Date of Graduation
8-2013
Document Type
Thesis
Degree Name
Master of Science in Computer Science (MS)
Degree Level
Graduate
Department
Computer Science & Computer Engineering
Advisor/Mentor
Banerjee, Nilanjan
Committee Member
Gauch, Susan E.
Second Committee Member
Thompson, Craig W.
Keywords
Applied sciences; Information retreival; Interaction; Personalization; Recommendation; Travel
Abstract
Trip planning is a time consuming task that most people do before going to any destination. Traveltant is an intelligent system that analyzes a user's Social network and suggests a complete trip plan detailed for every single day based on the user's interests extracted from the Social network. Traveltant also considers the interests of friends the user interacts with most by building a ranked friends list of interactivity, and then uses the interests of those people in this list to enrich the recommendation results. Traveltant provides a smooth user interface through a Windows Phone 7 application while doing most of the work in a backend cloud service. To evaluate the results of the system, volunteers have rated the personalized results better than those results from only common factors such popularity and rating.
Citation
Alfarhood, S. D. (2013). Traveltant: Social Interaction Based Personalized Recommendation System. Graduate Theses and Dissertations Retrieved from https://scholarworks.uark.edu/etd/805
Included in
Artificial Intelligence and Robotics Commons, Graphics and Human Computer Interfaces Commons
