NDLI: InfoGather: Entity Augmentation and Attribute Discovery By Holistic Matching with Web Tables

Content Provider	Microsoft Research
Author	Yakout, Mohamed Ganjam, Kris Chakrabarti, Kaushik Chaudhuri, Surajit
Copyright Year	2012
Abstract	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.
Language	English
Publisher	ACM SIGMOD Conference
Publisher Date	2012-01-01
Access Restriction	Open
Rights Holder	Microsoft Corporation
Subject Keyword	Search Information retrieval Knowledge management
Content Type	Text
Resource Type	Proceeding

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