基于环境信息的移动搜索个性化查询扩展

Personalized Query Expansion Based on Environment Information for Mobile Search

与传统搜索相比,移动搜索对位置、温度、速度等环境信息更为敏感。为了有效利用环境信息推断用户查询意图,提出了一种基于环境信息的查询扩展方法并应用在移动搜索系统Clever Search Engine(CSE)中。该方法利用专家系统对分词后的查询词和收集到的用户环境信息进行推理和融合,扩展查询词,实现个性化搜索。实验证明,基于环境信息的移动搜索个性化查询扩展方法能有效改善移动用户的搜索体验,比现有的公共搜索引擎(如Google)具有更高的查准率。

Compared with traditional search,mobile search is sensitive to the users＇ environment information such as lo cation, temperature, speed and so on. In order to use the environment information to infer the user intents, an expansion approach based on environment information was proposed, which has been applied in the Clever Search Engine （CSE）-a mobile search system we developed. Using segmented queries and users＇ environment information, the ap proach infers the user intents through the expert system and expands query in order to realize personalized query expan-sion. Experimental results show that the approach we proposed can significantly improve users＇ search experiences and has better performance in precision than existing public search engine（e, g. Google）.