Input Method of a Context-Awareness using Cloud Computing Technology

• Main Authors: Kun-Yu Hsieh, 謝堃育
• Other Authors: Yen-Lin Chen
• Language: zh-TW
• Online Access: http://ndltd.ncl.edu.tw/handle/44g2u7

碩士 === 國立臺北科技大學 === 電資碩士在職專班研究所 === 103 === Recently the smartphone penetration in Chinese users is growing annually. In fact, there is about an increase of 10.1 million users (aged 12 and over) in the population of smartphone owners in Taiwan for the period June to December 2014. Recently, there are about 14.3 million smartphone or tablet holders in Taiwan, which is about 70% of population aged 12 and over. Besides, there is also about 73.5% of population of smartphone owner will install &;quot;social networking app&;quot; in their device. All of these statistic are obtained from the survey of Institute for Information Industry (III) &;quot;FIND&;quot; Research. However, iiMedia Research found that “Typing correct phonetic but wrong Chinese words” is up to 56.6% among the Chinese users. Chinese smart devices holders&;#39; population is continues to grow up, and the use of social networking applications are also accordingly growing in these users. Nonetheless, up to 56.6% of the users are hard to choose the correct word when typing on the Device. In this thesis, we present a novel context-aware input method considering time, place, weather, and festival as the contextual information and combining with cloud computing technique to effectively improve the word selection problem and provide better typing experiences for Chinese users. We demonstrate that our word selection algorithm which based on clustering and related candidates could decrease the character typing by 10% and decrease the candidates distance by 2.25%