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Intelligent Mobile Maid Matching Using Similarity Search

Ong, Shu Xian (2020) Intelligent Mobile Maid Matching Using Similarity Search. Final Year Project, UTAR.

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    Abstract

    Intelligent Mobile Maid Matching using Similarity Search is a mobile application that allows maid seekers to search for an ideal maid by provide the maid matching function using similarity measures. The purpose of having this idea is because nowadays the maid seekers are lacked of a useful platform to find a quality maid. Moreover, all the applications that had been reviewed are using a simple matching method to search for maids. Thus, when performing searching, the result is very limited, especially when a user searches maids with more preferences. This application developed in this project is only available in Android Platform. Firebase is used as the application database that connects with a real-time database and allows user authentication process. The system development methodology used for this project is the Prototyping model. Therefore, the application can adapt to the environment changes when implementing the application. Functions of the application are implemented according to the result of the questionnaire. In this project, similarity measures such as Euclidean distance, Manhattan distance, Minkowski distance, Jaccard coefficient and cosine similarity will be studied. The most suitable method will be tested through usability testing to find out which method is closest to the ideal maid of maid seekers. According to the result of usability testing, the similarity measure that applied to the searching function is Jaccard Coefficient. This application is developed successfully and pass all the testing. In a nutshell, this project is a successful project that has achieved all the project’s objectives.

    Item Type: Final Year Project / Dissertation / Thesis (Final Year Project)
    Subjects: Q Science > QA Mathematics > QA76 Computer software
    Divisions: Lee Kong Chian Faculty of Engineering and Science > Bachelor of Science (Hons) Software Engineering
    Depositing User: Sg Long Library
    Date Deposited: 12 Jun 2021 03:31
    Last Modified: 12 Jun 2021 03:31
    URI: http://eprints.utar.edu.my/id/eprint/4087

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