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Title: An iPhone Application for a location-based recommendation system
Authors: Lam, Shuk Man
Department: Department of Computer Science
Issue Date: 2011
Supervisor: Supervisor: Dr. Chow, Ted Chi Yin; First Reader: Dr. Kwok, Lam For; Second Reader: Mr. Lee, Chan Hee
Abstract: During the semesters 2010-2011, as a Computer Science Student, I developed a Final Year Project with the topic of Location-Based Recommendation System on iPhone. This is a self prove of ability in the aspect of Computer Science. In this period of time, from design to management, from implementation to testing, from database to architecture, all are controlled in our hands. No wonder this is challenge but glad to have this meaningful achievement. For the final year project, my topic is Location-Based Recommendation System on iPhone, simply called the Restaurant Recommender. The subject area is the Mobile Computing [5]. The main concept of the Restaurant Recommender is to show out the top-k recommended restaurant to user with the methodology of Location-based Query and the Collaborative Filtering Process for Recommendations. How does the application runs is simply send the location information with the user identity with an iPhone, after the server receives the request, calculation with methodologies will be applied and retrieve the corresponding result back to the user via the mobile networking. The Location-based Querying, just as the title, it is talking about having the current location of the user, with some scientific calculations, the returns will be sorting with the calculation as a query. After that, we can apply the methodology of Collaborative Filtering. For the Collaborative Filtering, in Restaurant Recommender, we are using the Item-based Collaborative Filtering. The Item-based Collaborative Filtering is using the rating given by the user as the user preferences for the calculation. The idea of this theory is to find out the similarity of rate given by the users to certain items. In the Restaurant Recommender, of course the restaurant is defined as the items. After having the similarity of the items given by the users, corresponding similarity can be defined. Then the Weighted Sum acts as the recommended score comes out. The Recommended Score given to the user is showing the estimated rating given by the user after he/she tried that restaurant. The development tools are the Xcode, Interface Builder and iOS Simulator. The tools is developed by[11] in 2007. It is the SDK of iPhone application which providing professional development algorithm. The development tool is well prepared so that the application build in is very systematic and object oriented. Also database and application server were built up for data handling with mobile computing. With the user of the server, the data given by all the users can be synchronized.
Appears in Collections:Computer Science - Undergraduate Final Year Projects

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