Conceptual graphs (CGs) are a system of logic based on the existential graphs of Charles Sanders Peirce and the semantic networks of artificial intelligence. They express meaning in a form that is logically precise, humanly readable, and computationally tractable. With their direct mapping to language, conceptual graphs serve as an intermediate language for translating computer-oriented formalisms to and from natural languages. With their graphic representation, they serve as a readable, but formal design and specification language. CGs have been implemented in a variety of projects for information retrieval, database design, expert systems, and natural language processing.
Introductions to Conceptual Graphs
- John F. Sowa, Information Processing in Mind and Machine, Reading, MA: Addison-Wesley, 1984.
- Simon Polovina and John Heaton, "An Introduction to Conceptual Graphs," AI Expert, pp. 36-43, 1992.
- John F. Sowa, "Conceptual Graphs Summary," in Conceptual Structures: Current Research and Practice, P. Eklund, T. Nagle, J. Nagle, and L. Gerholz (Eds.), Ellis Horwood, pp. 3-52, 1992.
- Simon Polovina, "An Introduction to Conceptual Graphs" in Conceptual Structures: Knowledge Architectures for Smart Applications, U. Priss, S. Polovina, R. Hill (Eds.), Lecture Notes in Artificial Intelligence (LNAI 4604), Springer, pp. 1-15, 2007.
- John F. Sowa, Knowledge Representation : Logical, Philosophical, and Computational Foundations, is not limited to conceptual graphs, but provides broad coverage of the entire field. It is available from ResearchGate and Amazon.com.
- Aalborg University's Department of Communication has developed an excellent Online Conceptual Graphs course.
Conceptual Graphs Standard Notation
Current Standard
There is a standard for the Conceptual Graphs Interchange Format (CGIF). This standard was developed in conjunction with the ISO Common Logic Project, which seeks to standardize a form of logic for knowledge interchange, and includes three syntaxes for Common Logic, one of which is CGIF in Annex B. Comments and suggestions on the entire standard are welcome; see the web site for more details.
Earlier Proposals
Here are some documents that may be of some historical interest. Note that CGIF has undergone significant changes from these documents; see the current standard (above).
- Examples using the standard HTML 4.0 symbol definitions
- Examples using the symbols font in MS Windows
A very old draft proposed (c. 1998) for conceptual graphs:
- CG dpANS using the standard HTML 4.0 symbol definitions
- CG dpANS using the symbols font in MS Windows
Conceptual Graph Bibliographies
John F. Sowa's bibliography page
ICCS Conferences dblp:Computer Science bibliography page
Research Groups and Projects
Aalborg University - Department of Communication Online Conceptual Graphs course
INSEA, Morocco Amine Group deals in knowledge base and expert systems, natural language processing, Case Based Reasoning and learning, Intelligent Tutoring Systems and Multi-Agent Systems
Sheffield Hallam University, UK CSRG (Conceptual Structures Research Group)
Universite Laval, Quebec City, Canada Cognitive Informatics Laboratory
University of Montpellier 2, CNRS and INRA RCR/GraphiK
Tools
- Amine - a multi-layer platform dedicated to the development of Intelligent Systems and Multi-agent Systems.
- CharGer - a prototype conceptual graph editor developed at the University of Alabama in Huntsville, free for noncommercial use, and runs under Java.
- CG Mars Lander - fast conceptual graph retrieval and question answering tool, available for joint development and industrial funding.
- CoGITaNT - several useful utilities: a set of library routines in C++ for conceptual modeling, some knowledge bases in conceptual graphs, and an XML specification for CGXML.
- CPE - a modular environment that provides modules to give functionality to a user without having to take the whole environment. Currently, there is a CGIF editor, ARCEdit and other CG Operations (Projection and Maximal Join) should be available in the future.
- GoGui - a free graph-based visual tool, developed in Java, for building Conceptual Graph knowledge bases represented in COGXML format, compatible with CoGITaNT (see above).
- Prolog+CG - an object-oriented extension of PROLOG, based on CG. CG (both simple and compound) is a basic data structure, like term. PROLOG+CG is implemented with Java.
- WebKB - tools for information retrieval and knowledge representation.
At ICCS'05 in Kassel, Germany, a discussion was held about how to further the progress of CG tools. Here is a summary of the discussion.
Conceptual Graphs Email List
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Simon Polovina is the Conceptual Graphs Mailing List Administrator: s.polovina [at] shu [dot] ac [dot] uk
Conceptual Structures Frequently Asked Questions
(originated from ICCS 2007 and Gerard Ellis)
Here we answer some of the frequently asked questions about conceptual structures.
- What are Conceptual Structures?
- Hasn't Artificial Intelligence already been around for a long time?
- CS is based on graph theory, so is it all just mathematics?
- How should I pronounce "Peirce"?
- What are useful books/papers to read about conceptual structures?
- What journals have conceptual structures papers appeared
in?
What are Conceptual Structures?
Conceptual Structures, CS, are a set of techniques for representing knowledge in a computer. They can be used to capture knowledge as humans understand it - as information about humans playing roles in events; as knowledge about a process or method; as a means of capturing the implicit consequences of an action or event; or as reasoning about objects in the real world. Conceptual Graphs, CG, (as an example of Conceptual Structures) are based on a field of mathematics called graph theory, so they can be proven to derive correct conclusions from given premises whilst being easily converted to software. Conceptual Graphs were introduced in John Sowa's book ``Conceptual Structures: Information Processing in Mind and Machine'', and have been applied to several domains including natural language processing, information systems modelling, program specification, information retrieval, machine learning and case based reasoning.
Hasn't Artificial Intelligence already been around for a long time?
Yes, but one of the major problems for AI has been connecting the understanding of the computer to what's happening in the real world. Also, capturing the sense of human knowledge inside a computer's data structures has been a difficult problem. CSs help to overcome these problems by capturing the true semantics of the data by expressing all information in terms of basic concepts. These concepts can be aggregated to form more complex concepts and knowledge. Then, CSs express the relationship among all these concepts to capture the essence of the knowledge. These relationships can include simple ideas like "above" or "sister-of" or very complex relationships like "causes to fail" or "depends on" or "this process must precede that process". CSs therefore add value to data.
CS is based on graph theory, so is it all just mathematics?
Yes and no. It is based on graph theory, so we can prove that the software derived from our CSs will work and produce the correct answer. Besides, all software is just a form of executable mathematics anyway. The point is that CSs are a field where mathematics and software join with human knowledge to produce a new kind of reasoning system. Using CSs, we can capture all of the ideas, events, objects and actions in a domain (like steel manufacturing or building a house) and then employ that knowledge in a way similar to what humans do.
How should I pronounce "Peirce"?
Quote from John Sowa's message of 15 March'95: Re pronunciation of "Peirce": C. S. Peirce is descended from a man named John Pers, who came to America from England. I don't know how the spelling changed, but the pronunciation hasn't. Therefore, Peirce is still pronounced Pers, which rhymes with the English word "purse".
What are useful books/papers to read about conceptual structures?
- John F. Sowa (1984) "Conceptual Structures: Information Processing in Mind and Machine", Addison-Wesley, Reading, MA.
- Heather D. Pfeiffer and Timothy E. Nagle (Eds.) (1993) "Conceptual Structures: Theory and Implementation", Springer-Verlag, Number 754, Lecture Notes in Artificial Intelligence, Proceedings of the Seventh Annual Workshop on Conceptual Graphs, Las Cruces, New Mexico, July 8-10, 1992.
- Guy W. Mineau and Bernard Moulin and John F. Sowa (Eds.) (1993) "Conceptual Graphs for Knowledge Representation", Lecture Notes in Artificial Intelligence, Springer-Verlag, Berlin, Number 699, Proceedings of the 1st International Conference on Conceptual Structures, Quebec City, Canada, August 4-7.
- William M. Tepfenhart and Judith P. Dick and John F. Sowa (Eds.) (1994) "Conceptual Structures: Current Practices", Second International Conference on Conceptual Structures, ICCS'94, College Park, Maryland, USA, August, Lecture Notes in Artifical Intelligence, Number 835, Springer-Verlag, Berlin.
- Gerard Ellis and Robert A. Levinson and William Rich and John F. Sowa (Eds.) (1995) "Conceptual Graphs: Structure-based Knowledge Representation", Proceedings of the Third International Conference on Conceptual Structures ICCS'95, August 14-18, University of California, Santa Cruz, USA, Lecture Notes in Artificial Intelligence, Springer-Verlag, Number 954, Berlin.
- Tim Nagle and Jan Nagle and Laurie Gerholz and Peter Eklund (Eds.) (1992) "Conceptual Structures: Current Research and Practice", Ellis Horwood.
- John F. Sowa (1991) "Toward the Expressive Power of Natural Language," J.F. Sowa (Ed.), Principles of Semantic Networks: Explorations in the Representation of Knowledge, Morgan Kaufmann, San Mateo, CA, p. 157-189.
- John F. Sowa (1993) "Relating Diagrams to Logic", Guy W. Mineau and Bernard Moulin and John F. Sowa (Eds.), Conceptual Graphs for Knowledge Representation, Lecture Notes in Artificial Intelligence, Springer-Verlag, Berlin, Number 699, Proceedings of the 1st International Conference on Conceptual Structures, Quebec City, Canada, August 4-7.
- John F. Sowa (1992) "Conceptual Graphs Summary", T. E. Nagle and J. A. Nagle and L. L. Gerholz and P. W. Eklund (Eds.), Conceptual Structures: Current Research and Practice, Ellis Horwood, p. 3-51.
- John F. Sowa (1993) "Logical Foundations for Representing Object-Oriented Systems", Journal of Experimental & Theoretical Artificial Intelligence, volume 5.
- Kenneth Laine Ketner (1990) "Elements of Logic: An Introduction to Peirce's Existential Graphs," Texas Tech University Press, Lubbock, Texas.
- Don D. Roberts (1973) "The Existential Graphs of Charles S. Peirce", Mouton, The Hague, 1973.
- Collected papers of Charles Sanders Peirce Charles (1931-58) Hartshorne and Paul Weiss (Eds.) Harvard University Press, Cambridge.
- A conceptual structures bibliography.
What journals have conceptual structures papers appeared in?
- special editions of journals
- _Journal of Theoretical and Experimental AI (JETAI)_, vol. 4, no. 2, 1992, edited by Eileen C. Way.
- _Knowledge-Based Systems_, vol. 5, no. 3, 1992, ed. by John F. Sowa.
- _Revue d'Intelligence Artificielle_
- Computers and Mathematics with Applications Journal also had a special edition on Semantic Networks edited by Fritz Lehmann which could possibly also be classed in this group.
- other journals where papers have appeared
- Data and Knowledge Engineering
- Artificial Intelligence
- IBM Journal of Research and Development
- Computers and Mathematics with Applications
- Journal of the Assoc. for Literary and Linguistic Computing
- Applied Artificial Intelligence
- International Journal of Man-Machine Studies
- International Journal of Expert Systems
- Information and Software Technology
- Methodologies for Intelligent Systems
- Computational Linguistics
- IEEE Expert
- IEICE Transactions on Information and Systems
- Methods of Information in Medicine
- special editions of journals