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Advanced Strategy for MMO using Interactive Visualisation

Sarda, Swapnil (2019) Advanced Strategy for MMO using Interactive Visualisation. Masters thesis, Dublin, National College of Ireland.

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Abstract

Massive multiplayer online games are widely popular and fiercely competitive. Currently in-game statistics are limited to summary in a tabular format. Players invest many hours in honing their skills and have no clear view on which attributes of the game they are better at or need improvement. This study proposes to build a custom visualisation that would display the winning patterns in the game and also aid in designing a game winning strategy. Player data is fetched using PUBG API and a Kaggle data set is also used in this research. For feature selection, Boruta algorithm is applied to the dataset. The frequently occurring patterns are found using Apriori algorithm. The custom visualisation is built using D3 library in JavaScript. Frequently occurring patterns are generated using Apriori algorithm with support values up to 0.998. The visualisations clearly show the different subsets found in the data. The research successfully reveals interesting patterns which can be used to win the game. This paper describes the methodology which can be extended to data sets from different games and achieve similar results, and suggests improvements which can be made to achieve higher immersion rate in the game.

Item Type: Thesis (Masters)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science

Q Science > QA Mathematics > Computer software
T Technology > T Technology (General) > Information Technology > Computer software

G Geography. Anthropology. Recreation > GV Recreation Leisure > Games and Amusements > Computer Games. Video Games.
Divisions: School of Computing > Master of Science in Data Analytics
Depositing User: CAOIMHE NI MHAICIN
Date Deposited: 14 Oct 2019 09:13
Last Modified: 14 Oct 2019 09:13
URI: http://trap.ncirl.ie/id/eprint/3861

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