myDeal: The Context-Aware Urban Shopping Assistant

• Main Authors: MURALIDHARAN, Kartik, GOTTIPATI, Swapna, Jing JIANG, RAMASUBBU, Narayan, BALAN, Rajesh Krishna
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2012
• Subjects: Databases and Information Systems; Sales and Merchandising; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/3241; https://ink.library.smu.edu.sg/context/sis_research/article/4243/viewcontent/8905391.pdf
• Institution: Singapore Management University

A common problem in large Urban cities, of the sort seen in Asia, is the huge number of retail options available in the city. In particular, it is not uncommon to find multiple malls, each with hundreds of stores inside, just a short distance from each other in almost every part of these cities. These factors make it incredibly hard for consumers to identify stores of interest to them in any particular mall.In response, a number of shopping assistance applications have been created for mobile phones.However, these applications mostly just allow users to know which stores are where or to find promotions on specific items. What is missing is a system that factors in a user’s shopping preferences and automatically tells them which stores are most likely to capture their interest.The key challenge in this system is twofold; 1) building a matching algorithm that can combine user preferences with fairly unstructured deals and store information to generate a final rank ordered list, and 2) designing a mobile user interface that can display a large amount of deal and shopping information to the user in an easy intuitive way.