Article

An integrated environment for knowledge acquisition

Authors:

Surya Ramachandran,

Yolanda GilAuthors Info & Claims

IUI '01: Proceedings of the 6th international conference on Intelligent user interfaces

Pages 13 - 20

https://doi.org/10.1145/359784.359819

Published: 01 January 2001 Publication History

Abstract

This paper describes an integrated acquisition interface that includes several techniques previously developed to support users in various ways as they add new knowledge to an intelligent system. As a result of this integration, the individual techniques can take better advantage of the context in which they are invoked and provide stronger guidance to users. We describe the current implementation using examples from a travel planning domain, and demonstrate how users can add complex knowledge to the system.

References

[1]

G. Abbrett and M. Burstein. The kreme knowledge editing environment. International Journal of Man-Machine Studies, 27(2):103-126, August 1987.

Digital Library

[2]

J. Blythe. Extending the role-limiting approach: Supporting end users to acquire problem-solving knowledge. In ECAI 2000 Workshop on Applications of Ontologies and Problem-Solving Methods, 2000.

[3]

J. Blythe and S. Ramachandran. Knowledge acquisition using and english-based method editor. In Proc. Twelfth Knowledge Acquisition for Knowledge-Based Systems Workshop, Banff, Alberta, 1999.

[4]

J. H. Boose and J. M. Bradshaw. Expertise transfer and complex problems: Using aquinas as a knowledge acquisitiong workbench for knowledge-based systems. International Journal of Man-Machine Studies, 26, 1987.

Digital Library

[5]

A. Cypher. Bringing programming to end users. In Watch What I Do: Programming by Demonstration. MIT Press, 1993.

Digital Library

[6]

A. Farquhar, R. Fikes, and J. Rice. The ontolingua server: A tool for collaborative ontology construction. In Proc. Tenth Knowledge Acquisition for Knowledge-Based Systems Workshop, Banff, Alberta, 1996.

[7]

B. R. Gaines and M. L. G. Shaw. Eliciting knowledge and transferring it effectively to a knowledge-based system. IEEE Transactions on Knowledge and Data Engineering, 5(1), 1993.

Digital Library

[8]

Y. Gil and E. Melz. Explicit representations of problem-solving strategies to support knowledge acquisition. In Proc. Thirteenth National Conference on Artificial Intelligence. AAAI Press, 1996.

Digital Library

[9]

P. D. Karp, V. K. Chaudhri, and S. M. Paley. A collaborative environment for authoring large knowledge bases. Journal of Intelligent Information Systems, 13:155-194, 1999.

Digital Library

[10]

J. Kim and Y. Gil. Deriving expectations to guide knowledge-base creation. In Proc. Sixteenth National Conference on Artificial Intelligence, pages 235-241. AAAI Press, 1999.

Digital Library

[11]

J. Kim and Y. Gil. Acquiring problem-solving knowledge from end users: Putting interdependency models to the test. In Proc. Seventeenth National Conference on Artificial Intelligence. AAAI Press, 2000.

Digital Library

[12]

G. Linden, S. Hanks, and N. Lesh. Interactive assessment of user preference models: The automated travel assistant. Sixth International Conference on User Modelling, 1997.

[13]

D. L. McGuinness, R. Fikes, J. Rice, and S. Wilder. The chimaera ontology environment. In Proc. Seventeenth National Conference on Artificial Intelligence. AAAI Press, 2000.

Digital Library

[14]

K. Myers. Strategic advice for hierarchical planners. In Proceedings of the International Conference on Knowledge Representation, 1996.

[15]

A. R. Puerta, J. W. Egar, S. Tu, and M. A. Musen. A multiple-method knowledge acquisition shell for the automatic generation of knowledge acquisition tools. Knowledge Acquisition, 4(2):171-196, 1992.

Digital Library

[16]

B. Swartout, R. Patil, K. Knight, and T. Russ. Towards distributed use of large-scale ontologies. In Proc. Tenth Knowledge Acquisition for Knowledge-Based Systems Workshop, Banff, Alberta, 1996.

[17]

W. R. Swartout and Y. Gil. Expect: Explicit representations for flexible acquisition. In Proc. Ninth Knowledge Acquisition for Knowledge-Based Systems Workshop, Banff, Alberta, 1995.

[18]

M. Tallis and Y. Gil. Designing scripts to guide users in modifying knowledge-based systems. In Proc. Sixteenth National Conference on Artificial Intelligence. AAAI Press, 1999.

Digital Library

[19]

L. G. Terveen and D. A. Wroblewski. a collaborative interface for browsing and editing large knowledge bases. In Proc. Eighth National Conference on Artificial Intelligence. AAAI Press, 1990.

Cited By

Yanchinda JSinthamrongruk TDahal K(2017)STEM learning concept with fuzzy inference for organic rice farming knowledge acquisition2017 11th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)10.1109/SKIMA.2017.8294113(1-8)Online publication date: Dec-2017
https://doi.org/10.1109/SKIMA.2017.8294113
Lorenzetti CMaguitman ALeake DMenczer FReichherzer T(2016)Mining for Topics to Suggest Knowledge Model ExtensionsACM Transactions on Knowledge Discovery from Data10.1145/299765711:2(1-30)Online publication date: 3-Dec-2016
https://dl.acm.org/doi/10.1145/2997657
Han SYoon HKang BPark S(2014)Using MCRDR based Agile approach for expert system developmentComputing10.1007/s00607-013-0336-y96:9(897-908)Online publication date: 1-Sep-2014
https://dl.acm.org/doi/10.1007/s00607-013-0336-y
Show More Cited By

Index Terms

An integrated environment for knowledge acquisition
1. Computing methodologies
  1. Machine learning
    1. Learning settings
2. Human-centered computing
  1. Human computer interaction (HCI)

Recommendations

Case-based manufacturing process planning with integrated support for knowledge sharing
ISATP '95: Proceedings of the 1995 IEEE International Symposium on Assembly and Task Planning

Abstract: Computer aided process planning is a key part of bridging the link between design and manufacturing. Case-based reasoning provides an attractive paradigm for process planning as it combines the generative and variant approaches and improves ...
Automated Acquisition of Control Knowledge to Improve the Quality of Plans
Knowledge Intensive Planning

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

IUI '01: Proceedings of the 6th international conference on Intelligent user interfaces

January 2001

174 pages

ISBN:1581133251

DOI:10.1145/359784

Chairmen:
Candy Sidner
MERL
,
Johanna Moore
Univ. of Edinburgh, Edinburgh, Scotland

Copyright © 2001 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGAI: ACM Special Interest Group on Artificial Intelligence
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
AAAI: Am Assoc for Artifical Intelligence

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 January 2001

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Qualifiers

Article

Conference

IUI01

Sponsor:

IUI01: International Conference on Intelligent User Interfaces 2001

January 14 - 17, 2001

New Mexico, Santa Fe, USA

Acceptance Rates

Overall Acceptance Rate 746 of 2,811 submissions, 27%

Upcoming Conference

IUI '25

Sponsor:
sigai
sigai

30th International Conference on Intelligent User Interfaces

March 24 - 27, 2025

Cagliari , Italy

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

55
Total Citations
View Citations
969
Total Downloads

Downloads (Last 12 months)9
Downloads (Last 6 weeks)4

Reflects downloads up to 28 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Yanchinda JSinthamrongruk TDahal K(2017)STEM learning concept with fuzzy inference for organic rice farming knowledge acquisition2017 11th International Conference on Software, Knowledge, Information Management and Applications (SKIMA)10.1109/SKIMA.2017.8294113(1-8)Online publication date: Dec-2017
https://doi.org/10.1109/SKIMA.2017.8294113
Lorenzetti CMaguitman ALeake DMenczer FReichherzer T(2016)Mining for Topics to Suggest Knowledge Model ExtensionsACM Transactions on Knowledge Discovery from Data10.1145/299765711:2(1-30)Online publication date: 3-Dec-2016
https://dl.acm.org/doi/10.1145/2997657
Han SYoon HKang BPark S(2014)Using MCRDR based Agile approach for expert system developmentComputing10.1007/s00607-013-0336-y96:9(897-908)Online publication date: 1-Sep-2014
https://dl.acm.org/doi/10.1007/s00607-013-0336-y
Yoon HHan SKang BPark S(2012)V&V to Use Agile Approach in ES Development: Why RDR Works for Expert System Developments!Computer Applications for Software Engineering, Disaster Recovery, and Business Continuity10.1007/978-3-642-35267-6_15(113-120)Online publication date: 2012
https://doi.org/10.1007/978-3-642-35267-6_15
Zhuo HYang QPan RLi L(2011)Cross-domain action-model acquisition for planning via web searchProceedings of the Twenty-First International Conference on International Conference on Automated Planning and Scheduling10.5555/3038485.3038524(298-305)Online publication date: 11-Jun-2011
https://dl.acm.org/doi/10.5555/3038485.3038524
Gil Y(2011)Review: interactive knowledge capture in the new millenniumThe Knowledge Engineering Review10.1017/S026988891000040826:1(45-51)Online publication date: 1-Feb-2011
https://dl.acm.org/doi/10.1017/S0269888910000408
Panda SMishra D(2010)Development of a tribological failure knowledge modelInternational Journal of Knowledge Engineering and Data Mining10.1504/IJKEDM.2010.0348391:2(99-114)Online publication date: 1-Aug-2010
https://dl.acm.org/doi/10.1504/IJKEDM.2010.034839
Tallis MKim JGil Y(2010)User studies of knowledge acquisition tools: methodology and lessons learnedJournal of Experimental & Theoretical Artificial Intelligence10.1080/0952813011010026113:4(359-378)Online publication date: 9-Nov-2010
https://doi.org/10.1080/09528130110100261
Zhuo HYang QHu DLi L(2010)Learning complex action models with quantifiers and logical implicationsArtificial Intelligence10.1016/j.artint.2010.09.007174:18(1540-1569)Online publication date: 1-Dec-2010
https://dl.acm.org/doi/10.1016/j.artint.2010.09.007
(2010)ReferencesNo Code Required10.1016/B978-0-12-381541-5.00038-9(453-472)Online publication date: 2010
https://doi.org/10.1016/B978-0-12-381541-5.00038-9
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents