LinkedHealthAnswers: Towards Linked Data-driven Question Answering for the Health Care Domain
15417Authors
nan
Abstract
AbstractThis paper presents Linked Health Answers, a natural language question answering systems that utilizes health data drawn from the Linked Data Cloud. The contributions of this paper are three-fold: Firstly, we review existing state-of-the-art NLP platforms and components, with a special focus on components that allow or support an automatic SPARQL construction. Secondly, we present the implemented architecture of the Linked Health Answers systems. Thirdly, we propose an statistical bootstrap approach for the identification and disambiguation of RDF-based predicates using a machine learning-based classifier. The evaluation focuses on predicate detection in sentence statements, as well as within the scenario of natural language questions.
Keywords
Full Content
nan
Labeled Text
AbstractThis paper presents Linked Health Answers, a natural language question answering systems that utilizes health data drawn from the Linked Data Cloud. The contributions of this paper are three-fold: Firstly, we review existing state-of-the-art NLP platforms and components, with a special focus on components that allow or support an automatic SPARQL construction. Secondly, we present the implemented architecture of the Linked Health Answers systems. Thirdly, we propose an statistical bootstrap approach for the identification and disambiguation of RDF-based predicates using a machine learning-based classifier. The evaluation focuses on predicate detection in sentence statements, as well as within the scenario of natural language questions.
Publication Details
- Paper ID:
- 15417
- Year:
- 2014
- Publication:
- TIPSTER
- Publication Type:
- conf
- DOI:
- nan