从自由文本中推断信息目标：一种贝叶斯方法
Inferring Informational Goals from Free-Text Queries: A Bayesian Approach
摘要：
使用消费者软件应用程序的人们在查询帮助主题的在线数据库时通常不使用技术术语。相反，他们试图用常见的单词和短语来表达他们的目标，这些单词和短语根据他们理解的结构和对象来描述软件功能。我们描述了一种贝叶斯方法来建模的话在用户的查询帮助和用户的信息目标之间的关系。在回顾了一般方法之后，我们描述了几个扩展，这些扩展集中在将有关语言使用和用户目标的其他区别和结构集成到贝叶斯模型中。
英文摘要：
People using consumer software applications typically do not use technical jargon when querying an online database of help topics. Rather, they attempt to communicate their goals with common words and phrases that describe software functionality in terms of structure and objects they understand. We describe a Bayesian approach to modeling the relationship between words in a user's query for assistance and the informational goals of the user. After reviewing the general method, we describe several extensions that center on integrating additional distinctions and structure about language usage and user goals into the Bayesian models.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
