Bernardo Cuenca Grau and Adolfo Plasencia
- Published in print:
- 2017
- Published Online:
- January 2018
- ISBN:
- 9780262036016
- eISBN:
- 9780262339308
- Item type:
- chapter
- Publisher:
- The MIT Press
- DOI:
- 10.7551/mitpress/9780262036016.003.0015
- Subject:
- Society and Culture, Technology and Society
In this dialogue, Bernardo Cuenca Grau, a computer scientist at the Department of Computer Science, University of Oxford, begins by explaining his research in technology based on ontologies and ...
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In this dialogue, Bernardo Cuenca Grau, a computer scientist at the Department of Computer Science, University of Oxford, begins by explaining his research in technology based on ontologies and knowledge representation, somewhere between mathematics, philosophy, and computer science. He goes on to argue why we need to represent knowledge in a way that it can be processed by a computer and therefore enable automated reasoning of this knowledge using artificial intelligence. Later he explains how his investigation probes the limits of mathematics to find the most appropriate languages for developing practical applications. For example, the large-scale processing of structured information linked to comprehensive health systems. Bernardo is supportive of collective tools such as Wikipedia. He also discusses why in his opinion the success of a scientific or technological idea depends very much on luck, and why the semantic web has not been defined. Furthermore, he argues why bureaucracy confuses process with progress.Less
In this dialogue, Bernardo Cuenca Grau, a computer scientist at the Department of Computer Science, University of Oxford, begins by explaining his research in technology based on ontologies and knowledge representation, somewhere between mathematics, philosophy, and computer science. He goes on to argue why we need to represent knowledge in a way that it can be processed by a computer and therefore enable automated reasoning of this knowledge using artificial intelligence. Later he explains how his investigation probes the limits of mathematics to find the most appropriate languages for developing practical applications. For example, the large-scale processing of structured information linked to comprehensive health systems. Bernardo is supportive of collective tools such as Wikipedia. He also discusses why in his opinion the success of a scientific or technological idea depends very much on luck, and why the semantic web has not been defined. Furthermore, he argues why bureaucracy confuses process with progress.
Ronnie W. Smith and D. Richard Hipp
- Published in print:
- 1995
- Published Online:
- November 2020
- ISBN:
- 9780195091878
- eISBN:
- 9780197560686
- Item type:
- chapter
- Publisher:
- Oxford University Press
- DOI:
- 10.1093/oso/9780195091878.003.0008
- Subject:
- Computer Science, Human-Computer Interaction
Without development of an actual working system it is impossible to empirically validate the proposed computational model. Thus, the architecture introduced in section ...
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Without development of an actual working system it is impossible to empirically validate the proposed computational model. Thus, the architecture introduced in section 3.1 has been implemented on a Sun 4 workstation and later ported to a Spare II workstation. The majority of the code is written in Quintus Prolog while the parser is written in C. The system software is available via anonymous FTP as described in appendix C. The overall hardware configuration is illustrated in figure 6.1. Speech recognition is performed by a Verbex 6000 user-dependent connected-speech recognizer running on an IBM PC. The vocabulary is currently restricted to the 125 words given in table 7.1. Users are required to begin each utterance with the word “verbie” and end with the word “over” (e.g. “verbie, the switch is up, over”). The Verbex speech recognizer acknowledges each input with a small beep. These sentinel interactions act as a synchronization mechanism for the user arid the machine. Speech output is performed by a DECtalk DTCO1 text-to-speech converter. This chapter discusses the following technical aspects of the implementation. • The various knowledge representation formalisms. • The implemented domain processor, an expert system for assisting in simple circuit repair. • The implemented generation component. • The basic physical resource utilization of the system. The basis for the implementation has been the logic programming language, Prolog. Clocksin and Mellish [CM87] provide an introduction to this language. Pereira and Shieber [PS87] arid McCord [McC87] can be consulted for a discussion of the usage of Prolog for natural language analysis. Prolog allows the expression of rules and facts in a subset of first-order logic called Horn clauses. Prolog is supplemented with non-logical features that aid in efficient computation as well, but as a representational formalism, its utility in representing rules and facts in a declarative format provides a basis for the representation of knowledge and rules within the model. The Goal and Action Description Language was introduced in section 3.2.2. A detailed description is provided in appendix A. It is used as a standard formalism for representing goals that may be accomplished during a task.
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Without development of an actual working system it is impossible to empirically validate the proposed computational model. Thus, the architecture introduced in section 3.1 has been implemented on a Sun 4 workstation and later ported to a Spare II workstation. The majority of the code is written in Quintus Prolog while the parser is written in C. The system software is available via anonymous FTP as described in appendix C. The overall hardware configuration is illustrated in figure 6.1. Speech recognition is performed by a Verbex 6000 user-dependent connected-speech recognizer running on an IBM PC. The vocabulary is currently restricted to the 125 words given in table 7.1. Users are required to begin each utterance with the word “verbie” and end with the word “over” (e.g. “verbie, the switch is up, over”). The Verbex speech recognizer acknowledges each input with a small beep. These sentinel interactions act as a synchronization mechanism for the user arid the machine. Speech output is performed by a DECtalk DTCO1 text-to-speech converter. This chapter discusses the following technical aspects of the implementation. • The various knowledge representation formalisms. • The implemented domain processor, an expert system for assisting in simple circuit repair. • The implemented generation component. • The basic physical resource utilization of the system. The basis for the implementation has been the logic programming language, Prolog. Clocksin and Mellish [CM87] provide an introduction to this language. Pereira and Shieber [PS87] arid McCord [McC87] can be consulted for a discussion of the usage of Prolog for natural language analysis. Prolog allows the expression of rules and facts in a subset of first-order logic called Horn clauses. Prolog is supplemented with non-logical features that aid in efficient computation as well, but as a representational formalism, its utility in representing rules and facts in a declarative format provides a basis for the representation of knowledge and rules within the model. The Goal and Action Description Language was introduced in section 3.2.2. A detailed description is provided in appendix A. It is used as a standard formalism for representing goals that may be accomplished during a task.
