|
用于自然语言接口到数据库的语法结构内核
Syntactic Structural Kernels for Natural Language Interfaces to Databases |
|
| |
| 课程网址: |
http://videolectures.net/ecmlpkdd09_moschitti_ssknlid/
|
| 主讲教师: |
Alessandro Moschitti
|
| 开课单位: |
特伦托大学
|
| 开课时间: |
信息不详。欢迎您在右侧留言补充。
|
| 课程语种: |
英语
|
| 中文简介: |
数据挖掘的一个核心问题是以一种简单、人性化的方式检索数据。自动将自然语言问题转换为SQL查询将允许从用户的角度设计有效和有用的数据库系统。有趣的是，之前的工作主要集中在机器学习算法的使用上，它可以自动将自然语言（nl）问题映射到SQL查询。在本文中，我们提出了许多结构内核和它们的组合，用于诱导本地语言问题对和SQL查询之间的关系语义。我们在支持向量机中使用这些内核来选择正确回答本地语言问题的查询，以此来衡量这些内核的有效性。对两个不同数据集的实验结果表明，我们的方法是可行的，并且以成对的句法树片段（来自查询和问题）形式的句法信息在推导两种语言之间的关系语义中起着重要作用。
|
| 课程简介: |
A core problem in data mining is to retrieve data in a easy and human friendly way. Automatically translating natural language questions into SQL queries would allow for the design of effective and useful database systems from a user viewpoint. Interesting previous work has been focused on the use of machine learning algorithms for automatically mapping natural language (NL) questions to SQL queries. In this paper, we present many structural kernels and their combinations for inducing the relational semantics between pairs of NL questions and SQL queries. We measure the effectiveness of such kernels by using them in Support Vector Machines to select the queries that correctly answer to NL questions. Experimental results on two different datasets show that our approach is viable and that syntactic information under the form of pairs of syntactic tree fragments (from queries and questions) plays a major role in deriving the relational semantics between the two languages.
|
| 关 键 词: |
数据挖掘; 自然语言; 机器学习; 内核
|
| 课程来源: |
视频讲座网
|
| 最后编审: |
2019-12-05：cwx
|
| 阅读次数: |
37
|
|
图 书 馆