LOCAL AND GLOBAL LEARNING METHOD FOR QUESTION ANSWERING APPROACH release_m27yrwjjtjed3fhxnih5gkj6wu

by Radhika, Syama

Released as a article-journal .

Abstract

Vocabulary gap between health seekers and health care experts are more prevalent in health care domain. Different health seekers describe their questions in different ways and answers provided by the experts may contain non standardised terminologies. To overcome the vocabulary gap, a new scheme is used which combines two approaches namely local mining and global learning. Local mining extracts medical concepts from medical records and then map them to normalised terminologies based on standardized dictionary. Local mining suffer from problem of missing key concepts. Global learning overcome the issues in local mining by finding the missing key concepts.
In text/plain format

Archived Files and Locations

application/pdf  752.7 kB
file_szjqwu7izvfcxmh7s4m5cwwwqe
web.archive.org (webarchive)
irjet.net (web)
Read Archived PDF
Preserved and Accessible
Type  article-journal
Stage   unknown
Work Entity
access all versions, variants, and formats of this works (eg, pre-prints)
Catalog Record
Revision: 4e5b6f03-fa71-404a-ab46-74b5f6490010
API URL: JSON