Food Name Recognition Based Menu Generation and Food Recommendation System

• Main Authors: I-Chun Liu, 劉怡君
• Other Authors: Ming-Syan Chen
• Format: Others
• Language: en_US
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/64555268219248542312

碩士 === 臺灣大學 === 電信工程學研究所 === 98 === Web 2.0 is an important concept of World Wide Web and users are considered to be the core in Web 2.0 applications. In addition to browsing and retrieving information passively and unilaterally, users can post articles and share opinions freely on a Web 2.0 site. There are lots of platforms enabling users to publish and share their life experiences, such as travel, restaurant, and music. As the popularity of Web 2.0, people are getting used to search for user-generated data from the internet anytime and everywhere through handheld devices and universal high speed 3G mobile networks to get useful information and refer to others’ experiences. However, it is time-consuming to read and digest a large amount of data by ourselves. To alleviate the problem of spending a lot of time to read lots of restaurant reviews for figuring out which food is delicious, we propose a system which can return food recommendation list and restaurant related information automatically by blog mining technique. The blog mining method is first combined with food name extraction algorithm we proposed to generate food name list, and then sentiment analysis and social ranking are applied to calculate the ranking score of each food. To evaluate the performance of the system, three experiments are conducted. From the results of the experiments, we find that the food recommendation list is helpful for users and the accuracy of food name extraction is satisfactory.