A Hierarchical Framework for User Intention Recognition
Tang Jingxiao1, Lv Xueqiang1, Liu Chengyang2, Li Han2
1Beijing Key Laboratory of Internet Culture and Digital Dissemination Research,Beijing Information Science and Technology University,Beijing 100101,China; 2China National Institute of Standardization,Beijing 100191,China
Abstract：[Objective] Any query search engine has its potential query intention,and accurate intention identification can improve the efficiency. [Methods] For the explicit intent queries,the authors employ sliding window strategy to find the maximum common substring for extracting user intent templates and then use the templates to identify the user intention. For implicit intent queries,the authors use a multi-feature integration method to build classifier for the final query intention recognition. [Results] Experimental results show that the hierarchical intention recognition framework can achieve better precision comparing with methods based on classifier,and the accuracy enhances 19.04%. [Limitations] Intention template obtaining is limited,so explicit intention recognition has limitation. For large-scale data,complexity of the pattern match and machine learning algorithm is very high,the algorithm need further optimization. [Conclusions] Experiment shows that this method is valid in Web intention recognition,which has a positive significance for improvement of intention recognition rate.
唐静笑,吕学强,柳成洋,李涵. 用户查询意图的层次化识别方法*[J]. 现代图书情报技术, 2014, 30(1): 36-42.
Tang Jingxiao,Lv Xueqiang,Liu Chengyang,Li Han. A Hierarchical Framework for User Intention Recognition. New Technology of Library and Information Service, 2014, 30(1): 36-42.
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