This thesis presents the design and implementation of I-Shop, a context-aware, shopping smartphone application designed to provide shoppers with relevant advertisements for product and services available in close proximity. We argue that current context-aware mobile applications exhibit significant limitations in the following domains: (1) use of context, (2) invasion of privacy, (3) spam management, and (4) platform dependency. The proposed context model attempts to tackle these shortcomings by exploiting available contextual information from social media networks such as Facebook. Our goal is to use a user’s personal information, such as their native language and personal interests, to direct the most relevant advertisements to them. To alleviate any privacy issues, a user’s personal information is never sent out to any back-end services and only apply the filters locally. In addition, unlike most other predictive approaches that track the user’s location history, we follow a reactive approach which triggers only when the user is close to a shopping area. When a user arrives to a particular shopping area, the application asks whether she wishes to view any advertisements of local products and services. Upon approval, the application retrieves deals on products including services sorted by domain from databases, such as Groupon and our custom extended deals database. Finally, the application filters the retrieved data according to personal interests and then displays the results.
As a proof of concept, we designed and implemented the I-Shop prototype application. We built I-Shop as a hybrid application using IBM’s state-of-the-art Worklight infrastructure. This approach lets developers optimize their time and effort; enabling a “write once, deploy everywhere” development model that not only reduces development costs but also increases application performance by providing a combination of native and web capabilities. In addition, I-Shop also leverages several features offered by the IBM Worklight infrastructure including cross-platform support, direct update, internalization, and integration of third-party libraries and toolkits. / Graduate
Identifer | oai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/4479 |
Date | 28 February 2013 |
Creators | Jain, Ishita |
Contributors | Muller, Hausi A. |
Source Sets | University of Victoria |
Language | English, English |
Detected Language | English |
Type | Thesis |
Rights | Available to the World Wide Web |
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