Dynamic generation of a table of contents with consumer-friendly labels.

Trudi Miller, Gondy Augusta Leroy, Elizabeth Wood

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Consumers increasingly look to the Internet for health information, but available resources are too difficult for the majority to understand. Interactive tables of contents (TOC) can help consumers access health information by providing an easy to understand structure. Using natural language processing and the Unified Medical Language System (UMLS), we have automatically generated TOCs for consumer health information. The TOC are categorized according to consumer-friendly labels for the UMLS semantic types and semantic groups. Categorizing phrases by semantic types is significantly more correct and relevant. Greater correctness and relevance was achieved with documents that are difficult to read than those at an easier reading level. Pruning TOCs to use categories that consumers favor further increases relevancy and correctness while reducing structural complexity.

Original languageEnglish (US)
Pages (from-to)559-563
Number of pages5
JournalAMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
StatePublished - 2006
Externally publishedYes

Fingerprint

Consumer Health Information
Unified Medical Language System
Semantics
Natural Language Processing
Internet
Reading
Health

ASJC Scopus subject areas

  • Medicine(all)

Cite this

Dynamic generation of a table of contents with consumer-friendly labels. / Miller, Trudi; Leroy, Gondy Augusta; Wood, Elizabeth.

In: AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium, 2006, p. 559-563.

Research output: Contribution to journalArticle

@article{b763a84546464d15a7994dbf98c595be,
title = "Dynamic generation of a table of contents with consumer-friendly labels.",
abstract = "Consumers increasingly look to the Internet for health information, but available resources are too difficult for the majority to understand. Interactive tables of contents (TOC) can help consumers access health information by providing an easy to understand structure. Using natural language processing and the Unified Medical Language System (UMLS), we have automatically generated TOCs for consumer health information. The TOC are categorized according to consumer-friendly labels for the UMLS semantic types and semantic groups. Categorizing phrases by semantic types is significantly more correct and relevant. Greater correctness and relevance was achieved with documents that are difficult to read than those at an easier reading level. Pruning TOCs to use categories that consumers favor further increases relevancy and correctness while reducing structural complexity.",
author = "Trudi Miller and Leroy, {Gondy Augusta} and Elizabeth Wood",
year = "2006",
language = "English (US)",
pages = "559--563",
journal = "AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium",
issn = "1559-4076",
publisher = "American Medical Informatics Association",

}

TY - JOUR

T1 - Dynamic generation of a table of contents with consumer-friendly labels.

AU - Miller, Trudi

AU - Leroy, Gondy Augusta

AU - Wood, Elizabeth

PY - 2006

Y1 - 2006

N2 - Consumers increasingly look to the Internet for health information, but available resources are too difficult for the majority to understand. Interactive tables of contents (TOC) can help consumers access health information by providing an easy to understand structure. Using natural language processing and the Unified Medical Language System (UMLS), we have automatically generated TOCs for consumer health information. The TOC are categorized according to consumer-friendly labels for the UMLS semantic types and semantic groups. Categorizing phrases by semantic types is significantly more correct and relevant. Greater correctness and relevance was achieved with documents that are difficult to read than those at an easier reading level. Pruning TOCs to use categories that consumers favor further increases relevancy and correctness while reducing structural complexity.

AB - Consumers increasingly look to the Internet for health information, but available resources are too difficult for the majority to understand. Interactive tables of contents (TOC) can help consumers access health information by providing an easy to understand structure. Using natural language processing and the Unified Medical Language System (UMLS), we have automatically generated TOCs for consumer health information. The TOC are categorized according to consumer-friendly labels for the UMLS semantic types and semantic groups. Categorizing phrases by semantic types is significantly more correct and relevant. Greater correctness and relevance was achieved with documents that are difficult to read than those at an easier reading level. Pruning TOCs to use categories that consumers favor further increases relevancy and correctness while reducing structural complexity.

UR - http://www.scopus.com/inward/record.url?scp=34748853066&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=34748853066&partnerID=8YFLogxK

M3 - Article

C2 - 17238403

AN - SCOPUS:34748853066

SP - 559

EP - 563

JO - AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium

JF - AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium

SN - 1559-4076

ER -