Author:
Andrea Andrenucci
Affiliation:
Stockholm University/ Royal Institute of Technology, Sweden
Keyword(s):
Automated Question Answering, Natural Language Interfaces, Medical Applications.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Cloud Computing
;
Databases and Datawarehousing
;
e-Health
;
Expert Systems
;
Health Information Systems
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Online Medical Applications
;
Platforms and Applications
;
Symbolic Systems
Abstract:
The question-answering (QA) paradigm, i.e. the process of retrieving precise answers to natural language (NL) questions, was introduced in late 1960-ies and early 1970-ies within the framework of Artificial Intelligence. The advent of WWW and the need to provide advanced, user-friendly search tools has extended the QA paradigm to a larger audience of people and a larger number of fields, including medicine. This paper reviews and compares three main question-answering approaches based on Natural Language Processing, Information Retrieval, and question templates, eliciting their differences and the context of application that best suits each of them within the medical domain.