%0 Journal Article %A CAO Wei %A QIN Biao %A QIN Xiongpai %A WANG Qiuyue %T Entity relationship search over extended knowledge graph %D 2016 %R 10.11772/j.issn.1001-9081.2016.04.0985 %J Journal of Computer Applications %P 985-991 %V 36 %N 4 %X It is difficult for entity search and question answering over text corpora to join cues from multiple documents to process relationship-centric search tasks, although structured querying over knowledge base can resolve such problem, but it still suffers from poor recall because of the heterogeneity and incompleteness of knowledge base. To address these problems, the knowledge graph was extended with information from textual corpora and a corresponding triple pattern with textual phrases was designed for uniform query of knowledge graph and textual corpora. Accordingly, a model for automatic query relaxation and scoring query answers (tuples of entities) was proposed, and an efficient top-k query processing strategy was put forward. Comparison experiments were conducted with two classical methods on three different benchmarks including entity search, entity-relationship search and complex entity-relationship queries using a combination of the Yago knowledge graph and the entity-annotated ClueWeb '09 corpus. The experimental results show that the entity-relationship search system with query relaxation over extended knowledge base outperforms the comparison systems with a big margin, the Mean Average Precision (MAP) are improved by more than 27%, 37%, 64% respectively on the three benchmarks. %U http://www.joca.cn/EN/10.11772/j.issn.1001-9081.2016.04.0985