User dictionary merge for enhancing smart phone auto prediction

Abhijit Prakash Bhatnagar, A. Sehgal
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Abstract

Smart phone keyboards render a device based text prediction system which is usually built around the keyboard application under use. Withal, they infer a restriction since the techniques used in the system are mostly confined to device in scope. In this paper, we formulate a method to merge various user dictionaries so as to increase keystroke savings on average for a smart phone user. The method described in this paper takes into account relations among a multitude of users, and applies it to merge the user dictionary at a level derived from the relations. We show an increase in percentage keystroke savings for experimental data by applying this algorithm to context insensitive variation of word prediction.
用户字典合并,增强智能手机自动预测
智能手机键盘提供了一个基于设备的文本预测系统,该系统通常是围绕正在使用的键盘应用程序构建的。同时,他们推断出一个限制,因为系统中使用的技术大多局限于设备范围内。在本文中,我们制定了一种合并各种用户字典的方法,以增加智能手机用户的平均按键节省。本文所描述的方法考虑了众多用户之间的关系,并将其应用于从关系派生的层次上合并用户字典。通过将该算法应用于上下文不敏感的单词预测变化,我们展示了实验数据中按键节省百分比的增加。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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