Le Festin: Shop sign recognition assisted food recommendation system

摘要

As the popularity of smart phone, Web 2.0 data, and 3G mobile networks, people are getting used to search for information from the Internet anytime and everywhere. However, typing text query on mobile device and digesting a large number of retrieved user-generated data are both inconvenient for users. To overcome these troubles, we develop a wearable system, Le Festin, which is a shop sign recognition assisted food recommendation system. In Le Festin, food recommendation list and restaurant-related information can be easily obtained by just snapping restaurant signboard. The system is composed of two main techniques: Chinese character recognition (CCR) and blog mining. We integrate a powerful CCR algorithm which has the accuracy about 90% and propose a new blog mining method which is combined with food name extraction and sentiment analysis. By merging the above two functions, a convenient system is built.