Fang-Chun Lin
Master of Science Capstone Project, March 2022
[Proposal Report Final Presentation]
People are increasingly interested in fast and easy shopping at the supermarket. However, shopping for groceries can be a complex and stressful process that involves identifying, selecting, and purchasing required items for sustaining everyday lives. The grocery list is one of the most common solutions that assists in carrying out these activities. However, the task of creating and managing the lists for grocery shopping is often overlooked where the efforts and time spent are typically unseen and unrecognized. This study aims to bridge the gap by designing and developing a modern shopping list application that facilitates the process of creating and managing shopping lists for busy workers and assists them in locating products at nearby stores.
Existing shopping list applications lack an effective way to map shopping lists written in natural language to actual products in supermarkets. In addition, most mobile shopping assistants with search functionality rely on product information from single retailer and thus the recommended product lists are specific with limited options. It can be inconvenient and time-consuming for grocery shoppers who are in a hurry to locate specific products, especially when they are not familiar with the nearby stores. To address these issues, we designed a location-aware shopping list application that can locate products from nearby stores. 
With the API services and website information from supermarkets, it becomes possible to provide users with the option to choose from all the products available online from more than one retailer. Details of the relevant products are displayed in the search results, along with a navigation map showing all the nearby stores that carry the products. Additionally, once selected, when the product is available in a nearby store, a notification will be sent to the user. To streamline product selection process, our application supports ranking the product list based on the purchase history of the user.
Our implementation began with a proposed user story for typical grocery shopping, followed by a derived system specification to efficiently support the hypothetical shopper. We then designed and developed a multi-tier system to prototype the modern shopping list application based on the specified requirements. The evaluation results illustrated the completeness of the prototype system, including grocery list management, navigation map and location-aware notification. The results from a small-scale study showed that the personalized search ranking system achieved its initial success in integrating user preferences and the specified items in recommending personalized and appropriate products for different users. The results from our study contributed to the understanding of system and user interface requirements of a shopping list application. Our project and results can serve as an effective reference for developers and researchers in the field when developing similar applications.
