THESIS
2014
xi, 40 pages : illustrations ; 30 cm
Abstract
With the popularity of smart mobile devices, the amount of mobile applications (or
simply called apps) has been increasing dramatically in recent years. However, due to low
threshold to enter app industry, app developers vary significantly with respect to their
expertise and reputation in the production of apps. Currently, there is no well-recognized
objective and effective means to profile app developers. As the mobile market grows, it
already gives rise to the problem of finding appropriate apps from the users' point of view.
In this thesis, we propose a framework called App Developer Inspector (ADI), which aims
to effectively profile app developers in aspects of their expertise and reputation in developing
apps. ADI is essentially founded on two underlying models: the App Dev...[
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With the popularity of smart mobile devices, the amount of mobile applications (or
simply called apps) has been increasing dramatically in recent years. However, due to low
threshold to enter app industry, app developers vary significantly with respect to their
expertise and reputation in the production of apps. Currently, there is no well-recognized
objective and effective means to profile app developers. As the mobile market grows, it
already gives rise to the problem of finding appropriate apps from the users' point of view.
In this thesis, we propose a framework called App Developer Inspector (ADI), which aims
to effectively profile app developers in aspects of their expertise and reputation in developing
apps. ADI is essentially founded on two underlying models: the App Developer
Expertise (ADE) model and the App Developer Reputation (ADR) model. In a nutshell,
ADE is a generative model that derives the latent expertise for each developer and ADR
is a model that exploits multiple features to evaluate app developers' reputation. Using
the app developer profiles generated in ADI, we study two new applications which respectively
facilitate app search and app development outsourcing. We conduct extensive experiments on a large real world dataset to evaluate the performance of ADI. The results
of experiments demonstrate the effectiveness of ADI in profiling app developers as well as
its boosting impact on these new applications.
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