异构信息空间中时间感知的跨类型实体推荐

Time-aware Cross-type Entity Recommendation in Heterogeneous Information Spaces

随着实体搜索成为信息检索的一种新趋势,实体推荐也成为业界和学术界的热门研究问题之一。异构信息空间中的异构实体间彼此相互关联,因此跨类型实体推荐至关重要。此外,异构实体具有时间信息,异构信息空间中的实体不断随时间演化,用户希望得到在时间上最相关的实体推荐。提出一个时间感知的跨类型实体推荐框架TERe,利用异构实体间丰富的关联关系和查询日志实现跨类型的实体推荐。T-ERe考虑实体的时间信息和查询的时间上下文,给用户推荐时间上最相关的多种类型的实体。在真实数据集上的实验结果表明了T-ERe的可行性和有效性。

With entity search has become a new trend of information retrieval, entity recommendation has also become one of the hottest research problems in industry and academia. Due to heterogeneous entities with rich associations in heterogeneous information spaces, so cross-type entity recommendation is vital. Moreover heterogeneous entities have time information and evolve over time in heterogeneous information spaces, users want to get the most time relevant en- tity recommendation. In this paper, a time-aware cross-type entity recommendation framework T-ERe was proposed, which leverages rich associations among different entity types and query log to realize cross-type entity recommenda- tion. T-ERe considers temporal information of entities and recommends the most time-relevant various types of entities to users. Experimental results on two real data sets demonstrate the feasibility and effectiveness of T-ERe.