关键词: 时间感知,查询时实体识别,数据融合,异构信息空间

Abstract: Most of existing traditional entity resolution (ER) techniques mainly deal with static data sets by offline,non real-time methods.For large data sets,it usually requires a lot of time and system resources.In the face of evolved,hete-rogeneous entities with time information in heterogeneous information spaces,time-aware query-time ER and data fusion become a necessary trend to ensure data quality and user requirements.Aiming at entity search based on keyword query with temporal context in heterogeneous information spaces,this paper proposed a time-aware query-time ER approach TQ-ER to provide more accurate entity profiles to users.A time-aware iterative query expansion algorithm was proposed.TQ-ER leverags temporal context of query and temporal information of entities,which can identify the minimum entities to do ER and data fusion for a given query to be correctly answered.Extensive experimental results on real data sets show the effectiveness and correctness of TQ-ER.

Key words: Time-aware,Query-time entity resolution,Data fusion,Heterogeneous information spaces