Publication | Closed Access
Entity-Relationship Queries over Wikipedia
19
Citations
25
References
2012
Year
EngineeringSemantic SearchEntity-relationship QueriesQuery ModelSemanticsSemantic WebText MiningNatural Language ProcessingInformation RetrievalData ScienceWeighting SchemesQuery ExpansionEntity DisambiguationKnowledge DiscoveryQuery OptimizationKnowledge BaseStructured Query MechanismWikipedia CorpusRelationship Extraction
Wikipedia is the largest user-generated knowledge base. We propose a structured query mechanism, entity-relationship 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 (BCM) 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.
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