Loading…
A machine-learning apprentice for the completion of repetitive forms
The authors have developed a software environment in which workers can complete repetitive forms, and a machine-learning and prediction system that works within it. The nonintrusive assistant or apprentice provides viable default values for blank fields in a form, saving users up to 87 percent in ke...
Saved in:
Published in: | IEEE expert 1994-02, Vol.9 (1), p.28-33 |
---|---|
Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c281t-5f291c84efa522c118fe12ce2a3cf60e8208853a4a8caf91482ae392eb38b9373 |
---|---|
cites | cdi_FETCH-LOGICAL-c281t-5f291c84efa522c118fe12ce2a3cf60e8208853a4a8caf91482ae392eb38b9373 |
container_end_page | 33 |
container_issue | 1 |
container_start_page | 28 |
container_title | IEEE expert |
container_volume | 9 |
creator | Hermens, L.A. Shlimmer, J.C. |
description | The authors have developed a software environment in which workers can complete repetitive forms, and a machine-learning and prediction system that works within it. The nonintrusive assistant or apprentice provides viable default values for blank fields in a form, saving users up to 87 percent in keystroke effort and correctly predicting nearly 90 percent of the form's values. The system and prediction methods are active, yet not intrusive. Default predictions are always displayed, yet the user can override them easily with normal editing commands.< > |
doi_str_mv | 10.1109/64.295135 |
format | article |
fullrecord | <record><control><sourceid>crossref_ieee_</sourceid><recordid>TN_cdi_ieee_primary_295135</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>295135</ieee_id><sourcerecordid>10_1109_64_295135</sourcerecordid><originalsourceid>FETCH-LOGICAL-c281t-5f291c84efa522c118fe12ce2a3cf60e8208853a4a8caf91482ae392eb38b9373</originalsourceid><addsrcrecordid>eNo9j81LAzEUxIMouFYPXj3l6iE17yW7mxxLtSoUvOh5ScOLjewXySL439u6xdMMzI9hhrFbkEsAaR8qvURbgirPWIGq1sJqWZ-zQhpTCiulvGRXOX9JCVrXVcEeV7xzfh97Ei251Mf-k7txTNRP0RMPQ-LTnrgfurGlKQ49HwJPNB78FL__gC5fs4vg2kw3J12wj83T-_pFbN-eX9errfBoYBJlQAveaAquRPQAJhCgJ3TKh0qSweNK5bQz3gUL2qAjZZF2yuysqtWC3c-9Pg05JwrNmGLn0k8DsjnebyrdzPcP7N3MRiL6507hL8OTVTY</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>A machine-learning apprentice for the completion of repetitive forms</title><source>IEEE Xplore (Online service)</source><creator>Hermens, L.A. ; Shlimmer, J.C.</creator><creatorcontrib>Hermens, L.A. ; Shlimmer, J.C.</creatorcontrib><description>The authors have developed a software environment in which workers can complete repetitive forms, and a machine-learning and prediction system that works within it. The nonintrusive assistant or apprentice provides viable default values for blank fields in a form, saving users up to 87 percent in keystroke effort and correctly predicting nearly 90 percent of the form's values. The system and prediction methods are active, yet not intrusive. Default predictions are always displayed, yet the user can override them easily with normal editing commands.< ></description><identifier>ISSN: 0885-9000</identifier><identifier>EISSN: 2374-9407</identifier><identifier>DOI: 10.1109/64.295135</identifier><identifier>CODEN: IEEXE7</identifier><language>eng</language><publisher>IEEE</publisher><subject>Computer errors ; Computer networks ; Government ; Image recognition ; Image segmentation ; Machine learning ; Microcomputers ; NASA ; Routing ; Workstations</subject><ispartof>IEEE expert, 1994-02, Vol.9 (1), p.28-33</ispartof><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c281t-5f291c84efa522c118fe12ce2a3cf60e8208853a4a8caf91482ae392eb38b9373</citedby><cites>FETCH-LOGICAL-c281t-5f291c84efa522c118fe12ce2a3cf60e8208853a4a8caf91482ae392eb38b9373</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/295135$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,54796</link.rule.ids></links><search><creatorcontrib>Hermens, L.A.</creatorcontrib><creatorcontrib>Shlimmer, J.C.</creatorcontrib><title>A machine-learning apprentice for the completion of repetitive forms</title><title>IEEE expert</title><addtitle>EX-M</addtitle><description>The authors have developed a software environment in which workers can complete repetitive forms, and a machine-learning and prediction system that works within it. The nonintrusive assistant or apprentice provides viable default values for blank fields in a form, saving users up to 87 percent in keystroke effort and correctly predicting nearly 90 percent of the form's values. The system and prediction methods are active, yet not intrusive. Default predictions are always displayed, yet the user can override them easily with normal editing commands.< ></description><subject>Computer errors</subject><subject>Computer networks</subject><subject>Government</subject><subject>Image recognition</subject><subject>Image segmentation</subject><subject>Machine learning</subject><subject>Microcomputers</subject><subject>NASA</subject><subject>Routing</subject><subject>Workstations</subject><issn>0885-9000</issn><issn>2374-9407</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1994</creationdate><recordtype>article</recordtype><recordid>eNo9j81LAzEUxIMouFYPXj3l6iE17yW7mxxLtSoUvOh5ScOLjewXySL439u6xdMMzI9hhrFbkEsAaR8qvURbgirPWIGq1sJqWZ-zQhpTCiulvGRXOX9JCVrXVcEeV7xzfh97Ei251Mf-k7txTNRP0RMPQ-LTnrgfurGlKQ49HwJPNB78FL__gC5fs4vg2kw3J12wj83T-_pFbN-eX9errfBoYBJlQAveaAquRPQAJhCgJ3TKh0qSweNK5bQz3gUL2qAjZZF2yuysqtWC3c-9Pg05JwrNmGLn0k8DsjnebyrdzPcP7N3MRiL6507hL8OTVTY</recordid><startdate>19940201</startdate><enddate>19940201</enddate><creator>Hermens, L.A.</creator><creator>Shlimmer, J.C.</creator><general>IEEE</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>19940201</creationdate><title>A machine-learning apprentice for the completion of repetitive forms</title><author>Hermens, L.A. ; Shlimmer, J.C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c281t-5f291c84efa522c118fe12ce2a3cf60e8208853a4a8caf91482ae392eb38b9373</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1994</creationdate><topic>Computer errors</topic><topic>Computer networks</topic><topic>Government</topic><topic>Image recognition</topic><topic>Image segmentation</topic><topic>Machine learning</topic><topic>Microcomputers</topic><topic>NASA</topic><topic>Routing</topic><topic>Workstations</topic><toplevel>online_resources</toplevel><creatorcontrib>Hermens, L.A.</creatorcontrib><creatorcontrib>Shlimmer, J.C.</creatorcontrib><collection>CrossRef</collection><jtitle>IEEE expert</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hermens, L.A.</au><au>Shlimmer, J.C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A machine-learning apprentice for the completion of repetitive forms</atitle><jtitle>IEEE expert</jtitle><stitle>EX-M</stitle><date>1994-02-01</date><risdate>1994</risdate><volume>9</volume><issue>1</issue><spage>28</spage><epage>33</epage><pages>28-33</pages><issn>0885-9000</issn><eissn>2374-9407</eissn><coden>IEEXE7</coden><abstract>The authors have developed a software environment in which workers can complete repetitive forms, and a machine-learning and prediction system that works within it. The nonintrusive assistant or apprentice provides viable default values for blank fields in a form, saving users up to 87 percent in keystroke effort and correctly predicting nearly 90 percent of the form's values. The system and prediction methods are active, yet not intrusive. Default predictions are always displayed, yet the user can override them easily with normal editing commands.< ></abstract><pub>IEEE</pub><doi>10.1109/64.295135</doi><tpages>6</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0885-9000 |
ispartof | IEEE expert, 1994-02, Vol.9 (1), p.28-33 |
issn | 0885-9000 2374-9407 |
language | eng |
recordid | cdi_ieee_primary_295135 |
source | IEEE Xplore (Online service) |
subjects | Computer errors Computer networks Government Image recognition Image segmentation Machine learning Microcomputers NASA Routing Workstations |
title | A machine-learning apprentice for the completion of repetitive forms |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-26T13%3A46%3A41IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-crossref_ieee_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20machine-learning%20apprentice%20for%20the%20completion%20of%20repetitive%20forms&rft.jtitle=IEEE%20expert&rft.au=Hermens,%20L.A.&rft.date=1994-02-01&rft.volume=9&rft.issue=1&rft.spage=28&rft.epage=33&rft.pages=28-33&rft.issn=0885-9000&rft.eissn=2374-9407&rft.coden=IEEXE7&rft_id=info:doi/10.1109/64.295135&rft_dat=%3Ccrossref_ieee_%3E10_1109_64_295135%3C/crossref_ieee_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c281t-5f291c84efa522c118fe12ce2a3cf60e8208853a4a8caf91482ae392eb38b9373%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=295135&rfr_iscdi=true |