Identifying the Intent of a User Query Using Support Vector Machines
Identifying the Intent of a User Query Using Support Vector Machines
复制标题
使用支持向量机识别用户查询的意图
DOI：
10.1007/978-3-642-03784-9_13
复制
发表时间：
2009
影响因子：
--
通讯作者：
Juan Zamora
中科院分区：
文献类型：
--
作者：
Marcelo Mendoza;Juan Zamora
在本文中，我们介绍了一种高精度的查询分类方法来识别用户查询的意图，因为它已经在过去的信息，导航和事务分类的基础上。我们建议使用三个向量表示的查询，使用支持向量机，允许过去的查询用户的意图进行分类。查询已被表示为向量使用两个因素从点击数据：用户花时间来审查他们选择的文件和流行度（数量的偏好）的选定的文件。实验结果表明，时间是产生较高的分类精度的因素。实验结果表明，本文提出的分类器可以有效地识别过去的查询的意图与高精度。
In this paper we introduce a high-precision query classification method to identify the intent of a user query given that it has been seen in the past based on informational, navigational, and transactional categorization. We propose using three vector representations of queries which, using support vector machines, allow past queries to be classified by user's intents. The queries have been represented as vectors using two factors drawn from click-through data: the time users take to review the documents they select and the popularity (quantity of preferences) of the selected documents. Experimental results show that time is the factor that yields higher precision in classification. The experiments shown in this work illustrate that the proposed classifiers can effectively identify the intent of past queries with high-precision.