• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Computer speech and language >Modelling text prediction systems in low- and high-inflected languages
【24h】

Modelling text prediction systems in low- and high-inflected languages

机译：用低和高变化语言建模文本预测系统

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Text prediction was initially proposed to help people with a low text composition speed to enhance their message composition. After the important advancements obtained in the last years, text prediction methods may nowadays benefit anyone trying to input text messages or commands, if they are adequately integrated within the user interface of the application. Diverse text prediction methods are based in different statistic and linguistic properties of natural languages. Hence, they are very dependent on the language concerned. In order to discuss general issues of text prediction it is necessary to propose abstract descriptions of the methods used. In this paper a number of models applied to text prediction are presented. Some of them are oriented to low-inflected languages while others are for high-inflected languages. All these models have been implemented and their results are compared. Presented models may be useful for future discussion. Finally, some comments related to the comparison of previously published results are also done.
机译：最初提出文本预测是为了帮助文本撰写速度较慢的人增强其消息撰写。在过去的几年中取得了重要的进步之后，如今，如果文本预测方法已充分集成在应用程序的用户界面中，则可能使尝试输入文本消息或命令的任何人受益。多种文本预测方法基于自然语言的不同统计和语言属性。因此，它们非常依赖于相关语言。为了讨论文本预测的一般问题，有必要提出对所用方法的抽象描述。在本文中，提出了许多应用于文本预测的模型。它们中的一些面向低变形语言，而其他则针对高变形语言。所有这些模型均已实施，其结果进行了比较。提出的模型可能对将来的讨论有用。最后，还完成了一些与以前发布的结果比较相关的评论。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号