyze road accident data , 2015, Journal of Big Data.

[7]  S. N. Sivanandam,et al.  Introduction to Data Mining and its Applications , 2006, Studies in Computational Intelligence.

[8]  H Du,et al.  Data Mining Techniques and Applications , 2010 .

[9]  Das Amrita,et al.  Mining Association Rules between Sets of Items in Large Databases , 2013 .

[10]  Zuraini Zainol,et al.  Keyword based Clustering Technique for Collections of Hadith Chapters , 2016 .

[11]  Ritu Ganda Knowledge Discovery from Database using an Integration of Clustering and Association Rule Mining , 2013 .

[12]  Zuraini Zainol,et al.  Trend cluster analysis using self organizing maps , 2014, 2014 4th World Congress on Information and Communication Technologies (WICT 2014).

[13]  Angela Siew Hoong Lee,et al.  A case study in knowledge acquisition for logistic cargo distribution data mining framework , 2018 .

[14]  Omar Zakaria,et al.  Document Clustering in Military Explicit Knowledge: A Study on Peacekeeping Documents , 2017, IVIC.

[15]  Nur Ashikin Harun,et al.  The Application of Apriori Algorithm in Predicting Flood Areas , 2017 .

[16]  Syahaneim Marzukhi,et al.  Discovering “interesting” keyword patterns in Hadith chapter documents , 2016, 2016 International Conference on Information and Communication Technology (ICICTM).

[17]  Ion Lungu,et al.  Improving Decision Support Systems with Data Mining Techniques , 2012 .

[18]  Arun K Pujari,et al.  Clustering Techniques in Data Mining—A Survey , 2001 .

[19]  Mohd Naz'ri Mahrin,et al.  Improving the accuracy of collaborative filtering recommendations using clustering and association rules mining on implicit data , 2017, Comput. Hum. Behav..

[20]  Zuraini Zainol,et al.  Association Rule Mining Using Time Series Data for Malaysia Climate Variability Prediction , 2017, IVIC.