Effectiveness of Context-Aware Character Input Method for Mobile Phone Based on Artificial Neural Network

Opportunities and needs are increasing to input Japanese sentences on mobile phones since performance of mobile phones is improving. Applications like E-mail, Web search, and so on are widely used on mobile phones now. We need to input Japanese sentences using only 12 keys on mobile phones. We have proposed a method to input Japanese sentences on mobile phones quickly and easily. We call this method number-Kanji translation method. The number string inputted by a user is translated into Kanji-Kana mixed sentence in our proposed method. Number string to Kana string is a one-to-many mapping. Therefore, it is difficult to translate a number string into the correct sentence intended by the user. The proposed context-aware mapping method is able to disambiguate a number string by artificial neural network (ANN). The system is able to translate number segments into the intended words because the system becomes aware of the correspondence of number segments with Japanese words through learning by ANN. The system does not need a dictionary. We also show the effectiveness of our proposed method for practical use by the result of the evaluation experiment in Twitter data

Effectiveness of Ambiguity-aware Web Search Algorithm for Mobile Phone

We have proposed a fast Web search method for mobile terminals such as mobile phones. We need to input some terms for Web searching usually. A full QWERTY keyboard is used for input of terms. It is not easy to press the intended key because the key size is small on a mobile phone. Moreover, a user needs to press a few keys per Kana character since one Kana character generally consists of a few alphabets in Japanese. A flick input method has been developed and is used for input of Kana-characters on a touch panel of a smart phone. Because the method needs only about 12 keys, the key size is larger than a full QWERTY keyboard. However, the flick operation is not easy. In our proposed method, a user is able to easily input terms because our proposed method needs only one keystroke per character using only 12 keys without flick operations. Character-strings inputted by the user are ambiguous because each string corresponds to not only the intended term but also other terms. However, the ambiguous strings are not translated into the intended terms in our proposed method. The system based on our proposed method directly searches Web pages by the ambiguous strings and outputs the searched result based on co-occurrence. Thus, we are able to find the intended Web page on a mobile phone rapidly and easily. In the result of the evaluation experiment, the Web search accuracy was 80[%] and the system was able to search Web pages by the correct terms at 90[%]. It was proved that our proposed method was effective for mobile terminals