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ReferencesNavigation arrowAuthorsNavigation arrowB. Chandrasekaran

Publication statistics

Pub. period:1979-2007
Pub. count:17
Number of co-authors:19



Co-authors

Number of publications with 3 favourite co-authors:

Bonny Banerjee:4
Sanjay Mittal:3
David C. Brown:2

 

 

Productive colleagues

B. Chandrasekaran's 3 most productive colleagues in number of publications:

Norman K. Sondheim..:9
Ashok K. Goel:7
Sanjay Mittal:6
 
 
 
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B. Chandrasekaran

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Publications by B. Chandrasekaran (bibliography)

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2007
 
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Banerjee, Bonny and Chandrasekaran, B. (2007): Representations and Strategies for Solving Spatial Problems with Diagrams. In: VL-HCC 2007 - IEEE Symposium on Visual Languages and Human-Centric Computing 23-27 September, 2007, Coeur dAlene, Idaho, USA. pp. 183-188.

2006
 
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Banerjee, Bonny and Chandrasekaran, B. (2006): Synthesizing Visual and Action Routines Using Constraint Programming. In: Barker-Plummer, Dave, Cox, Richard and Swoboda, Nik (eds.) Diagrams 2006 - Diagrammatic Representation and Inference - 4th International Conference June 28-30, 2006, Stanford, CA, USA. pp. 196-198.

 
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Chandrasekaran, B. (2006): Diagrams as Physical Models. In: Barker-Plummer, Dave, Cox, Richard and Swoboda, Nik (eds.) Diagrams 2006 - Diagrammatic Representation and Inference - 4th International Conference June 28-30, 2006, Stanford, CA, USA. pp. 204-217.

2004
 
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Banerjee, Bonny and Chandrasekaran, B. (2004): Constructing Diagrams Representing Group Motions. In: Blackwell, Alan, Marriott, Kim and Shimojima, Atsushi (eds.) Diagrams 2004 - Diagrammatic Representation and Inference - Third International Conference March 22-24, 2004, Cambridge, UK. pp. 376-378.

 
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Chandrasekaran, B., Kurup, Unmesh, Banerjee, Bonny, Josephson, John R. and Winkler, Robert (2004): An Architecture for Problem Solving with Diagrams. In: Blackwell, Alan, Marriott, Kim and Shimojima, Atsushi (eds.) Diagrams 2004 - Diagrammatic Representation and Inference - Third International Conference March 22-24, 2004, Cambridge, UK. pp. 151-165.

2002
 
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Chandrasekaran, B. (2002): What Does It Mean for a Computer to Do Diagrammatic Reasoning? A Functional Characterization of Diagrammatic Reasoning and Its Implications. In: Hegarty, Mary, Meyer, Bernd and Narayanan, N. Hari (eds.) Diagrams 2002 - Diagrammatic Representation and Inference - Second International Conference April 18-20, 2002, Callaway Gardens, GA, USA. pp. 1-2.

1999
 
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Chandrasekaran, B. and Mittal, Sanjay (1999): Deep Versus Compiled Knowledge Approaches to Diagnostic Problem-Solving. In International Journal of Human-Computer Studies, 51 (2) pp. 357-368.

“Most of the current generation expert systems use knowledge which does not represent a deep understanding of the domain, but is instead a collection of "pattern action" rules, which correspond to the problem-solving heuristics of the expert in the domain. There has thus been some debate in the field about the need for and role of "deep" knowledge in the design of expert systems. It is often argued that this underlying deep knowledge will enable an expert system to solve hard problems. In this paper we consider diagnostic expert systems and argue that given a body of underlying knowledge that is relevant to diagnostic reasoning in a medical domain, it is possible to create a diagnostic problem-solving structure which has all the aspects of the underlying knowledge needed for diagnostic reasoning "compiled" into it. It is argued this compiled structure can solve all the diagnostic problems in its scope efficiently, without any need to access the underlying structures. We illustrate such a diagnostic structure by reference to our medical system MDX. We also analyze the use of these knowledge structures in providing explanations of diagnostic reasoning.”

© All rights reserved Chandrasekaran and Mittal and/or Academic Press

1993
 
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Chandrasekaran, B., Goel, Ashok K. and Iwasaki, Yumi (1993): Functional Representation as Design Rationale. In IEEE Computer, 26 (1) pp. 48-56.

1992
 
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Chandrasekaran, B., Johnson, Todd R. and Smith, Jack W. (1992): Task-Structure Analysis for Knowledge Modeling. In Communications of the ACM, 35 (9) pp. 124-137.

1991
 
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Chandrasekaran, B., Bhatnager, R. and Sharma, D. D. (1991): Real-Time Disturbance Control. In Communications of the ACM, 34 (8) pp. 32-47.

1989
 
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Chandrasekaran, B., Josephson, John, Keuneke, Anne and Herman, David (1989): Building Routine Planning Systems and Explaining Their Behaviour. In International Journal of Man-Machine Studies, 30 (4) pp. 377-398.

“It has become increasingly clear to builders of knowledge-based systems that no single representational formalism or control construct is optimal for encoding the wide variety of types of problem solving that commonly arise and are of practical significance. In this paper we identify a class of problem solving activities which we have labeled routine planning. We consider the constructs necessary to represent the problem solving which appropriately characterizes this class, and describe DSPL, a high-level language designed specifically to encompass the required knowledge structures and control methodology for routine planning. Finally, we consider what type of structure is appropriate to represent an agent's understanding of how the plan itself works.”

© All rights reserved Chandrasekaran et al. and/or Academic Press

1987
 
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Bylander, Tom and Chandrasekaran, B. (1987): Generic Tasks for Knowledge-Based Reasoning: The "Right" Level of Abstraction for Knowledge Acquisition. In International Journal of Man-Machine Studies, 26 (2) pp. 231-243.

“Our research strategy has been to identify generic tasks -- basic combinations of knowledge structures and inference strategies that are powerful for solving certain kinds of problems. Our strategy is best understood by considering the "interaction problem", that representing knowledge for the purpose of solving some problem is strongly affected by the nature of the problem and by the inference strategy to be applied to the knowledge. The interaction problem implies that different knowledge-acquisition methodologies will be required for different kinds of reasoning, e.g. a different knowledge-acquisition methodology for each generic task. We illustrate this using the generic task of hierarchical classification. Our proposal and the interaction problem call into question many generally held beliefs about experts systems such as the belief that the knowledge base should be separated from the inference engine.”

© All rights reserved Bylander and Chandrasekaran and/or Academic Press

 
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Bylander, Tom, Chandrasekaran, B. and Josephson, John R. (1987): The Generic Task Toolset. In: Salvendy, Gavriel (ed.) HCI International 1987 - Proceedings of the Second International Conference on Human-Computer Interaction - Volume 2 August 10-14, 1987, Honolulu, Hawaii. pp. 507-514.

1986
 
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Brown, David C. and Chandrasekaran, B. (1986): Knowledge and Control for a Mechanical Design Expert System. In IEEE Computer, 19 (7) pp. 92-100.

1984
 
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Mittal, Sanjay, Chandrasekaran, B. and Sticklen, Jon (1984): Patrec: A Knowledge-Directed Database for a Diagnostic Expert System. In IEEE Computer, 17 (9) pp. 51-58.

1983
 
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Chandrasekaran, B. and Mittal, Sanjay (1983): Deep versus Compiled Knowledge Approaches to Diagnostic Problem-Solving. In International Journal of Man-Machine Studies, 19 (5) pp. 425-436.

“Most of the current generation expert systems use knowledge which does not represent a deep understanding of the domain, but is instead a collection of "pattern -> action" rules, which correspond to the problem-solving heuristics of the expert in the domain. There has thus been some debate in the field about the need for and role of "deep" knowledge in the design of expert systems. It is often argued that this underlying deep knowledge will enable an expert system to solve hard problems. In this paper we consider diagnostic expert systems and argue that given a body of underlying knowledge that is relevant to diagnostic reasoning in a medical domain, it is possible to create a diagnostic problem-solving structure which has all the aspects of the underlying knowledge needed for diagnostic reasoning "compiled" into it. It is argued this compiled structure can solve all the diagnostic problems in its scope efficiently, without any need to access the underlying structures. We illustrate such a diagnostic structure by reference to our medical system MDX. We also analyze the use of these knowledge structures in providing explanations of diagnostic reasoning.”

© All rights reserved Chandrasekaran and Mittal and/or Academic Press

1979
 
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Brown, David C., Kwasny, Stanley C., Chandrasekaran, B. and Sondheimer, Norman K. (1979): An experimental graphics system with natural language input. In Computers & Graphics, 4 (1) pp. 13-22.

 
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Page maintainer: The Editorial Team
URL: http://www.interaction-design.org/references/authors/b__chandrasekaran.html

Publication statistics

Pub. period:1979-2007
Pub. count:17
Number of co-authors:19



Co-authors

Number of publications with 3 favourite co-authors:

Bonny Banerjee:4
Sanjay Mittal:3
David C. Brown:2

 

 

Productive colleagues

B. Chandrasekaran's 3 most productive colleagues in number of publications:

Norman K. Sondheim..:9
Ashok K. Goel:7
Sanjay Mittal:6
 
 
 
May 20

“ The moment clients realize that revisions are not an all-you-can-eat buffet, suddenly they realize they are not hungry. ”

-- Lester Beall

 
 

Featured chapter

Read the fascinating history of Wearable Computing, told by its father, Steve Mann

Read Steve's chapter !

 
 

Help us help you!

 
 
 
 
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