Unsupervised Ontology Induction From Text - Microsoft Research

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This Talk: OntoUSP • Jointly conducts: Ontology induction, population, and knowledge extraction • Learns ISA hierarchy over logical expressions • Populates it by translating sentences into logical forms Five times as many correct answers as TextRunner • Extends USP with hierarchical clustering • Hierarchical smoothing Improves on the recall of USP by 47% • Encoded in a few high-order formulas in Markov Logic [Richardson & Domingos, 2006] • Sole input is dependency trees 10
Outline • Background: USP • Unsupervised ontology induction • Conclusion 11
Page 1 and 2: Unsupervised Ontology Induction Fro
Page 5 and 6: Extracting Knowledge From Text …
Page 7 and 8: Unsupervised Learning for Knowledge
Page 9: Ontology Learning • Attracts incr
Page 13 and 14: Challenge: Same Meaning, Many Varia
Page 15 and 16: Unsupervised Semantic Parsing • U
Page 21 and 22: Unsupervised Semantic Parsing • E
Page 23 and 24: Learning: Hill-Climb Likelihood Ini
Page 25 and 26: OntoUSP • USP + Hierarchical clus
Page 27 and 28: Experiments • Evaluate on an end
Page 29 and 30: Induced Ontology (Partial)
Page 31: Conclusion • OntoUSP: Unsupervise

Unsupervised Ontology Induction From Text - Microsoft Research

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