Entity-Relationship Queries over Wikipedia

被引:3
|
作者
Li, Xiaonan [1 ]
Li, Chengkai [1 ]
Yu, Cong
机构
[1] Univ Texas Arlington, Dept Comp Sci & Engn, Arlington, TX 76019 USA
基金
美国国家科学基金会;
关键词
Design; Languages; Performance; Entity search and ranking; structured entity query; Wikipedia;
D O I
10.1145/2337542.2337555
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Wikipedia is the largest user-generated knowledge base. We propose a structured query mechanism, entityrelationship query, for searching entities in the Wikipedia corpus by their properties and interrelationships. An entity-relationship query consists of multiple predicates on desired entities. The semantics of each predicate is specified with keywords. Entity-relationship query searches entities directly over text instead of preextracted structured data stores. This characteristic brings two benefits: (1) Query semantics can be intuitively expressed by keywords; (2) It only requires rudimentary entity annotation, which is simpler than explicitly extracting and reasoning about complex semantic information before query-time. We present a ranking framework for general entity-relationship queries and a position-based Bounded Cumulative Model (B CM) for accurate ranking of query answers. We also explore various weighting schemes for further improving the accuracy of BCM. We test our ideas on a 2008 version of Wikipedia using a collection of 45 queries pooled from INEX entity ranking track and our own crafted queries. Experiments show that the ranking and weighting schemes are both effective, particularly on multipredicate queries.
引用
收藏
页数:20
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