Query Classification by Using URL-Key
LI Xuewe · Beijing Daxue Xuebao. Zirankexueban · 2015
For the problem of query classification, a variance based method is proposed to identify domain URLkey by the domain URL organized manually from aggregator sites and the use frequency of URL-key in each category. Then, the URL-key is filtered by using machine translation, pinyin and search results feedback technology. Finally, coupled with relevance feedback, the authors classify the query by selecting the URL-key as feature and establishing the URL-key vector with a SVM multi-class classifier. Experimental results show that the proposed method uses less resources and the F-value is 7% higher than contrast method.