Mobile applications quality evaluation according to ISO 9126 quality model using Naïve Bayes

QR Code

Mobile applications quality evaluation according to ISO 9126 quality model using Naïve Bayes

In this study a tool to evaluate the quality of mobile applications from the user provided reviews in Google Play app store is developed. ISO 9126 quality in use part is used as the quality model. We used a supervised Machine learning technique to undertake this project. Specifically, Weka Naïve Bay...

Full description

Bibliographic Details
Main Author:	Ali, Jabir Abdullahi
Format:	Thesis
Language:	English
Published:	2018
Subjects:	Mobile apps - Evaluation
Online Access:	http://psasir.upm.edu.my/id/eprint/69053/ http://psasir.upm.edu.my/id/eprint/69053/1/FSKTM%202018%2060%20IR.pdf

Similar Items

Addressing usability quality attribute in techno-spiritual mobile application
by: Abdul Wahab, Ahairul Afza
Published: (2015)

Porting process model for mobile application
by: Rajadorai @ Rajoo, Kesava Pillai
Published: (2017)

Usability evaluation framework for mobile apps
by: Rahmat, Hazwani
Published: (2020)

Development of type 1 diabetes mellitus blood glucose level simulation mobile application
by: Mohamad Akbar, Asyraf Aiman
Published: (2020)

Effectiveness of mobile career competencies intervention for Malaysian public managers
by: Ho, Hsin Hung
Published: (2021)

Factors influencing continuance of usage intention towards a gamified e-quiz mobile application among Malaysian higher learning students
by: Roslan, Rosfuzah
Published: (2023)

Digital forensics framework for investigating client cloud storage applications on smartphones
by: Daryabar, Farid
Published: (2015)

Dynamic Task Offloading Algorithm for optimising IoT network quality of service in the Mobile-Fog-Cloud System
by: Nwogbaga, Nweso Emmanuel
Published: (2023)

Responsible practices in the wild: an actor-network perspective on mobile apps in learning as translation(s)
by: Laasch, Oliver, et al.
Published: (2019)

Proportionate methods for evaluating a simple digital mental health tool
by: Davies, Eleanor Bethan, et al.
Published: (2017)

Inferring User Needs & Tasks from App Usage Interactions
by: Tian, Yuan
Published: (2022)

Guidelines on Interaction: An exploration into implementing secondary screen experiences on mobile devices
by: Bradford, Jordan
Published: (2013)

Given the barriers and complexities of developing applications for Clinical Commissioners within the NHS, what could be the killer application?
by: Steele, Diane
Published: (2013)

Fun and useful apps: female identity construction and social connectedness using the mobile phone
by: Rickard, S., et al.
Published: (2012)

Factors affecting blind mobility
by: Clark-Carter, David
Published: (1985)

E-service quality model for assessing customer satisfaction of mobile banking application
by: Owuamanam, Jude Ndubuisi
Published: (2021)

Consuming apps: The Australian woman’s slow appetite for apps
by: Rickard, S., et al.
Published: (2012)

Smartphone apps for the self-management of low back pain: a systematic review
by: Machado, Gustavo C., et al.
Published: (2017)

Exploring the potential facilitators and barriers of using personal data collected by sensor-based technologies to promote health and well-being.
by: Venancio Santos, Elaine Conceicao
Published: (2023)

Developing a mobile app as a communication aid for the Deaf people of Cyprus
by: Pieri, Katerina
Published: (2017)

Mobility and quality of service in wireless multicast infrastructure
by: Singh, Jaipal, et al.
Published: (2005)

Application of Bay’ Al-Salam in e-commerce transaction / Norhanisah Nordin
by: Nordin, Norhanisah
Published: (2019)

Mobile Trainer Organizer Application
by: Armi Riffa, Mohamad Faiz, et al.
Published: (2020)

A "non-parametric" version of the naive Bayes classifier
by: Soria, Daniele, et al.
Published: (2011)

A regularized attribute weighting framework for naive bayes
by: Wang, Shihe, et al.
Published: (2020)

Naive bayes-guided bat algorithm for feature selection.
by: Taha, Ahmed Majid, et al.
Published: (2013)

Babysitter Finder Mobile Application with Geofencing
by: Izul Murad, Siti Nursyazwani, et al.
Published: (2020)

Comparison of SVM, Naive Bayes, and ELM Models in Plant Growth Classification
by: M., Muflih, et al.
Published: (2024)

An evaluation of mobile application for dyslexic student developed based on Golden Rules design principle / Wan Nur Syahira Wan Othman
by: Wan Othman, Wan Nur Syahira
Published: (2015)

On the design of mobile applications for Geometry
by: Fabian, Khristin
Published: (2010)

Bacteria identification from microscopic morphology using naïve bayes
by: Mohamad, Noor Amaleena, et al.
Published: (2014)

Prediction of Diabetes Using Hidden Naïve Bayes: Comparative Study
by: Al-Hameli, Bassam Abdo, et al.
Published: (2021)

A Naïve-Bayes classifier for damage detection in engineering materials
by: Addin, O., et al.
Published: (2007)

License plate localization using a Naive Bayes classifier
by: Abdul Halin, Alfian, et al.
Published: (2013)

Quality of service in mobile IP networks with parametric multi-channel routing algorithms based on linear programming approach
by: Gholizadeh, Somayyeh
Published: (2018)

Smart Catalogue Mobile Application (SCM) with Beacon Device
by: Odzaly, Edzreena Edza Binti, et al.
Published: (2020)

Korean Learning Mobile Application for UiTM Students
by: Rosland, Siti Nurqamarina, et al.
Published: (2020)

Software quality evaluation through maintenance processes
by: Al-Badareen, Anas Bassam, et al.
Published: (2010)

Common Mobile Learning Characteristics-An Analysis Of Mobile Learning Models And Frameworks
by: Imtinan, Umera, et al.
Published: (2013)

Promoting Independence in Dementia – Changing Lifestyles & Improving Outcomes: RE-AIM Study of The PRIDE Self-Management App
by: Lee, Abigail Rebecca
Published: (2023)