Unsupervised Ontology Induction from Text

By Hoifung Poon, Pedro M. Domingos. 2010

142 citations recorded by the source corpus.

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Citations in the corpus

Long Short-Term Memory-Networks for Machine Reading (2016, background): “, 2011), ontology learning (Poon and Domingos, 2010), and textual entailment (Dagan et al.”
Joint Learning of Words and Meaning Representations for Open-Text Semantic Parsing (2012, methodology): “A method based on Markov-Logic Networks has been recently introduced for unsupervised semantic parsing that can be also used for information acquisition (Poon and Domingos, 2009, 2010).”
Bootstrapping Semantic Parsers from Conversations (2011, background): “…from context-dependent database queries (Miller et al., 1996; Zettlemoyer and Collins, 2009), grounded event streams (Chen et al., 2010; Liang et al., 2009), environment interactions (Branavan et al., 2009; 2010; Vogel and Jurafsky, 2010), and even unanno-tated text (Poon and Domingos, 2009; 2010).”
Improved Pattern Learning for Bootstrapped Entity Extraction (2014, background): “Thelen and Riloff (2002) extended the above bootstrapping algorithm for multi-class learning.”
A latent factor model for highly multi-relational data (2012, background): “SRL systems are a useful tool there, as they can automatically extract high level information from the collected data by building summaries [22], sense categorization lexicons [11], ontologies [20], etc.”
Machine Reading at the University of Washington (2010, methodology): “…jointly performs ontology induction, population, and knowledge extraction via joint recursive relational clustering and shrinkage with Markov logic (Poon and Domingos, 2010); OLPI improves the efﬁciency of lifted probabilistic inference and learning via coarse-to-ﬁne inference based on type…”
Joint learning of ontology and semantic parser from text (2016, unknown): “This problem was also observed by [28].”
Machine Reading: A "Killer App" for Statistical Relational AI (2010, methodology): “In this section, we demonstrate the promise of our unifying approach by presenting OntoUSP (Poon and Domingos 2010), a recent system that capitalizes on Markov logic and joint inference and achieves state-of-the-art results on a machine reading task.”