Abstract
The core issue of analogical reasoning is the transfer of relational knowledge from a source case to a target problem. Visual analogical reasoning pertains to problems containing only visual knowledge. Holyoak and Thagard proposed that the retrieval and mapping tasks of analogy in general can be productively viewed as constraint satisfaction problems, and provided connectionist implementations of their proposal. In this paper, we reexamine the retrieval and mapping tasks of analogy in the context of diagrammatic cases, representing the spatial structure of source and target diagrams as semantic networks in which the nodes represent spatial elements and the links represent spatial relations. We use a method of constraint satisfaction with backtracking for the retrieval and mapping tasks, with subgraph isomorphism over a particular domain language as the similarity measure. Results in the domain of 2D line drawings suggest that at least for this domain the above method is quite promising.
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Thagard P, Holyoak KJ, Nelson G, Gochfeld D (1990) Analog retrieval by constrain satisfaction. Artificial Intelligence 46:259–310
Holyoak KJ, Thagard P (1989) Analogical mapping by constraint satisfaction. Cogn Sci 13(3):295–355
Bayardo Jr., RJ, Schrag R (1997) Using CSP look-back techniques to solve real-world SAT instances. In: Proc. AAAI-97. AAAI Press, Providence, Rhode Island, pp 203–208
Davies J, Goel AK (2001) Visual analogy in problem solving. In: Proc. IJCAI-01. Morgan Kaufmann Publishers, Seattle, WA, pp 377–382
Davies J, Goel AK (2003) Representation issues in visual analogy. In: Proc. 25th Annual Conf. Cognitive Science Society. Lawrence Erlbaum Associates, Boston, MA
Kolodner J (1993) Case-based reasoning. Morgan Kaufmann Publishers, San Mateo, CA
Forbus KD, Gentner D, Law K (1995) MAC/FAC: A model of similarity-based retrieval. Cogn Sci 19(2):141–205
Gick ML, Holyoak KJ (1980) Analogical problem solving. Cognitive Psychology 12:306–355
Evans TG (1968) A heuristic program to solve geometric analogy problems. In: Minsky Marvin (eds) Semantic Information processing. MIT Press, Cambridge, MA
Ferguson RW (2000) Modeling orientation effects in symmetry detection: The role of visual structure. In: Gleitman L. R., Josh Ar. K. (eds) Proc. 22nd Annual Conf. Cognitive Science Society, Lawrence Erlbaum Associates, Philadelphia, PA
Ferguson RW, Forbus KD (1998) Telling juxtapositions: Using repetition and alignable difference in diagram understanding. In: Holyoak K, Gentner D, and Kokinov B (eds) Advances in analogy Research, New Bulgarian University, Sofia, Bulgaria, pp 109–117
Falkenhainer B, Forbus KD, Gentner D (1990) The structure-mapping engine: Algorithm and examples. Artificial Intelligence 41:1–63
Pearce M, Goel AK, Kolodner JL, Zimring C, Sentosa L, Billington R (1992) Case-based design support: A case study in architectural design. IEEE Expert: Intell Syst & their Applis 7(5):14–20
Barber J, Jacobson M, Penberthy L, Simpson R, Bhatta S, Goel A, Pearce M, Shankar M, Stroulia E (1992) Integrating artificial intelligence and multimedia technologies for interface design advising. NCR J Res Dev 6(1):75–85
Gross MD, E Yi-Luen Do (1995) Diagram query and image retrieval in design. In: Proc. 2nd Int’l Conf. on Image Processing, IEEE Computer Society Press, Crystal City, VA
Gebhardt F, Voss A, Gräther W, Schmidt-Belz B (1997) Reasoning with Complex Cases, Kluwer Series in Engineering and Computer Science. vol. 393 Kluwer Academic Publishers,Boston
Börner K, Eberhard P, Tammer E-C, Coulon C-H (1996) Structural similarity and adaptation. In: Smith I, Faltings B (eds) Advances in Cased-Based Reasoning: Proc. 3rd European Workshop on Cased-Based Reasoning, Lecture Notes in Artificial Intelligence, Lausanne, Switzerland, Springer-Verlag, vol 1168, pp 58–75
Hua K, Smith I, Faltings B (1993) Exploring case-based building design—CADRE. Art Intell for Engrs Design, Anal and Manuf (AI EDAM) 7(2):135–144
Maher ML, Zhang DM (1993) CADSYN: A case-based design process model. Art Intell Engrs Design, Anal Manuf (AI EDAM) 7(2):135–144
Sqalli MH, Purvis L, Freuder EC (1999) Survey of applications integrating constraint satisfaction and case-based reasoning. In: Layfield C, S B, Wren A (eds) Proc. Practical Applications of Constraint Technologies and Logic Programming (PACLP 1999), Practical Applications Company, London,UK
Levinson R, Ellis G (1992) Multi-level hierarchical retrieval. Knowl-Based Syst 5(3):233–244
Petrakis EGM, Faloutsos C, Lin K-I (2002) An architecture for a CBR image segmentation system. IEEE Trans Knowl Data Engrs 14(5):959–987
Tombre K (1996) Structural and semantic methods in line drawing analysis: To which extent do they work? In: Perner P, Wang P S-P, Rosenfeld A (eds) Advances in Structural and Syntactical Pattern Recognition, 6th Int’l Workshop, SSPR ’96, Lecture Notes in Computer Science, Springer-Verlag, Leipzig, Germany, vol 1121, pp 310–321
Perner P (1995) Case-based reasoning for image interpretation. In: Hlavac V, Sara R (eds) Computer Analysis of Images and Patterns, 6th Int’l Conf., CAIP ’95, Lecture Notes in Computer Science, Springer-Verlag, Prague, Czech Republic, vol 970, pp 532–537
Perner P (1999) An architecture for a cbr image segmentation system. In: Althoff K-D, Bergmann R, Branting LK (eds) Case-Based Reasoning Research and Development, 3rd Int’l Conf. on Case-Based Reasoning, ICCBR-99, Lecture Notes in Artificial Intelligence, Springer-Verlag, Seeon Monastery, Germany, vol 1650, pp 525–534
Grimnes M (1996) A two-layer case-based reasoning architecture for medical image understanding. In: Smith I, Faltings B (eds) Advances in Case-Based Reasoning, 3rd European Workshop, EWCBR-96, Lecture Notes in Artificial Intelligence, Springer-Verlag,Lausanne, Switzerland, vol 1168, pp 164–178
Grimson WEL, Huttenlocher DP (1991) On the verification of hypothesized matches in model-based recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 13(12):1201–1213
Gupta A, Jain R (1997) Visual information retrieval. Comm ACM 40(5):69–79
Rui Y, Huang TS, Chang S-F (1999) Image retrieval: Current techniques, promising directions and open issues. J Visual Comm Image Repr 10(4):39–62
Santini S, Jain R (1999) Similarity measures. PAMI 21(9):871–883
Veltkamp RC, Tanase M (2000) Content-based image retrieval systems: A survey. Technical Report UU-CS-2000-34, Institute of Information and Computing Sciences, Utrecht University, Utrecht, The Netherlands
Egenhofer MJ (1996) Spatial-Query-by-Sketch. In: Burnett W,Citrin W (eds) IEEE Symposium on Visual Lnguages, IEEE Press, Boulder, CO, pp 60–67
Randell DA, Cui Z, Cohn AG (1992) A spatial logic based on regions and connections. In: Nebel B, Rich C, Swartout WR (eds) Proc. 3rd Int’l Conf. on Knowledge Representation and Reasoning, Morgan Kaufmann Publishers, Cambridge, MA, pp 165–176
Prosser P (1993) Hybrid algorithms for the constraint satisfaction problem. Comp Intell 9(3):268–299
Ounis I, Pacsca M (1998) RELIEF: Combining expressiveness and rapidity into a single system. In: Proc. 21st Annual ACM SIGIR Conference, Melbourne, Australia, ACM Press, pp 266–274
Ferguson RW, Forbus KD (2000) GeoRep: A flexible tool for spatial representation of line drawings. In: Proc. AAAI-2000, Austin, Texas, AAAI Press
Papadias D, Kalnis P, Mamoulis N (1999) Hierarchical constraint satisfaction in spatial databases. In: Procedubgs. AAAI-99, Orlando, FL, AAAI Press
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Yaner, P.W., Goel, A.K. Visual analogy: Viewing analogical retrieval and mapping as constraint satisfaction problems. Appl Intell 25, 91–105 (2006). https://doi.org/10.1007/s10489-006-8868-x
Issue Date:
DOI: https://doi.org/10.1007/s10489-006-8868-x