Graph-Based Web Query Classification

摘要：

　　Understanding Web users search intent expressed by their queries is essential for a search engine to provide the appropriate answers.Web query classification (QC)algorithms have been widely studied to improve the accuracy and meet users demands.Some QC algorithms convert queries into vectors and use SVM or CRF model as the classifier.However, with the volume of data increasing, the time consumed significantly increases.In this paper, we propose a method in which we split the queries into words and convert queries into a graph, after that, we adopt a liner equation as the classifier.Experimental results exhibit that our method has similar accuracy but higher efficiency compared with the existing methods.Our method can decrease the training time by 10% compared with the SVM algorithm, and also outperform the CRF model.

关键词： graph query classification search context

作者: Chunwei Xia Xin Wang

作者单位: School of Computer Science and Technology Tianjin University Tianjin, China

会议类型: 国际会议

会议名称: The 12th Web Information System and Application Conference第十二届全国Web信息系统及其应用学术会议(WISA2015)、全国第十次语义Web 与本体论学术研讨会(SWON2015)、全国第九次电子政务技术及应用学术研讨会(EGTA2015)

会议地点: 济南

会议语种:英文

页码: 241-244

在线出版日期: 2015-09-11（万方平台首次上网日期，不代表论文的发表时间）