What's Important About Knowledge Representation?
TL;DR: The author discusses a number of issues that serve as research goals for discovering the principles of knowledge representation, using techniques and concepts evolved while developing the knowledge-representation system KL-one as illustrations.
Abstract: The author discusses a number of issues that serve as research goals for discovering the principles of knowledge representation, using techniques and concepts evolved while developing the knowledge-representation system KL-one as illustrations. The focus is on what constitutes a good representational system and a good set of representational primitives for dealing with an open-ended range of knowledge domains. Issues of interest include those problems that arise in attempting to construct intelligent computer programs that use knowledge to perform some task. 7 references.
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TL;DR: KL-ONE as mentioned in this paper is a system for representing knowledge in Artificial Intelligence programs and has been used in both basic research and implemented knowledge-based systems in a number of places in the AI community.
1,719Â citations
TL;DR: A frame-based representation facility contributes to a knowledge system's ability to reason and can assist the system designer in determining strategies for controlling the system's reasoning.
Abstract: A frame-based representation facility contributes to a knowledge system's ability to reason and can assist the system designer in determining strategies for controlling the system's reasoning.
858Â citations
Proceedings Articleâ˘
06 Aug 1984TL;DR: This work defines the correct partial ordering to use in inheritance and shows how it applies to semantic network systems.
Abstract: There is a natural partial ordering of defaults in inheritance systems that resolves ambiguities in an intuitive way. This is not the shortest-path ordering used by most existing inheritance reasoners. The flaws of the shortest-path ordering become apparent when we consider multiple inheritance. We define the correct partial ordering to use in inheritance and show how it applies to semantic network systems. Use of this ordering also simplifies the representation of inheritance in default logic.
132Â citations
Patentâ˘
24 Oct 1986TL;DR: This paper proposed a method and an apparatus for generating/maintaining automatically or interactively a lexicon for storing information of cooccurrence relations utilized for determining whether or not a sequence of words in a given sentence described in a natural language is semantically correct with the aid of a memory, a data processor and a textual sentence file.
Abstract: A method and an apparatus for generating/maintaining automatically or interactively a lexicon for storing information of cooccurrence relations utilized for determining whether or not a sequence of words in a given sentence described in a natural language is semantically correct with the aid of a memory, a data processor and a textual sentence file. A hypothesized cooccurrence relation table for storing hypothesized cooccurrence relations each having a high probabliity of being a valid cooccurrence relation is prepared by consulting the file. A hypothesis for the cooccurrence relation is previously established on the basis of a cooccurrence relation pattern indicating a probably acceptable conjunction by consulting the hypothesized cooccurrence relation table. Subsequently, a corresponding actual cooccurrence relation is derived from the textual file by parsing the relevant textual sentence and is tested to determine whether the cooccurrence relation is valid or not with reference to predetermined threshold conditions. On the basis of the results of the test, the information of the cooccurrence relation is correspondingly modified. The present method and apparatus can be utilized in a natural language parsing system and a machine translation system.
113Â citations
TL;DR: The major emerging trends in temporal representation and reasoning as well as the relationships with other wellâestablished areas, such as temporal databases and logic programming are analyzed.
Abstract: Time is one of the most relevant topics in AI. It plays a major role in several areas, ranging from logical foundations to applications of knowledgedbased systems. In this paper, we survey a wide range of research in temporal representation and reasoning, without committing ourselves to the point of view of any specific application. The organization of the paper follows the commonly recognized division of the field in two main subfields: reasoning about actions and change, and reasoning about temporal constraints. We give an overview of the basic issues, approaches, and results in these two areas, and outline relevant recent developments. Furthermore, we briefly analyze the major emerging trends in temporal representation and reasoning as well as the relationships with other welldestablished areas, such as temporal databases and logic programming.
110Â citations
Cites background from "What's Important About Knowledge Re..."
...With respect to the expressive power, time granularity and abstraction increase both the temporal distinctions that a language can make and the distinctions that it can leave unspecified [247]....
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References
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Bookâ˘
01 Jan 1975
TL;DR: The use of narrative and other prose forms as a tool for investigating mental processes is not new as discussed by the authors, and there has been a renewal of interest in the study of narratives and memory due to the recognition that narrative taps certain processes that syllables and isolated words do not.
Abstract: The use of narrative and other prose forms as a tool for investigating mental processes is not new. Psychologists such as Jean Piaget and F.C. Bartlett both used stories in research on complex cognitive skills in children and adults. However, with the advent of Ebbinghaus' monumental work on memory using "nonsense syllables," theoretical psychology turned away from the use of meaningful material. With the use of nonsense syllables, researchers hoped to isolate the variables of memory and individual content associations. Recently, there has been a renewal of interest in the study of narrative and memory due to the recognition that narrative taps certain processes that syllables and isolated words do not. In addition, narrative and memory studies have generated interest among those researchers concerned with the applicability of memory studies to educational settings. Disciplines Child Psychology | Cognitive Psychology | Early Childhood Education | Education | Educational Psychology | Language and Literacy Education This review is available at ScholarlyCommons: https://repository.upenn.edu/literacyorg_articles/26 VOL. 22 KEYSTONE FOLKLORE NO. 1-2
956Â citations
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01 Jan 1975
TL;DR: The chapter presents the logical inadequacies of almost all current network notations for representing quantified information and also discusses some of the disadvantages of a few logically adequate techniques.
855Â citations
01 Nov 1975
TL;DR: In this paper, the theoretical underpinnings for semantic network representations are discussed and the logical inadequacies of almost all current network notations for representing quantified information are discussed.
Abstract: Publisher Summary This chapter focuses on the theoretical underpinnings for semantic network representations. It also focuses on several issues, such as the meaning of semantics, the need for explicit understanding of the intended meanings for various types of arcs and links, the need for careful thought in choosing conventions for representing facts as assemblages of arcs and nodes, and several specific difficult problems in knowledge representationâespecially problems of relative clauses and quantification. When the semantics of the notations are made clear, many of the techniques used in existing semantic networks are inadequate for representing knowledge in general. The chapter presents the logical inadequacies of almost all current network notations for representing quantified information and also discusses some of the disadvantages of a few logically adequate techniques.
743Â citations
Proceedings Articleâ˘
18 Aug 1980TL;DR: The RUS framework for natural language processing is described, in which a parser incorporating a substantial ATN grammar for English interacts with a semantic interpreter to simultaneously parse and interpret input.
Abstract: This paper describes the RUS framework for natural language processing, in which a parser incorporating a substantial ATN grammar for English interacts with a semantic interpreter to simultaneously parse and interpret input. The structure of that interaction is discussed, including the roles played by syntactic and semantic knowledge. Several implementations of the RUS framework are currently in use, sharing the same grammar, but differing in the form of their semantic component. One of these, the PSI-KLONE system, is based on a general object-centered knowledge representation system, called KL-ONE. The operation of PSI-KLONE is described, including its use of KL-ONE to support a general inference process called "incremental description refinement." The last section of the paper discusses several important criteria for knowledge representation systems to be used in syntactic and semantic processing.
239Â citations
01 Jan 1978
TL;DR: In this chapter a brief overview of pattern-directed inference systems is presented, including an historical perspective, a review of basic concepts, and a survey of current work in this area.
Abstract: Pattern-directed inference systems are programs that look for interesting or important situations occuring as patterns in their input or memory data. These patterns select pieces of program code to be executed. In this chapter a brief overview of pattern-directed inference systems is presented, including an historical perspective, a review of basic concepts, and a survey of current work in this area. Examples of the best known type of pattern-directed inference system, the production system, are presented and discussed in detail.
132Â citations