Evaluating the botanical coverage of PATO using an unsupervised learning algorithm

Alyssa Janning, Hong Cui

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this paper, we explore issues in adopting PATO as a standard phenotypic quality ontology for the biological community. Using CharaParser's unsupervised learning algorithm and the Stanford Parser, we extract morphological descriptions from Flora of North America to be matched to terms in PATO. Using the resulting data, we examine PATO's coverage of botanically interesting terms in order to find gaps and to determine accuracy. To maintain PATO's neutrality, we recommend that term definitions be reevaluated and propose that complimentary ontologies be enhanced to close any outstanding gaps in terminology.

Original languageEnglish (US)
Title of host publicationACM International Conference Proceeding Series
Pages504-505
Number of pages2
DOIs
StatePublished - 2012
Event2012 iConference: Culture, Design, Society, iConference 2012 - Toronto, ON, Canada
Duration: Feb 7 2012Feb 10 2012

Other

Other2012 iConference: Culture, Design, Society, iConference 2012
CountryCanada
CityToronto, ON
Period2/7/122/10/12

Fingerprint

Unsupervised learning
Learning algorithms
Ontology
Terminology
Biota

Keywords

  • botany
  • Flora of North America
  • ontologies
  • open biological ontologies
  • PATO
  • Stanford Parser
  • unsupervised learning

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

Cite this

Evaluating the botanical coverage of PATO using an unsupervised learning algorithm. / Janning, Alyssa; Cui, Hong.

ACM International Conference Proceeding Series. 2012. p. 504-505.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Janning, A & Cui, H 2012, Evaluating the botanical coverage of PATO using an unsupervised learning algorithm. in ACM International Conference Proceeding Series. pp. 504-505, 2012 iConference: Culture, Design, Society, iConference 2012, Toronto, ON, Canada, 2/7/12. https://doi.org/10.1145/2132176.2132265
Janning, Alyssa ; Cui, Hong. / Evaluating the botanical coverage of PATO using an unsupervised learning algorithm. ACM International Conference Proceeding Series. 2012. pp. 504-505
@inproceedings{79da4426c5bc4640b597872f7df20242,
title = "Evaluating the botanical coverage of PATO using an unsupervised learning algorithm",
abstract = "In this paper, we explore issues in adopting PATO as a standard phenotypic quality ontology for the biological community. Using CharaParser's unsupervised learning algorithm and the Stanford Parser, we extract morphological descriptions from Flora of North America to be matched to terms in PATO. Using the resulting data, we examine PATO's coverage of botanically interesting terms in order to find gaps and to determine accuracy. To maintain PATO's neutrality, we recommend that term definitions be reevaluated and propose that complimentary ontologies be enhanced to close any outstanding gaps in terminology.",
keywords = "botany, Flora of North America, ontologies, open biological ontologies, PATO, Stanford Parser, unsupervised learning",
author = "Alyssa Janning and Hong Cui",
year = "2012",
doi = "10.1145/2132176.2132265",
language = "English (US)",
isbn = "9781450307826",
pages = "504--505",
booktitle = "ACM International Conference Proceeding Series",

}

TY - GEN

T1 - Evaluating the botanical coverage of PATO using an unsupervised learning algorithm

AU - Janning, Alyssa

AU - Cui, Hong

PY - 2012

Y1 - 2012

N2 - In this paper, we explore issues in adopting PATO as a standard phenotypic quality ontology for the biological community. Using CharaParser's unsupervised learning algorithm and the Stanford Parser, we extract morphological descriptions from Flora of North America to be matched to terms in PATO. Using the resulting data, we examine PATO's coverage of botanically interesting terms in order to find gaps and to determine accuracy. To maintain PATO's neutrality, we recommend that term definitions be reevaluated and propose that complimentary ontologies be enhanced to close any outstanding gaps in terminology.

AB - In this paper, we explore issues in adopting PATO as a standard phenotypic quality ontology for the biological community. Using CharaParser's unsupervised learning algorithm and the Stanford Parser, we extract morphological descriptions from Flora of North America to be matched to terms in PATO. Using the resulting data, we examine PATO's coverage of botanically interesting terms in order to find gaps and to determine accuracy. To maintain PATO's neutrality, we recommend that term definitions be reevaluated and propose that complimentary ontologies be enhanced to close any outstanding gaps in terminology.

KW - botany

KW - Flora of North America

KW - ontologies

KW - open biological ontologies

KW - PATO

KW - Stanford Parser

KW - unsupervised learning

UR - http://www.scopus.com/inward/record.url?scp=84857668394&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84857668394&partnerID=8YFLogxK

U2 - 10.1145/2132176.2132265

DO - 10.1145/2132176.2132265

M3 - Conference contribution

AN - SCOPUS:84857668394

SN - 9781450307826

SP - 504

EP - 505

BT - ACM International Conference Proceeding Series

ER -