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Title: Knowledge-Worker Requirements for Next Generation Query Answering & Explanation Systems

Abstract

Knowledge workers need tools to help them navigate through, evaluate, and understand large stores of information. Motivated by the needs of ARDA's, Novel Intelligence from Massive Data program, Battelle, Stanford University, and IBM have developed a suite of technologies for knowledge discovery, knowledge extraction, knowledge representation, automated reasoning, explanation, and human information interaction. Our team has developed an integrated analytic environment composed of a collection of analyst associates, software components that aid the analyst at different stages of the analytical process, collectively known as 'Knowledge Associates for Novel Intelligence (KANI)'. As part of this effort, we have incorporated a Query Answering and Explanation component that allows analysts to pose questions of the system based on the knowledge it has of a particular domain and specific tasking (problem). Answers are presented along with optional information about sources, assumptions, explanation summaries, and interactive justifications. This paper describes the analyst requirements and response to the explanation component of the KANI system. We believe the explanation infrastructure, its interface for analysts and knowledge workers, and the provenance requirements are all contributions that are leverageable beyond the KANI implementation.

Authors:
; ; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
895458
Report Number(s):
PNWD-SA-7220
TRN: US200702%%787
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Conference
Resource Relation:
Conference: Proceedings of the Workshop on Intelligent User Interfaces for Intelligence Analysis, International Conference on Intelligent User Interfaces (IUI 2006), January 29 - February 1, 2006, Sydney, Australia
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; INFORMATION SYSTEMS; MAN-MACHINE SYSTEMS; INFORMATION RETRIEVAL; K CODES

Citation Formats

Cowell, Andrew J., McGuinness, Deborah L., Varley, Caroline F., and Thurman, David A. Knowledge-Worker Requirements for Next Generation Query Answering & Explanation Systems. United States: N. p., 2006. Web.
Cowell, Andrew J., McGuinness, Deborah L., Varley, Caroline F., & Thurman, David A. Knowledge-Worker Requirements for Next Generation Query Answering & Explanation Systems. United States.
Cowell, Andrew J., McGuinness, Deborah L., Varley, Caroline F., and Thurman, David A. Sun . "Knowledge-Worker Requirements for Next Generation Query Answering & Explanation Systems". United States. doi:.
@article{osti_895458,
title = {Knowledge-Worker Requirements for Next Generation Query Answering & Explanation Systems},
author = {Cowell, Andrew J. and McGuinness, Deborah L. and Varley, Caroline F. and Thurman, David A.},
abstractNote = {Knowledge workers need tools to help them navigate through, evaluate, and understand large stores of information. Motivated by the needs of ARDA's, Novel Intelligence from Massive Data program, Battelle, Stanford University, and IBM have developed a suite of technologies for knowledge discovery, knowledge extraction, knowledge representation, automated reasoning, explanation, and human information interaction. Our team has developed an integrated analytic environment composed of a collection of analyst associates, software components that aid the analyst at different stages of the analytical process, collectively known as 'Knowledge Associates for Novel Intelligence (KANI)'. As part of this effort, we have incorporated a Query Answering and Explanation component that allows analysts to pose questions of the system based on the knowledge it has of a particular domain and specific tasking (problem). Answers are presented along with optional information about sources, assumptions, explanation summaries, and interactive justifications. This paper describes the analyst requirements and response to the explanation component of the KANI system. We believe the explanation infrastructure, its interface for analysts and knowledge workers, and the provenance requirements are all contributions that are leverageable beyond the KANI implementation.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sun Jan 29 00:00:00 EST 2006},
month = {Sun Jan 29 00:00:00 EST 2006}
}

Conference:
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