Semantic Networks

A username and password may be required for some online papers. Please contact Bill Rapaport.

1. History:
   1. The Tree of Porphyry
      • from John F. Sowa, Knowledge Representation (Pacific Grove, CA: Brooks/Cole).

      • English translation of Peter of Spain's (Pope John XXI's) version, also from Sowa.

   2. Masterman, M.M. (1957), "The Thesaurus in Syntax and Semantics", Mechanical Translation 4(1/2) (November): 35-43.
      • Arguably the first modern paper on semantic networks.

   3. Kruja, Eriola; Marks, Joe; Blair, Ann; & Waters, Richard (2001), "A Short Note on the History of Graph Drawing", Proceedings of the 9th International Symposium on Graph Drawing (GD 2001, Vienna) (Berlin: Springer Lecture Notes in Computer Science 2265): 272-286.

2. 3 Semantic-Network-based theories:
   1. The SNePS Knowledge Representation, Reasoning, and Acting System
      • SNePS (Semantic Network Processing System) is a KRRA system created by Stuart C. Shapiro and developed by him in collaboration with numerous colleagues and students.

   2. Quillian's semantic-network theory (one of the earliest in AI):
      • Quillian, M. Ross (1967), "Word Concepts: A Theory and Simulation of Some Basic Semantic Capabilities", Behavioral Science 12: 410-430.
        • Reprinted in Ronald J. Brachman & Hector J. Levesque (eds.), Readings in Knowledge Representation (Los Altos, CA: Morgan Kaufmann, 1985): 97-118.

        • Figure 4-1 [PDF]
        • Figure 4-1a [PDF]
        • Figure 4-1b [PDF]
        • Figure 4-2b [PDF]
        • Table 4-1 [PDF]
        • The "meaning" of a word (node) is its "location" in the entire network

      • Quillian, M. Ross (1968), "Semantic Memory", in Marvin Minsky (ed.) Semantic Information Processing (Cambridge, MA: MIT Press): 227-270.

      • Quillian, M . Ross (1969), "The Teachable Language Comprehender: A Simulation Program and Theory of Language", Communications of the Association for Computing Machinery 12(8): 459-476.
        • An important paper on the first semantic-network knowledge-representation-and-reasoning system in AI, and how to get it to read and comprehend a natural-language text.

      • Collins, Allan M. & Quillian, M. Ross (1969), "Retrieval Time from Semantic Memory", Journal of Verbal Learning and Verbal Behavior 8: 240-247.
        • LOCKWOOD Periodical Collection Per BF455.A1 J6
        • online abstract [PDF]
        • Collins & Quillian semantic network [PDF]

      • Johnson-Laird, P.N.; Herrman, D.J.; & Chaffin, R. (1984), "Only Connections: A Critique of Semantic Networks", Psychological Bulletin 96(2): 292-315.

        • To access articles from Psychological Bulletin, Psychological Review, or American Psychologist:
          1. Link to: UB Libraries Electronic Journals.
             • If you are off-campus, you may need to enter your UBIT username and password.

          2. Type the journal title into the Search box and click the "Search" button.
             • Other journals (e.g., Language, Proc. IRE) can be accessed in a similar fashion;
               most have much simpler interfaces than the one described here for Psych. Bul., Psych. Rev., and Amer. Psych.!

          3. Click on "Journals@Ovid PsycArticles".
          4. Find the volume and number that you are looking for (click the red "Next" button to go to earlier issues).
          5. Click the "Table of Contents" button for the issue you want.
          6. Find the article in the table of contents, and then click either
             "Complete Reference" for a full citation with abstract, or
             "Ovid Full Text" to download a PDF copy of the article.

   3. Roger Schank's theory of Conceptual Dependency.

3. Some references:
   1. Findler, Nicholas V. (ed.) (1979), Associative Networks: The Representation and Use of Knowledge by Computers (New York: Academic Press).
      • SCI/ENGR Book Collection Q360 .A87
      • Contains the first major paper on SNePS (there were earlier ones in conference publications; see the full SNeRG bibliography):
        Shapiro, Stuart C. (1979), "The SNePS Semantic Network Processing System", pp. 179-203.

   2. Evens, Martha Walton (ed.) (1988), Relational Models of the Lexicon: Representing Knowledge in Semantic Networks (Cambridge, UK: Cambridge University Press).

   3. Sowa, John F. (ed.) (1991), Principles of Semantic Networks: Explorations in the Representation of Knowledge (San Mateo, CA: Morgan Kaufmann).
      • LOCKWOOD Book Collection Q335 .P7 1991

   4. Lehmann, Fritz (ed.) (1992), Semantic Networks in Artificial Intelligence (Oxford: Pergamon Press).
      • Reprinted from Computers & Mathematics with Applications 23(2-5): 1-375 and 23(6-9): 377-758.

4. On the relationship between first-order logic and semantic networks:
   1. Israel, David J. & Brachman, Ronald J. (1981), "Distinctions and Confusions: A Catalogue Raisonné", Proceedings of the 7th International Joint Conference on Artificial Intelligence (IJCAI-81, University of British Columbia) (Los Altos: William Kaufmann): 452-459.

   2. Schubert, Lenhart K. (1991), "Semantic Nets Are in the Eye of the Beholder", in John F. Sowa (ed.), Principles of Semantic Networks: Explorations in the Representation of Knowledge (San Mateo, CA: Morgan Kaufmann): 95-107.

   3. Shastri, Lokendra (1991), "Why Semantic Networks?", in John F. Sowa (ed.), Principles of Semantic Networks: Explorations in the Representation of Knowledge (San Mateo, CA: Morgan Kaufmann): 109-136.

   4. On the difficulty of representing meta-knowledge (knowledge about knowledge) in FOL and how it can be done in SNePS:
      • 2 papers (and a review) on the difficulty of representing meta-knowledge in FOL:
        • des Rivières, Jim, & Levesque, Hector J. (1986), "The Consistency of Syntactical Treatments of Knowledge", in Joseph Y. Halpern (ed.), Theoretical Aspects of Reasoning about Knowledge: Proceedings of the 1986 Conference (TARK-86; Monterey, CA) (Los Altos, CA: Morgan Kaufmann): 115-130.

        • Asher, Nicholas M., & Kamp, Johan A.W. (1986), "The Knower's Paradox and Representational Theories of Attitudes", in Joseph Y. Halpern (ed.), Theoretical Aspects of Reasoning about Knowledge: Proceedings of the 1986 Conference (TARK-86; Monterey, CA) (Los Altos, CA: Morgan Kaufmann): 131-147.
          • Rapaport, William J. (1988), Review of Joseph Y. Halpern (ed.), Theoretical Aspects of Reasoning About Knowledge: Proceedings of the 1986 Conference (Los Altos, CA: Morgan Kaufmann, 1986), Journal of Symbolic Logic 53: 660-670.

      • 3 papers on how SNePS handles the problem:
        • Barnden, John A. (1986), "A Viewpoint Distinction in the Representation of Propositional Attitudes", Proceedings of the 5th National Conference on Artificial Intelligence (AAAI-86, Philadelphia) (Los Altos, CA: Morgan Kaufmann), Vol. 1, pp. 411-415.

        • Shapiro, Stuart C., & Rapaport, William J. (1991), "Models and Minds: Knowledge Representation for Natural-Language Competence", in Robert Cummins & John Pollock (eds.), Philosophy and AI: Essays at the Interface (Cambridge, MA: MIT Press): 215-259.
          Abstract: Cognitive agents, whether human or computer, that engage in natural-language discourse and that have beliefs about the beliefs of other cognitive agents must be able to represent objects the way they believe them to be and the way they believe others believe them to be. They must be able to represent other cognitive agents both as objects of beliefs and as agents of beliefs. They must be able to represent their own beliefs, and they must be able to represent beliefs as objects of beliefs. These requirements raise questions about the number of tokens of the belief representation language needed to represent believers and propositions in their normal roles and in their roles as objects of beliefs. In this paper, we explicate the relations among nodes, mental tokens, concepts, actual objects, concepts in the belief spaces of an agent and the agent's model of other agents, concepts of other cognitive agents, and propositions. We extend, deepen, and clarify our theory of intensional knowledge representation for natural-language processing, as presented in previous papers and in light of objections raised by others. The essential claim is that tokens in a knowledge-representation system represent only intensions and not extensions. We are pursuing this investigation by building CASSIE, a computer model of a cognitive agent and, to the extent she works, a cognitive agent herself. CASSIE's mind is implemented in the SNePS knowledge-representation and reasoning system.

        • Shapiro, Stuart C. (1993), "Belief Spaces as Sets of Propositions", Journal of Experimental and Theoretical Artificial Intelligence 5(2&3): 225-235.

5. Other semantic-network-related KRR theories:
   1. Frames

   2. Description Logics

   3. Concept Maps

6. Semantic Networks and the Web:
   1. Original Posters of the Internet

   2. Members of the Clever Project (1999), "Hypersearching the Web", Scientific American (June): 54-60.

   3. Berners-Lee, Tim; Hendler, James; & Lassila, Ora (2001), "The Semantic Web", Scientific American (May): 35-43.

   4. Feigenbaum, Lee; Herman, Ivan; Hongsermeier, Tonya; Neumann, Eric; & Stephens, Susie (2007), "The Semantic Web in Action", Scientific American 297(6) (December): 90-97.

7. Miscellaneous:
   1. Taylor, M.M. (1974), "Speculations on Bilingualism and the Cognitive Network", Working Papers on Bilingualism, Issue 2 (Toronto: Ontario Institute for Studies in Education, Bilingual Education Project).
      • Reprinted as Research Paper No. 74-RP-1013 (Defence and Civil Institute of Enviornmental Medicine, Defence Research Board)

   2. Werner, Oswald (1988), "How to Teach a Network: Minimal Design Features for a Cultural Knowledge Acquisition Device or C-KAD", in Martha Walton Evens (ed.), Relational Models of the Lexicon: Representing Knowledge in Semantic Networks (Cambridge, UK: Cambridge University Press): 141-166.

   3. Hartley, Roger T.; & Barnden, John A. (1997), "Semantic Networks: Visualizations of Knowledge", Trends in Cognitive Sciences 1(5) (August): 169-175.

   4. 
      Special Issue on AI and Networks, AI Magazine 29(3) (Fall 2008).