Publication | Closed Access
InfoGather
227
Citations
18
References
2012
Year
Unknown Venue
Natural Language ProcessingEngineeringInformation RetrievalData ScienceKnowledge ExtractionWeb IntelligenceStructured DataIntelligent Information RetrievalKnowledge DiscoveryHtml TablesData IntegrationEntity Attribute TablesSemantic WebInformation ExtractionData ManagementText MiningEntity Augmentation
The Web contains a vast corpus of HTML tables, specifically entity attribute tables. We present three core operations, namely entity augmentation by attribute name, entity augmentation by example and attribute discovery, that are useful for "information gathering" tasks (e.g., researching for products or stocks). We propose to use web table corpus to perform them automatically. We require the operations to have high precision and coverage, have fast (ideally interactive) response times and be applicable to any arbitrary domain of entities. The naive approach that attempts to directly match the user input with the web tables suffers from poor precision and coverage.
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