LocoLit: a real-time view of local attractions

Abstract

This report describes the development of a location-based restaurant finding application, with a machine learning bases classification capability for summarizing user rating. The main idea behind the application is to allow the user access rating, images and videos uploaded in real- time before deciding to visit that respective location. The goal of tis implementation is to apply information integration- especially geolocation, video data and text bases rating analysis – to develop a usable, responsive information retrieval and access system for area restaurant and user review. There is a huge tradeoff in terms of information gain and time spent viewing a certain page. It is increasingly becoming important to consolidate information about a place into one tap. A simple online search may provide data about time and location but does not provide the user a visual representation of what is going on. The purpose of this project is to develop an application to reduce this technical gap and to serve the cliental of local businesses and patrons. The main motivation was to create a minimalistic application that encompassed all the needs a young adult would require making day-to-day decisions. It also increases transparency and drastically saves users the cost of physical presence by providing summative information about local businesses, including georeferenced videos and other users written review.