K-means clustering and visualizing of significant words prototype for crowdsourced relationship comments / Muhammad Syafiq Mastor

Having a love relationship is normal to the humankind. It is the most common emotion that human has. Nevertheless, conflicts often occur throughout the relationship. Conflicts occur due to lack of understanding between partners. The most common conflicts are the misunderstanding women‟s feeling from...

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Main Author:	Mastor, Muhammad Syafiq
Format:	Thesis
Language:	English
Published:	2015
Subjects:	Real-time programming Evolutionary programming (Computer science). Genetic algorithms
Online Access:	http://ir.uitm.edu.my/id/eprint/14569/ http://ir.uitm.edu.my/id/eprint/14569/1/TD_MUHAMMAD%20SYAFIQ%20MASTOR%20CS%2015_5.pdf

id	uitm-14569
recordtype	eprints
spelling	uitm-145692016-08-23T03:28:54Z http://ir.uitm.edu.my/id/eprint/14569/ K-means clustering and visualizing of significant words prototype for crowdsourced relationship comments / Muhammad Syafiq Mastor Mastor, Muhammad Syafiq Real-time programming Evolutionary programming (Computer science). Genetic algorithms Having a love relationship is normal to the humankind. It is the most common emotion that human has. Nevertheless, conflicts often occur throughout the relationship. Conflicts occur due to lack of understanding between partners. The most common conflicts are the misunderstanding women‟s feeling from their partners. In spite of the conflicts, men would do anything that is possible to understand their partners in order to save their relationship, either going for relationship counselling, asking for opinion in social media, learn from other‟s experience or even seeking advice from family and friends. However, these conventional methods have their disadvantages. Therefore, this research proposed a K-means clustering and visualizing of significant words prototype for crowdsourced relationship comments. Crowdsourcing is the practice of obtaining needed content by asking contributions from a batch of people and typically from the online community. The comments are clustered using K-Means algorithm and visualized using scatter plot. Each plot represents a comment where each comment are coloured according to their cluster and significant words. Compared to the existing relationship website, most of the website did not give freedom for user to browse on comments that have same ideas as they are. Most of the website force user to follow the highly rated advice which may not applicable to the user. This project gives freedom for users to choose which comments or advice that is suitable for their situation as well as to give comments or advice anonymously. This project also identifies the common issues or topics has been discussed in the comments. 2015 Thesis NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/14569/1/TD_MUHAMMAD%20SYAFIQ%20MASTOR%20CS%2015_5.pdf Mastor, Muhammad Syafiq (2015) K-means clustering and visualizing of significant words prototype for crowdsourced relationship comments / Muhammad Syafiq Mastor. Degree thesis, Universiti Teknologi MARA.
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Teknologi MARA
building	UiTM Institutional Repository
collection	Online Access
language	English
topic	Real-time programming Evolutionary programming (Computer science). Genetic algorithms
spellingShingle	Real-time programming Evolutionary programming (Computer science). Genetic algorithms Mastor, Muhammad Syafiq K-means clustering and visualizing of significant words prototype for crowdsourced relationship comments / Muhammad Syafiq Mastor
description	Having a love relationship is normal to the humankind. It is the most common emotion that human has. Nevertheless, conflicts often occur throughout the relationship. Conflicts occur due to lack of understanding between partners. The most common conflicts are the misunderstanding women‟s feeling from their partners. In spite of the conflicts, men would do anything that is possible to understand their partners in order to save their relationship, either going for relationship counselling, asking for opinion in social media, learn from other‟s experience or even seeking advice from family and friends. However, these conventional methods have their disadvantages. Therefore, this research proposed a K-means clustering and visualizing of significant words prototype for crowdsourced relationship comments. Crowdsourcing is the practice of obtaining needed content by asking contributions from a batch of people and typically from the online community. The comments are clustered using K-Means algorithm and visualized using scatter plot. Each plot represents a comment where each comment are coloured according to their cluster and significant words. Compared to the existing relationship website, most of the website did not give freedom for user to browse on comments that have same ideas as they are. Most of the website force user to follow the highly rated advice which may not applicable to the user. This project gives freedom for users to choose which comments or advice that is suitable for their situation as well as to give comments or advice anonymously. This project also identifies the common issues or topics has been discussed in the comments.
format	Thesis
author	Mastor, Muhammad Syafiq
author_facet	Mastor, Muhammad Syafiq
author_sort	Mastor, Muhammad Syafiq
title	K-means clustering and visualizing of significant words prototype for crowdsourced relationship comments / Muhammad Syafiq Mastor
title_short	K-means clustering and visualizing of significant words prototype for crowdsourced relationship comments / Muhammad Syafiq Mastor
title_full	K-means clustering and visualizing of significant words prototype for crowdsourced relationship comments / Muhammad Syafiq Mastor
title_fullStr	K-means clustering and visualizing of significant words prototype for crowdsourced relationship comments / Muhammad Syafiq Mastor
title_full_unstemmed	K-means clustering and visualizing of significant words prototype for crowdsourced relationship comments / Muhammad Syafiq Mastor
title_sort	k-means clustering and visualizing of significant words prototype for crowdsourced relationship comments / muhammad syafiq mastor
publishDate	2015
url	http://ir.uitm.edu.my/id/eprint/14569/ http://ir.uitm.edu.my/id/eprint/14569/1/TD_MUHAMMAD%20SYAFIQ%20MASTOR%20CS%2015_5.pdf
first_indexed	2023-09-18T22:51:55Z
last_indexed	2023-09-18T22:51:55Z
_version_	1777417601318649856

K-means clustering and visualizing of significant words prototype for crowdsourced relationship comments / Muhammad Syafiq Mastor

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