Parsimonious covering as a method for natural language interfaces to expert systems

Abstract Abductive inference has been characterized in the AI literature as ‘inference to the best explanation’ or as ‘plausible inference involving context-sensitive discrimination among explanatory hypotheses’. Analogously, understanding natural language involves context-sensitive discrimination among word senses, and there has been a growing awareness that it can be viewed as a type of abductive inference. Parsimonious covering theory, first formulated to model the abductive inference underlying medical diagnostic problem solving, is examined here as a method for automating natural language processing for medical expert system interfaces. The nature of ‘parsimony’ in natural language processing and the relationship of parsimonious covering to a notion of focus of attention are discussed. An experimental prototype developed to test these ideas in the context of a medical expert system is briefly described. This prototype is domain-independent in the same sense that a generic expert system shell is domain-independent. Given a knowledge base for a specific medical application, a vocabulary extractor extracts and indexes the linguistic information which it contains. In addition, an indexed domain-independent knowledge base that contains linguistic knowledge common to many domains is used. With a parsimonious covering inference mechanism superimposed on this knowledge, a natural language interface is generated for the specific application defined by the knowledge base.

[1]  James A. Reggia,et al.  Diagnostic Expert Systems Based on a Set Covering Model , 1983, Int. J. Man Mach. Stud..

[2]  J. Fodor,et al.  The structure of a semantic theory , 1963 .

[3]  Roger C. Schank,et al.  Computer Models of Thought and Language , 1974 .

[4]  Yun Peng,et al.  A Probabilistic Causal Model for Diagnostic Problem Solving Part I: Integrating Symbolic Causal Inference with Numeric Probabilistic Inference , 1987, IEEE Transactions on Systems, Man, and Cybernetics.

[5]  James A. Reggia,et al.  A formal model of diagnostic inference. I. Problem formulation and decomposition , 1985, Inf. Sci..

[6]  Eugene Charniak,et al.  A Neat Theory of Marker Passing , 1986, AAAI.

[7]  Yun Peng,et al.  A Probabilistic Causal Model for Diagnostic Problem Solving Part II: Diagnostic Strategy , 1987, IEEE Transactions on Systems, Man, and Cybernetics.

[8]  Candace L. Sidner,et al.  Attention, Intentions, and the Structure of Discourse , 1986, CL.

[9]  Daniel B. Hier,et al.  Using Set Covering and Uncertain Reasoning to Determine Treatments , 1987 .

[10]  Chuck Rieger,et al.  An Organization of Knowledge for Problem Solving and Language Comprehension , 1976, Artif. Intell..

[11]  Harry E. Pople,et al.  Session 6 Theorem Proving and Logic: I I ON THE MECHANIZATION OF ABDUCTIVE LOGIC , 2006 .

[12]  J A Reggia,et al.  Modelling reading aloud and its relevance to acquired dyslexia. , 1985, Computer methods and programs in biomedicine.

[13]  Eugene Charniak,et al.  Passing Markers: A Theory of Contextual Influence in Language Comprehension* , 1983 .

[14]  G. Gorry,et al.  Clinical problem solving: a behavioral analysis. , 1978, Annals of internal medicine.

[15]  Judea Pearl,et al.  On Evidential Reasoning in a Hierarchy of Hypotheses , 1990, Artif. Intell..

[16]  Barbara J. Grosz,et al.  Focusing and Description in Natural Language Dialogues , 1979 .

[17]  Brian C. Williams,et al.  Reasoning about Multiple Faults , 1986, AAAI.

[18]  Yun Peng,et al.  Plausibility of Diagnostic Hypotheses: The Nature of Simplicity , 1986, AAAI.

[20]  G F Cooper,et al.  A diagnostic method that uses causal knowledge and linear programming in the application of Bayes' formula. , 1986, Computer methods and programs in biomedicine.

[21]  James F. Allen,et al.  A Plan Recognition Model for Subdialogues in Conversations , 1987, Cogn. Sci..

[22]  Raymond Reiter,et al.  A Theory of Diagnosis from First Principles , 1986, Artif. Intell..

[23]  Jack W. Smith,et al.  Assembling the best explanation , 1984 .

[24]  Henry A. Kautz.  A formal theory of plan recognition , 1987 .

[25]  Diane J. Litman,et al.  Plan recognition and discourse analysis: an integrated approach for understanding dialogues , 1986 .

[26]  Yun Peng,et al.  Diagnostic problem‐solving with causal chaining , 1987, Int. J. Intell. Syst..