Relationship Analysis between User’s Contexts and Real Input Words through Twitter Yutaka Arakawa, Shigeaki Tagashira and Akira Fukuda Graduate School of Information Science and Electrical Engineering, Kyushu University, Fukuoka, Japan 744, Motooka, Nishi-ku, Fukuoka, Fukuoka, JAPAN, 819-0395 Email: arakawa, shigeaki,
[email protected] Abstract—In this paper, we propose a method to evaluate such as location, presence and time. We mainly focus on effectiveness of our proposed context-aware text entry by using how to make dictionary dynamically among above-mentioned Twitter. We focus on ”geo-tagged” public tweets because they three component of predictive transform in text entry. The include user’s important contexts, real location and time. We also focus on TV program listing because 50% traffic of iPhone reason is that the word not included in the dictionary cannot in Japan is generated from our home, in which I often tweets in be recommended, and we are not specialists of philolog- watching a TV. Cyclical collecting system based on Streaming API ical syntactic parsing. In our proposed system, based on and Search API of Twitter is proposed for gathering the target user’s current contexts, the dictionary in the mobile phone tweets efficiently. In order to find the relationship between user’s is updated periodically in cooperation with the dictionary contexts and really used words, we compare really-tweeted words with words obtained from Local Search API of Yahoo! Japan that creation server on the Internet, which generates user’s current is used for our context-aware text entry and words obtained from dictionary dynamically by using several public Web APIs.