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Ontology Learning from Text: Methods, Evaluation and Applications
TLDR
This volume presents current research in ontology learning, addressing three perspectives, including methodologies that have been proposed to automatically extract information from texts and to give a structured organization to such knowledge, including approaches based on machine learning techniques.
Ontology Learning from Text: An Overview
This volume brings together a collection of extended versions of selected papers from two workshops on ontology learning, knowledge acquisition and related topics that were organized in the context
Towards Linguistically Grounded Ontologies
TLDR
It is argued that in the light of tasks such as ontology-based information extraction, ontology learning and population from text and natural language generation from ontologies, currently available datamodels are not sufficient as they only allow to associate atomic terms without linguistic grounding or structure to ontology elements.
A Protégé Plug-In for Ontology Extraction from Text Based on Linguistic Analysis
TLDR
A plug-in for the widely used Protege ontology development tool that supports the interactive extraction and/or extension of ontologies from text and provides an environment for the integration of linguistic analysis in ontology engineering through the definition of mapping rules.
LexInfo: A declarative model for the lexicon-ontology interface
TLDR
A model for linguistic grounding of ontologies called LexInfo, implemented as an OWL ontology and freely available together with an API, which allows us to associate linguistic information to elements in an ontology with respect to any level of linguistic description and expressivity.
RelExt: A Tool for Relation Extraction from Text in Ontology Extension
TLDR
A system that is capable of automatically identifying highly relevant triples over concepts from an existing ontology, developed in the context of the SmartWeb project, which aims at providing intelligent information services via mobile broadband devices on the FIFA World Cup that will be hosted in Germany in 2006.
SemEval-2019 Task 9: Suggestion Mining from Online Reviews and Forums
TLDR
This work presents the pilot SemEval task on Suggestion Mining, where labeled data from feedback forum and hotel reviews respectively was created and details of the methods used by the top ranked systems were provided.
Challenges for the multilingual Web of Data
TLDR
A vision of a multilingual Web of Data is presented and the role that techniques such as ontology localization, ontology mapping, and cross-lingual ontology-based information access and presentation will play in achieving this is discussed.
SemEval-2016 Task 13: Taxonomy Extraction Evaluation (TExEval-2)
TLDR
This paper describes the second edition of the shared task on Taxonomy Extraction Evaluation organised as part of SemEval 2016, which introduced a multilingual setting for this task, covering four different languages including English, Dutch, Italian and French from domains as diverse as environment, food and science.
Ontology-based information extraction and integration from heterogeneous data sources
TLDR
The design, implementation and evaluation of SOBA is presented, a system for ontology-based information extraction from heterogeneous data resources, including plain text, tables and image captions, and it straightforwardly integrates deep and shallow natural language processing to increase robustness and accuracy.
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