Ontology learning and population from text - algorithms, evaluation and applications

By Philipp Cimiano. 2006

621 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Citations in the corpus

Joint Video and Text Parsing for Understanding Events and Answering Queries (2013, methodology): “This ontology can be manually constructed using an ontology editor (e.g., [41], [42], [43]), adapted from an existing ontology (e.g., [44], [45]), or automatically or semi-automatically learned from data (e.g., [46], [47], [48]).”
Book Reviews: Ontology-Based Interpretation of Natural Language by Philipp Cimiano, Christina Unger and John McCrae (2014, background): “e paper by Cimiano et al. [2013] discusses theoretical aspects related to the role of sense objects in the lexicon-ontology interface.”
Unsupervised Ontology Induction from Text (2010, background): “Recently, ontology learning has attracted increasing interest in both NLP and semantic Web communities (Cimiano, 2006; Maedche, 2002), and a number of machine learning approaches have been developed (e.g., Snow et al. (2006), Cimiano (2006), Suchanek et al. (2008,2009), Wu & Weld (2008)).”
Joint Learning of Words and Meaning Representations for Open-Text Semantic Parsing (2012, background): “Some approaches have been directly targeting to enrich existing resources, as we do here with WordNet, (Agirre et al., 2000; Cuadros and Rigau, 2008; Cimiano, 2006) but these never use learning.”
Machine Reading: A "Killer App" for Statistical Relational AI (2010, methodology): “More recently, machine learning approaches have been developed (e.g., Snow et al. (2006), Cimiano (2006), Suchanek et al. (2008,2009), Wu & Weld (2008)), but they are still limited in several aspects.”