skip to main content
survey
Open Access

Conceptual Representations for Computational Concept Creation

Authors Info & Claims
Published:25 February 2019Publication History
Skip Abstract Section

Abstract

Computational creativity seeks to understand computational mechanisms that can be characterized as creative. The creation of new concepts is a central challenge for any creative system. In this article, we outline different approaches to computational concept creation and then review conceptual representations relevant to concept creation, and therefore to computational creativity. The conceptual representations are organized in accordance with two important perspectives on the distinctions between them. One distinction is between symbolic, spatial and connectionist representations. The other is between descriptive and procedural representations. Additionally, conceptual representations used in particular creative domains, such as language, music, image and emotion, are reviewed separately. For every representation reviewed, we cover the inference it affords, the computational means of building it, and its application in concept creation.

Skip Supplemental Material Section

Supplemental Material

References

  1. Agnar Aamodt and Enric Plaza. 1994. Case-based reasoning: Foundational issues, methodological variations, and system approaches. AI Communications 7, 1 (1994), 39--59. Google ScholarGoogle ScholarCross RefCross Ref
  2. Moshe Abeles. 2011. Cell assemblies. Scholarpedia 6, 7 (2011), 1505.Google ScholarGoogle ScholarCross RefCross Ref
  3. Lada A. Adamic and Eytan Adar. 2003. Friends and neighbors on the web. Social Networks 25, 3 (2003), 211--230.Google ScholarGoogle ScholarCross RefCross Ref
  4. Eugene Agichtein and Luis Gravano. 2000. Snowball: Extracting relations from large plain-text collections. In Proceedings of the 5th ACM Conference on Digital Libraries (DL’00). 85--94. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Janet Aisbett and Greg Gibbon. 2001. A general formulation of conceptual spaces as a meso level representation. Artificial Intelligence 133, 1--2 (2001), 189--232. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Ahmed F. AlEroud and George Karabatis. 2013. A system for cyber attack detection using contextual semantics. In Proceedings of the 7th International Conference on Knowledge Management in Organizations: Service and Cloud Computing. 431--442.Google ScholarGoogle Scholar
  7. Shumeet Baluja, Dean Pomerleau, and Todd Jochem. 1994. Towards automated artificial evolution for computer-generated images. Connection Science 6 (1994), 325--354.Google ScholarGoogle ScholarCross RefCross Ref
  8. Albert-Laszlo Barabâsi, Hawoong Jeong, Zoltan Néda, Erzsebet Ravasz, Andras Schubert, and Tamas Vicsek. 2002. Evolution of the social network of scientific collaborations. Physica A: Statistical Mechanics and Its Applications 311, 3 (2002), 590--614.Google ScholarGoogle ScholarCross RefCross Ref
  9. Marco Baroni, Georgiana Dinu, and Germán Kruszewski. 2014. Don’t count, predict! A systematic comparison of context-counting vs. context-predicting semantic vectors. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics. 238--247.Google ScholarGoogle Scholar
  10. Atilim Günes Baydin, Ramon López de Mántaras, and Santiago Ontañón. 2012. Automated generation of cross-domain analogies via evolutionary computation. In Proceedings of the 3rd International Conference on Computational Creativity (ICCC’12). 25--32.Google ScholarGoogle Scholar
  11. Yoshua Bengio, Aaron C. Courville, and Pascal Vincent. 2013. Representation learning: A review and new perspectives. IEEE Transactions on Pattern Analysis and Machine Intelligence 35, 8 (2013), 1798--1828. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Matthew Berland and Eugene Charniak. 1999. Finding parts in very large corpora. In Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics (ACL’99). 57--64. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Michael R. Berthold. 2012. Towards bisociative knowledge discovery. In Bisociative Knowledge Discovery: An Introduction to Concept, Algorithms, Tools, and Applications, M. R. Berthold (Ed.). Springer, Berlin, Germany, 1--10. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Tarek R. Besold and Enric Plaza. 2015. Generalize and blend: Concept blending based on generalization, analogy, and amalgams. In Proceedings of the 6th International Conference on Computational Creativity (ICCC’15).Google ScholarGoogle Scholar
  15. Shashank Bhatia and Stephan Chalup. 2013. A model of heteroassociative memory: Deciphering surprising features and locations. In Proceedings of the 4th International Conference on Computational Creativity (ICCC’13). 139--146.Google ScholarGoogle Scholar
  16. Greg Bickerman, Sam Bosley, Peter Swire, and Robert M. Keller. 2010. Learning to create jazz melodies using deep belief nets. In Proceedings of the 1st International Conference on Computational Creativity (ICCC’10). 228--237.Google ScholarGoogle Scholar
  17. Chris Biemann. 2005. Ontology learning from text: A survey of methods. LDV Forum 20, 2 (2005), 75--93.Google ScholarGoogle Scholar
  18. Eduardo Blanco, Nuria Castell, and Dan Moldovan. 2008. Causal relation extraction. In Proceedings of the 6th International Language Resources and Evaluation (LREC’08). 310--313.Google ScholarGoogle Scholar
  19. David Blei. 2012. Probabilistic topic models. Communications of the ACM 55, 4 (2012), 77--84. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. David Blei, Thomas Griffiths, Michael Jordan, and Joshua Tenenbaum. 2004. Hierarchical topic models and the nested Chinese restaurant process. Advances in Neural Information Processing Systems 16 (2004), 17--24. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. David Blei and Pedro Moreno. 2001. Topic segmentation with an aspect hidden Markov model. In Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval. 343--348. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. David Blei, Andrew Y. Ng, and Michael I. Jordan. 2003. Latent Dirichlet allocation. Machine Learning Research 3 (2003), 993--1022. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Margaret A. Boden. 1990. The Creative Mind: Myths and Mechanisms. Basic Books, New York, NY. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Georgeta Bordea, Paul Buitelaar, Stefano Faralli, and Roberto Navigli. 2015. Semeval-2015 task 17: Taxonomy extraction evaluation. In Proceedings of the 9th International Workshop on Semantic Evaluation (TExEval’15).Google ScholarGoogle ScholarCross RefCross Ref
  25. Maroua Bouzid, Carlo Combi, Michael Fisher, and Gérard Ligozat. 2006. Guest editorial: Temporal representation and reasoning. Annals of Mathematics and Artificial Intelligence 46, 3 (2006), 231--234. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Oliver Bown and Sebastian Lexer. 2006. Continuous-time recurrent neural networks for generative and interactive musical performance. In Applications of Evolutionary Computing. Springer, 652--663. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Ronald J. Brachman and Hector J. Levesque (Eds.). 1985. Readings in Knowledge Representation. Morgan Kaufmann,San Francisco, CA. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Sergey Brin. 1999. Extracting patterns and relations from the World Wide Web. In Selected Papers From the International Workshop on the World Wide Web and Databases (WebDB’98). 172--183. http://dl.acm.org/citation.cfm?id=646543.696220 Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Peter Bruza and Marc Weeber. 2008. Literature-Based Discovery. Germany. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Jonathan Byrne, Erik Hemberg, Anthony Brabazon, and Michael O’Neill. 2012. A local search interface for interactive evolutionary architectural design. In Evolutionary and Biologically Inspired Music, Sound, Art and Design, P. Machado, J. Romero, and A. Carballal (Eds.). Lecture Notes in Computer Science, Vol. 7247. Springer, 23--34. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Andrea Capocci, Vito D. P. Servedio, Guido Caldarelli, and Francesca Colaiori. 2005. Detecting communities in large networks. Physica A: Statistical Mechanics and Its Applications 352, 2 (2005), 669--676.Google ScholarGoogle ScholarCross RefCross Ref
  32. Sharon A. Caraballo. 1999. Automatic construction of a hypernym-labeled noun hierarchy from text. In Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics (ACL’99). 120--126. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Antonio Chella. 2015. A cognitive architecture for music perception exploiting conceptual spaces. In Applications of Conceptual Spaces: The Case for Geometric Knowledge Representation. Springer, 187--203.Google ScholarGoogle Scholar
  34. Antonio Chella, Silvia Coradeschi, Marcello Frixione, and Alessandro Saffiotti. 2004. Perceptual anchoring via conceptual spaces. In Proceedings of the AAAI-04 Workshop on Anchoring Symbols to Sensor Data.Google ScholarGoogle Scholar
  35. Antonio Chella, Haris Dindo, and Ignazio Infantino. 2007. Imitation learning and anchoring through conceptual spaces. Applied Artificial Intelligence 21, 4 (2007), 343--359. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. Antonio Chella, Marcello Frixione, and Salvatore Gaglio. 2008. A cognitive architecture for robot self-consciousness. Artificial Intelligence in Medicine 44, 2 (2008), 147--154. Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. Massimiliano Ciaramita, Aldo Gangemi, Esther Ratsch, Jasmin Šaric, and Isabel Rojas. 2005. Unsupervised learning of semantic relations between concepts of a molecular biology ontology. In Proceedings of the 19th International Joint Conference on Artificial Intelligence (IJCAI’05). 659--664. Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. Philipp Cimiano, Andreas Hotho, and Steffen Staab. 2005. Learning concept hierarchies from text corpora using formal concept analysis. Artificial Intelligence Research 24, 1 (2005), 305--339. Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. Bob Coecke, Mehrnoosh Sadrzadeh, and Stephen Clark. 2011. Mathematical foundations for a compositional distributional model of meaning. Linguistic Analysis 36, 1--4 (2011), 345--384.Google ScholarGoogle Scholar
  40. Simon Colton and Geraint A. Wiggins. 2012. Computational creativity: The final frontier? In Proceedings of the 20th Biennial European Conference on Artificial Intelligence (ECAI’12). 21--26. Google ScholarGoogle ScholarDigital LibraryDigital Library
  41. Shauna Concannon and Matthew Purver. 2014. Inferring cultural preference of arts audiences through Twitter data. In Proceedings of the Conference on Digital Intelligence.Google ScholarGoogle Scholar
  42. Roberto Confalonieri, Joe Corneli, Alison Pease, Enric Plaza, and Marco Schorlemmer. 2015. Using argumentation to evaluate concept blends in combinatorial creativity. In Proceedings of the 6th International Conference on Computational Creativity (ICCC’15).Google ScholarGoogle Scholar
  43. Holk Cruse. 1996. Neural Networks as Cybernetic Systems. Thieme, Stuttgart, Germany. Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. Amitava Das and Björn Gambäck. 2014. Poetic machine: Computational creativity for automatic poetry generation in bengali. In Proceedings of the 5th International Conference on Computational Creativity (ICCC’14).Google ScholarGoogle Scholar
  45. Dmitry Davidov and Ari Rappoport. 2006. Efficient unsupervised discovery of word categories using symmetric patterns and high frequency words. In Proceedings of the 21st International Conference on Computational Linguistics and the 44th Annual Meeting of the Association for Computational Linguistics (ACL-44). 297--304. Google ScholarGoogle ScholarDigital LibraryDigital Library
  46. Darcy Davis, Ryan Lichtenwalter, and Nitesh V. Chawla. 2011. Multi-relational link prediction in heterogeneous information networks. In Proceedings of the 2011 International Conference on Advances in Social Networks Analysis and Mining (ASONAM’11). 281--288. Google ScholarGoogle ScholarDigital LibraryDigital Library
  47. Randall Davis, Howard E. Shrobe, and Peter Szolovits. 1993. What is a knowledge representation? AI Magazine 14, 1 (1993), 17--33.Google ScholarGoogle Scholar
  48. Celso M. de Melo and Jonathan Gratch. 2010. Evolving expression of emotions through color in virtual humans using genetic algorithms. In Proceedings of the 1st International Conference on Computational Creativity (ICCC’10). 248--257.Google ScholarGoogle Scholar
  49. Luciano Del Corro and Rainer Gemulla. 2013. ClausIE: Clause-based open information extraction. In Proceedings of the 22nd International Conference on World Wide Web (WWW’13). 355--366. Google ScholarGoogle ScholarDigital LibraryDigital Library
  50. Luca Donetti and Miguel A. Munoz. 2004. Detecting network communities: A new systematic and efficient algorithm. Journal of Statistical Mechanics: Theory and Experiment 2004, 10 (2004), P10012.Google ScholarGoogle ScholarCross RefCross Ref
  51. David Dubin. 2004. The most influential paper Gerard Salton never wrote. Library Trends 52, 4 (2004), 748--764.Google ScholarGoogle Scholar
  52. Werner Dubitzky, Tobias Kötter, Oliver Schmidt, and Michael R. Berthold. 2012. Towards creative information exploration based on Koestler’s concept of bisociation. In Bisociative Knowledge Discovery: An Introduction to Concept, Algorithms, Tools, and Applications, M. R. Berthold (Ed.). Springer, 11--32. Google ScholarGoogle ScholarDigital LibraryDigital Library
  53. Douglas Eck and Juergen Schmidhuber. 2002. Learning the long-term structure of the blues. In Proceedings of the 16th International Conference on Artificial Neural Networks (ICANN’02). 284--289. Google ScholarGoogle ScholarDigital LibraryDigital Library
  54. Oren Etzioni, Anthony Fader, Janara Christensen, Stephen Soderland, and Mausam Mausam. 2011. Open information extraction: The second generation. In Proceedings of the 22nd International Joint Conference on Artificial Intelligence—Volume One (IJCAI’11). 3--10. Google ScholarGoogle ScholarDigital LibraryDigital Library
  55. Anthony Fader, Stephen Soderland, and Oren Etzioni. 2011. Identifying relations for open information extraction. In Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing (EMNLP’11). 1535--1545. Google ScholarGoogle ScholarDigital LibraryDigital Library
  56. Gilles Fauconnier and Mark Turner. 1998. Conceptual integration networks. Cognitive Science 22, 2 (1998), 133--187.Google ScholarGoogle ScholarCross RefCross Ref
  57. Christiane Fellbaum (Ed.). 1998. WordNet: An Electronic Lexical Database (Language, Speech, and Communication). MIT Press, Cambridge, MA.Google ScholarGoogle Scholar
  58. Jerry A. Fodor. 1975. The Language of Thought. Harvard University Press, Cambridge, MA.Google ScholarGoogle Scholar
  59. Blaž Fortuna, Dunja Mladenić, and Marko Grobelnik. 2006. Semi-automatic construction of topic ontologies. In Semantics, Web and Mining, M. Ackermann, B. Berendt, M. Grobelnik, A. Hotho, D. Mladenič, G. Semeraro, et al. (Eds.). Lecture Notes in Computer Science, Vol. 4289. Springer, 121--131. Google ScholarGoogle ScholarDigital LibraryDigital Library
  60. Aldo Gangemi, Nicola Guarino, Claudio Masolo, Alessandro Oltramari, and Luc Schneider. 2002. Sweetening ontologies with DOLCE. In Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web (EKAW’02). 166--181. Google ScholarGoogle ScholarDigital LibraryDigital Library
  61. Peter Gärdenfors. 2000. Conceptual Spaces: The Geometry of Thought. MIT Press, Cambridge, MA.Google ScholarGoogle ScholarCross RefCross Ref
  62. Leon A. Gatys, Alexander S. Ecker, and Matthias Bethge. 2015. A neural algorithm of artistic style. arXiv:1508.06576.Google ScholarGoogle Scholar
  63. Roxana Girju, Adriana Badulescu, and Dan Moldovan. 2006. Automatic discovery of part-whole relations. Computational Linguistics 32, 1 (March 2006), 83--135. Google ScholarGoogle ScholarDigital LibraryDigital Library
  64. Roxana Girju and Dan I. Moldovan. 2002. Text mining for causal relations. In Proceedings of the 15th International Florida Artificial Intelligence Research Society Conference. 360--364. Google ScholarGoogle ScholarDigital LibraryDigital Library
  65. Roxana Girju, Preslav Nakov, Vivi Nastase, Stan Szpakowicz, Peter Turney, and Deniz Yuret. 2007. SemEval-2007 task 04: Classification of semantic relations between nominals. In Proceedings of the 4th International Workshop on Semantic Evaluations (SemEval’07). 13--18. Google ScholarGoogle ScholarDigital LibraryDigital Library
  66. Robert L. Goldstone and Andrew T. Hendrickson. 2010. Categorical perception. Wiley Interdisciplinary Reviews: Cognitive Science 1, 1 (2010), 69--78.Google ScholarGoogle ScholarCross RefCross Ref
  67. Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, et al. 2014. Generative adversarial nets. In Advances in Neural Information Processing Systems 27 (2014), 2672--2680. Google ScholarGoogle ScholarDigital LibraryDigital Library
  68. Gérard Govaert and Mohamed Nadif. 2014. Co-Clustering: Models, Algorithms and Applications. Wiley, London, UK. Google ScholarGoogle ScholarDigital LibraryDigital Library
  69. Gary Greenfield. 2012. A platform for evolving controllers for simulated drawing robots. In Evolutionary and Biologically Inspired Music, Sound, Art and Design, P. Machado, J. Romero, and A. Carballal (Eds.). Lecture Notes in Computer Science, Vol. 7247. Springer, 108--116. Google ScholarGoogle ScholarDigital LibraryDigital Library
  70. Karol Gregor, Ivo Danihelka, Alex Graves, Danilo Jimenez Rezende, and Daan Wierstra. 2015. DRAW: A recurrent neural network for image generation. arXiv:1502.04623.Google ScholarGoogle ScholarDigital LibraryDigital Library
  71. Thomas L. Griffiths, Mark Steyvers, David Blei, and Joshua B. Tenenbaum. 2005. Integrating topics and syntax. In Advances in Neural Information Processing Systems 17 (2005), 537--544. Google ScholarGoogle ScholarDigital LibraryDigital Library
  72. Tom Gruber. 2009. Ontology. In Encyclopedia of Database Systems, T. Özsu and L. Liu (Eds.). Springer, Boston, MA, 1963–1965.Google ScholarGoogle Scholar
  73. Miha Grčar, Nejc Trdin, and Nada Lavrač. 2013. A methodology for mining document-enriched heterogeneous information networks. Computer 56, 3 (2013), 321--335. Google ScholarGoogle ScholarDigital LibraryDigital Library
  74. Nicola Guarino and Pierdaniele Giaretta. 1995. Ontologies and knowledge bases: Towards a terminological clarification. In Towards Very Large Knowledge Bases: Knowledge Building and Knowledge Sharing. IOS Press, Amsterdam, Netherlands, 25--32.Google ScholarGoogle Scholar
  75. Kevin Gurney. 1997. An Introduction to Neural Networks. CRC Press, Boca Raton, FL. Google ScholarGoogle ScholarDigital LibraryDigital Library
  76. Stevan Harnad. 1990. The symbol grounding problem. Physica D: Nonlinear Phenomena 42, 1 (1990), 335--346. Google ScholarGoogle ScholarDigital LibraryDigital Library
  77. Kenneth D. Harris. 2005. Neural signatures of cell assembly organization. Nature Reviews Neuroscience 6 (2005), 399--407.Google ScholarGoogle ScholarCross RefCross Ref
  78. David A. Hart. 2007. Toward greater artistic control for interactive evolution of images and animation. In Proceedings of the 2007 EvoWorkshops on EvoCoMnet, EvoFIN, EvoIASP, EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTransLog. 527--536. Google ScholarGoogle ScholarDigital LibraryDigital Library
  79. John Haugeland. 1985. Artificial Intelligence: The Very Idea. MIT Press, Cambridge, MA. Google ScholarGoogle ScholarDigital LibraryDigital Library
  80. Simon S. Haykin. 1994. Neural Networks: A Comprehensive Foundation. Prentice Hall. Google ScholarGoogle ScholarDigital LibraryDigital Library
  81. Marti A. Hearst. 1992. Automatic acquisition of hyponyms from large text corpora. In Proceedings of the 14th Conference on Computational Linguistics (COLING’92). 539--545. Google ScholarGoogle ScholarDigital LibraryDigital Library
  82. Derrall Heath, Aaron Dennis, and Dan Ventura. 2015. Imagining imagination: A computational framework using associative memory models and vector space models. In Proceedings of the 6th International Conference on Computational Creativity (ICCC’15).Google ScholarGoogle Scholar
  83. Donald O. Hebb. 1949. The Organization of Behavior: A Neuropsychological Theory. Wiley, New York, NY.Google ScholarGoogle Scholar
  84. Iris Hendrickx, Su Nam Kim, Zornitsa Kozareva, Preslav Nakov, Diarmuid Ó. Séaghdha, Sebastian Padó, et al. 2010. SemEval-2010 task 8: Multi-way classification of semantic relations between pairs of nominals. In Proceedings of the 5th International Workshop on Semantic Evaluation (SemEval’10). 33--38. Google ScholarGoogle ScholarDigital LibraryDigital Library
  85. Geoffrey E. Hinton. 2009. Deep belief networks. Revision #91189. Scholarpedia 4, 5 (2009), 5947.Google ScholarGoogle ScholarCross RefCross Ref
  86. Geoffrey E. Hinton, James L. McClelland, and David E. Rumelhart. 1986. Distributed representations. In Parallel Distributed Processing: Explorations in the Microstructure of Cognition. Vol. 1. MIT Press, Cambridge, MA, 77--109. Google ScholarGoogle ScholarDigital LibraryDigital Library
  87. Geoffrey E. Hinton, Simon Osindero, and Yee-Whye Teh. 2006. A fast learning algorithm for deep belief nets. Neural Computation 18, 7 (2006), 1527--1554. Google ScholarGoogle ScholarDigital LibraryDigital Library
  88. Geoffrey E. Hinton and Ruslan R. Salakhutdinov. 2006. Reducing the dimensionality of data with neural networks. Science 313, 5786 (2006), 504--507.Google ScholarGoogle Scholar
  89. Thomas Hofmann. 1999. Probabilistic latent semantic indexing. In Proceedings of the 22nd Annual International SIGIR Conference on Research and Development in Information Retrieval (SIGIR’99). 50--57. Google ScholarGoogle ScholarDigital LibraryDigital Library
  90. Liangjie Hong and Brian D. Davison. 2010. Empirical study of topic modeling in Twitter. In Proceedings of the SIGKDD Workshop on Social Media Analytics. 80--88. Google ScholarGoogle ScholarDigital LibraryDigital Library
  91. Amy K. Hoover, Paul A. Szerlip, Marie E. Norton, Trevor A. Brindle, Zachary Merritt, and Kenneth O. Stanley. 2012. Generating a complete multipart musical composition from a single monophonic melody with functional scaffolding. In Proceedings of the 3rd International Conference on Computational Creativity. 111--118.Google ScholarGoogle Scholar
  92. Dominik Hornel and Tomas Ragg. 1996. Learning musical structure and style by recognition, prediction and evolution. In Proceedings of the 1996 International Computer Music Conference (ICMC’96). 59--62.Google ScholarGoogle Scholar
  93. Andrew Horner and David Goldberg. 1991. Genetic algorithms and computer-assisted music composition. In Proceedings of the 4th International Conference on Genetic Algorithms (ICGA’91). 427--441.Google ScholarGoogle Scholar
  94. Ping Hou, Broes de Cat, and Marc Denecker. 2010. Fo(Fd): Extending classical logic with rule-based fixpoint definitions. Theory and Practice of Logic Programming 10, 4--6 (2010), 581--596. Google ScholarGoogle ScholarDigital LibraryDigital Library
  95. Taehyun Hwang and Rui Kuang. 2010. A heterogeneous label propagation algorithm for disease gene discovery. In Proceedings of the 2010 SIAM International Conference on Data Mining (SDM’10). 583--594.Google ScholarGoogle ScholarCross RefCross Ref
  96. Ashwin Ittoo and Gosse Bouma. 2011. Extracting explicit and implicit causal relations from sparse, domain-specific texts. In Proceedings of the 16th International Conference on Natural Language Processing and Information Systems (NLDB’11). 52--63. Google ScholarGoogle ScholarDigital LibraryDigital Library
  97. Ashwin Ittoo, Gosse Bouma, Laura Maruster, and Hans Wortmann. 2010. Extracting meronomy relations from domain-specific, textual corporate databases. In Proceedings of the 15th International Conference on Applications of Natural Language to Information Systems (NLDB’10). 48--59. Google ScholarGoogle ScholarDigital LibraryDigital Library
  98. Gerhard Jäger. 2010. Natural color categories are convex sets. In Proceedings of Logic, Language and Meaning: 17th Amsterdam Colloquium. 11--20. Google ScholarGoogle ScholarDigital LibraryDigital Library
  99. Anil K. Jain, M. Narasimha Murty, and Patrick J. Flynn. 1999. Data clustering: A review. ACM Computing Surveys 31, 3 (1999), 264--323. Google ScholarGoogle ScholarDigital LibraryDigital Library
  100. Grega Jakus, Veljko Milutinovic, Sanida Omerović, and Săso Tomăzĭc. 2013. Concepts, Ontologies, and Knowledge Representation. Springer-Verlag New York, NY. Google ScholarGoogle ScholarDigital LibraryDigital Library
  101. Glen Jeh and Jennifer Widom. 2002. SimRank: A measure of structural-context similarity. In Proceedings of the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’02). 538--543. Google ScholarGoogle ScholarDigital LibraryDigital Library
  102. Kyle E. Jennings. 2010. Developing creativity: Artificial barriers in artificial intelligence. Minds and Machines 20, 4 (Nov. 2010), 489--501. Google ScholarGoogle ScholarDigital LibraryDigital Library
  103. Ming Ji, Yizhou Sun, Marina Danilevsky, Jiawei Han, and Jing Gao. 2010. Graph regularized transductive classification on heterogeneous information networks. In Proceedings of the 2010 European Conference on Machine Learning and Knowledge Discovery in Databases: Part I (ECML PKDD’10). 570--586. Google ScholarGoogle ScholarDigital LibraryDigital Library
  104. Bradley E. Johanson and Riccardo Poli. 1998. GP-Music: An interactive genetic programming system for music generation with automated fitness raters. In Proceedings of the 3rd Annual Conference on Genetic Programming (GP’98). 181--186.Google ScholarGoogle Scholar
  105. Matjaž Juršič, Borut Sluban, Bojan Cestnik, Miha Grčar, and Nada Lavrač. 2012. Bridging concept identification for constructing information networks from text documents. In Bisociative Knowledge Discovery: An Introduction to Concept, Algorithms, Tools, and Applications, M. R. Berthold (Ed.). Springer, 66--90. Google ScholarGoogle ScholarDigital LibraryDigital Library
  106. Nal Kalchbrenner and Phil Blunsom. 2013. Recurrent convolutional neural networks for discourse compositionality. In Proceedings of the Workshop on Continuous Vector Space Models and their Compositionality. 119--126.Google ScholarGoogle Scholar
  107. Nal Kalchbrenner, Edward Grefenstette, and Phil Blunsom. 2014. A convolutional neural network for modelling sentences. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 655--665.Google ScholarGoogle ScholarCross RefCross Ref
  108. George Karabatis, Zhiyuan Chen, Vandana P. Janeja, Tania Lobo, Monish Advani, Mikael Lindvall, et al. 2009. Using semantic networks and context in search for relevant software engineering artifacts. In Journal on Data Semantics XIV, S. Spaccapietra and L. Delcambre (Eds.). Lecture Notes in Computer Science, Vol. 5880. Springer, 74--104. Google ScholarGoogle ScholarDigital LibraryDigital Library
  109. Christopher S. G. Khoo, Syin Chan, and Yun Niu. 2000. Extracting causal knowledge from a medical database using graphical patterns. In Proceedings of the 38th Annual Meeting on Association for Computational Linguistics (ACL’00). 336--343. Google ScholarGoogle ScholarDigital LibraryDigital Library
  110. Douwe Kiela and Stephen Clark. 2014. A systematic study of semantic vector space model parameters. In Proceedings of the 2nd Workshop on Continuous Vector Space Models and their Compositionality (CVSC’14).Google ScholarGoogle ScholarCross RefCross Ref
  111. Arthur Koestler. 1964. The Act of Creation. MacMillan, New York, NY.Google ScholarGoogle Scholar
  112. Risi I. Kondor and John D. Lafferty. 2002. Diffusion kernels on graphs and other discrete input spaces. In Proceedings of the 19th International Conference on Machine Learning (ICML’02). 315--322. Google ScholarGoogle ScholarDigital LibraryDigital Library
  113. Sotiris B. Kotsiantis. 2007. Supervised machine learning: A review of classification techniques. In Proceedings of the 2007 Conference on Emerging Artificial Intelligence Applications in Computer Engineering. 3--24. Google ScholarGoogle ScholarDigital LibraryDigital Library
  114. Zornitsa Kozareva and Eduard Hovy. 2010. A semi-supervised method to learn and construct taxonomies using the Web. In Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing (EMNLP’10). 1110--1118. Google ScholarGoogle ScholarDigital LibraryDigital Library
  115. Zornitsa Kozareva, Ellen Riloff, and Eduard Hovy. 2008. Semantic class learning from the web with hyponym pattern linkage graphs. In Proceedings of the 2008 Annual Meeting of the Association for Computational Linguistics: Human Languages Technologies (ACL-08: HLT). 1048--1056.Google ScholarGoogle Scholar
  116. Ben Kröse and Patrick van der Smagt. 1993. An Introduction to Neural Networks (5th ed.). University of Amsterdam.Google ScholarGoogle Scholar
  117. Oliver Kutz, Till Mossakowski, Joana Hois, Mehul Bhatt, and John Bateman. 2012. Ontological blending in DOL. In Proceedings of the 1st International ECAI Workshop on Computational Creativity, Concept Invention, and General Intelligence (C3GI’12).Google ScholarGoogle Scholar
  118. Thomas K. Landauer, Peter W. Foltz, and Darrell Laham. 1998. An introduction to latent semantic analysis. Discourse Processes, Special Issue on Quantitative Approaches to Semantic Knowledge Representations 25, 2--3 (1998), 259--284.Google ScholarGoogle Scholar
  119. Yann LeCun, Yoshua Bengio, and Geoffrey E. Hinton. 2015. Deep learning. Nature 521, 7553 (2015), 436--444.Google ScholarGoogle Scholar
  120. Douglas Lenat. 1995. CYC: A large-scale investment in knowledge infrastructure. Communications of the ACM 38 (1995), 33--38. Google ScholarGoogle ScholarDigital LibraryDigital Library
  121. Robert P. Levy. 2001. A computational model of poetic creativity with neural network as measure of adaptive fitness. In Proceedings of the 4th International Conference on Case-Based Reasoning (ICCBR’01).Google ScholarGoogle Scholar
  122. Shu-Hsien Liao. 2003. Knowledge management technologies and applications--literature review from 1995 to 2002. Expert Systems With Applications 25, 2 (2003), 155--164.Google ScholarGoogle ScholarCross RefCross Ref
  123. Antonios Liapis, Héctor P. Martínez, and Georgios N. Julian Togelius. 2013. Transforming exploratory creativity with DeLeNoX. In Proceedings of the 4th International Conference on Computational Creativity (ICCC’13). 56--63.Google ScholarGoogle Scholar
  124. Dekang Lin and Patrick Pantel. 2001. DIRT @SBT@Discovery of inference rules from text. In Proceedings of the 7th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’01). 323--328. Google ScholarGoogle ScholarDigital LibraryDigital Library
  125. Hugo Liu and Push Singh. 2004. ConceptNet—A practical commonsense reasoning tool-kit. BT Technology 22, 4 (2004), 211--226. Google ScholarGoogle ScholarDigital LibraryDigital Library
  126. Maria Teresa Llano, Simon Colton, Rose Hepworth, and Jeremy Gow. 2016. Automated fictional ideation via knowledge base manipulation. Cognitive Computation 8, 2 (2016), 153--174.Google ScholarGoogle ScholarCross RefCross Ref
  127. Ziyu Lu, Nikos Mamoulis, Evaggelia Pitoura, and Panayiotis Tsaparas. 2016. Sentiment-based topic suggestion for micro-reviews. In Proceedings of the 10th International AAAI Conference on Web and Social Media (ICWSM’16). 231--240.Google ScholarGoogle Scholar
  128. Penousal Machado and Amílcar Cardoso. 2002. All the truth about NEvAr. Applied Intelligence: Special Issue on Creative Systems 16, 2 (2002), 101--119. Google ScholarGoogle ScholarDigital LibraryDigital Library
  129. Penousal Machado, Henrique Nunes, and Juan Romero. 2010. Graph-based evolution of visual languages. In Applications of Evolutionary Computation, C. Di Chio, A. Brabazon, G. A. Di Caro, M. Ebner, M. Farooq, A. Fink, et al. (Eds.). Lecture Notes in Computer Science, Vol. 6025. Springer Berlin Heidelberg, 271--280. Google ScholarGoogle ScholarDigital LibraryDigital Library
  130. Penousal Machado, Juan Romero, and Bill Manaris. 2008. Experiments in computational aesthetics. In The Art of Artificial Evolution, J. Romero and P. Machado (Eds.). Springer, Berlin, Germany, 381--415.Google ScholarGoogle Scholar
  131. Penousal Machado, Juan Romero, Antonino Santos, Amílcar Cardoso, and Alejandro Pazos. 2007. On the development of evolutionary artificial artists. Computers and Graphics 31, 6 (2007), 818--826. Google ScholarGoogle ScholarDigital LibraryDigital Library
  132. Mary L. Maher, Douglas Fisher, and Kate Brady. 2013. Computational models of surprise as a mechanism for evaluating creative design. In Proceedings of the 4th International Conference on Computational Creativity (ICCC’13). 147--151.Google ScholarGoogle Scholar
  133. Pedro Martins, Tanja Urbančič, Senja Pollak, Nada Lavrac, and Amílcar Cardoso. 2015. The good, the bad, and the AHA! blends. In Proceedings of the 6th International Conference on Computational Creativity (ICCC’15).Google ScholarGoogle Scholar
  134. Mausam, Michael Schmitz, Robert Bart, Stephen Soderland, and Oren Etzioni. 2012. Open language learning for information extraction. In Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL’12). Google ScholarGoogle ScholarDigital LibraryDigital Library
  135. Jon McCormack. 1993. Interactive evolution of l-system grammars for computer graphics modelling. In Complex Systems: From Biology to Computation. ISO Press, 118--130.Google ScholarGoogle Scholar
  136. Jon McCormack. 1996. Grammar based music composition. Complex Systems 96 (1996), 321--336.Google ScholarGoogle Scholar
  137. James McDermott. 2013. Graph grammars for evolutionary 3D design. Genetic Programming and Evolvable Machines 14, 3 (2013), 369--393. Google ScholarGoogle ScholarDigital LibraryDigital Library
  138. Stephen McGregor, Kat Agres, Matthew Purver, and Geraint A. Wiggins. 2015. From distributional semantics to conceptual spaces: A novel computational method for concept creation. Journal of Artificial General Intelligence 6 (2015), 55--86.Google ScholarGoogle ScholarCross RefCross Ref
  139. Stephen McGregor, Geraint A. Wiggins, and Matthew Purver. 2014. Computational creativity: A philosophical approach, and an approach to philosophy. In Proceedings of the 5th International Conference on Computational Creativity (ICCC’14).Google ScholarGoogle Scholar
  140. Sarnoff A. Mednick. 1962. The associative basis of the creative process. Psychological Review 69, 3 (1962), 220--232.Google ScholarGoogle ScholarCross RefCross Ref
  141. Larry R. Medsker and Lakhmi C. Jain. 1999. Recurrent Neural Networks: Design and Applications. CRC Press, Boca Raton, FL. Google ScholarGoogle ScholarDigital LibraryDigital Library
  142. Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013. Efficient estimation of word representations in vector space. In Proceedings of the Workshop at the International Conference on Learning Representations 2013 (ICLR’13).Google ScholarGoogle Scholar
  143. Dragana Miljkovic, Tjaša Stare, Igor Mozetič, Vid Podpečan, Marko Petek, Kamil Witek, et al. 2012. Signalling network construction for modelling plant defence response. PLoS One 7 (2012), e51822--1e51822--18.Google ScholarGoogle ScholarCross RefCross Ref
  144. George A. Miller, Richard Beckwith, Christiane Fellbaum, Derek Gross, and Katherine Miller. 1990. Introduction to WordNet: An on-line lexical database. International Journal of Lexicography 3, 4 (1990), 235--244.Google ScholarGoogle ScholarCross RefCross Ref
  145. Mike Mintz, Steven Bills, Rion Snow, and Dan Jurafsky. 2009. Distant supervision for relation extraction without labeled data. In Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP—Volume 2 (ACL’09). 1003--1011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  146. Nicolas Monmarché, Isabelle Mahnich, and Mohamed Slimane. 2007. Artificial art made by artificial ants. In The Art of Artificial Evolution: A Handbook on Evolutionary Art and Music, J. Romero and P. Machado (Eds.). Springer, Berlin, Germany, 227--247.Google ScholarGoogle Scholar
  147. Kristine Monteith, Tony Martinez, and Dan Ventura. 2010. Automatic generation of music for inducing emotive response. In Proceedings of the 1st International Conference on Computational Creativity. 140--149.Google ScholarGoogle Scholar
  148. Richard Morris, Scott Burton, Paul Bodily, and Dan Ventura. 2012. Soup over bean of pure joy: Culinary ruminations of an artificial chef. In Proceedings of the 3rd International Conference on Computational Creativity (ICCC’12). 119--125.Google ScholarGoogle Scholar
  149. Vivi Nastase, Preslav Nakov, Diarmuid ó Séaghdha, and Stan Szpakowicz. 2013. Semantic Relations Between Nominals. Morgan 8 Claypool. Google ScholarGoogle ScholarDigital LibraryDigital Library
  150. Roberto Navigli. 2016. Ontologies. In The Oxford Handbook of Computational Linguistics (2nd ed.), R. Mitkov (Ed.). Oxford University Press.Google ScholarGoogle Scholar
  151. Roberto Navigli and Paola Velardi. 2010. Learning word-class lattices for definition and hypernym extraction. In Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics. 1318--1327. Google ScholarGoogle ScholarDigital LibraryDigital Library
  152. Thien Hai Nguyen and Kiyoaki Shirai. 2015. Topic modeling based sentiment analysis on social media for stock market prediction. In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). 1354--1364.Google ScholarGoogle ScholarCross RefCross Ref
  153. David Norton, Derrall Heath, and Dan Ventura. 2010. Establishing appreciation in a creative system. In Proceedings of the 1st International Conference on Computational Creativity (ICCC’10). 26--35.Google ScholarGoogle Scholar
  154. Andrew Olney and Zhiqiang Cai. 2005. An orthonormal basis for topic segmentation in tutorial dialogue. In Proceedings of the Human Language Technology Conference and the Conference on Empirical Methods in Natural Language Processing (HLT/EMNLP’05). 971--978. Google ScholarGoogle ScholarDigital LibraryDigital Library
  155. Alex F. Osborn. 1953. Applied Imagination. Scribner.Google ScholarGoogle Scholar
  156. Patrick Pantel and Marco Pennacchiotti. 2006. Espresso: Leveraging generic patterns for automatically harvesting semantic relations. In Proceedings of the 21st International Conference on Computational Linguistics and the 44th Annual Meeting of the Association for Computational Linguistics (ACL’06). 113--120. Google ScholarGoogle ScholarDigital LibraryDigital Library
  157. Patrick Pantel and Deepak Ravichandran. 2004. Automatically labeling semantic classes. In Proceedings of the 2004 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT’04). 321--328.Google ScholarGoogle Scholar
  158. Michael J. Paul and Mark Dredze. 2014. Discovering health topics in social media using topic models. PLoS One 9, 8 (2014), e103408.Google ScholarGoogle ScholarCross RefCross Ref
  159. Adam Pease and Ian Niles. 2002. IEEE standard upper ontology: A progress report. Knowledge Engineering Review 17, 1 (2002), 65--70. Google ScholarGoogle ScholarDigital LibraryDigital Library
  160. Michel Plantié and Michel Crampes. 2013. Survey on social community detection. In Social Media Retrieval, N. Ramzan, R. van Zwol, J.-S. Lee, K. Clüver, and X.-S. Hua (Eds.). Springer, London, England, 65--85.Google ScholarGoogle Scholar
  161. Jeffrey Putnam. 1994. Genetic Programming of Music. Technical Report. New Mexico Institute of Mining and Technology.Google ScholarGoogle Scholar
  162. V. V. Raghavan and S. K. M. Wong. 1986. A critical analysis of vector space model for information retrieval. Journal of the American Society for Information Science 37, 5 (1986), 279--287.Google ScholarGoogle ScholarCross RefCross Ref
  163. Martin Raubal. 2004. Formalizing conceptual spaces. In Proceedings of the 3rd International Conference on Formal Ontology in Information Systems (FOIS’04). 153--164.Google ScholarGoogle Scholar
  164. Martin Raubal. 2008. Cognitive modeling with conceptual spaces. In Proceedings of the Workshop on Cognitive Models of Human Spatial Reasoning. 7--11.Google ScholarGoogle Scholar
  165. Deepak Ravichandran and Eduard Hovy. 2002. Learning surface text patterns for a question answering system. In Proceedings of the 40th Annual Meeting on Association for Computational Linguistics (ACL’02). 41--47. Google ScholarGoogle ScholarDigital LibraryDigital Library
  166. John T. Rickard. 2006. A concept geometry for conceptual spaces. Fuzzy Optimization and Decision Making 5, 4 (2006), 311--329. Google ScholarGoogle ScholarDigital LibraryDigital Library
  167. John T. Rickard, Janet Aisbett, and Greg Gibbon. 2007a. Reformulation of the theory of conceptual spaces. Information Sciences 177, 21 (2007), 4539--4565. Google ScholarGoogle ScholarDigital LibraryDigital Library
  168. John T. Rickard, Janet Aisbett, and Greg Gibbon. 2007b. Knowledge representation and reasoning in conceptual spaces. In Proceedings of the 1st IEEE Symposium on Foundations of Computational Intelligence (FOCI’07). 583--590.Google ScholarGoogle ScholarCross RefCross Ref
  169. Steven Rooke. 1996. The Evolutionary Art of Steven Rooke. Retrieved June 1, 2014 from http://srooke.com.Google ScholarGoogle Scholar
  170. Nicholas Roussopoulos and John Mylopoulos. 1975. Using semantic networks for data base management. In Proceedings of the 1st International Conference on Very Large Data Bases (VLDB’75). 144--172. Google ScholarGoogle ScholarDigital LibraryDigital Library
  171. Gerard Salton. 1971. The SMART Retrieval System—Experiments in Automatic Document Processing. Prentice-Hall, Upper Saddle River, NJ. Google ScholarGoogle ScholarDigital LibraryDigital Library
  172. Gerard Salton. 1989. Automatic Text Processing: The Transformation, Analysis, and Retrieval of Information by Computer. Addison Wesley Longman, Boston, MA. Google ScholarGoogle ScholarDigital LibraryDigital Library
  173. Sunita Sarawagi. 2008. Information extraction. Foundations and Trends in Databases 1, 3 (2008), 261--377. Google ScholarGoogle ScholarDigital LibraryDigital Library
  174. Rob Saunders and John Gero. 2001. The digital clockwork muse: A computational model of aesthetic evolution. In Proceedings of the AISB’01 Symposium on Artificial Intelligence and Creativity in Arts and Science (AISB’01). 12--21.Google ScholarGoogle Scholar
  175. Angela Schwering and Martin Raubal. 2005. Spatial relations for semantic similarity measurement. In Perspectives in Conceptual Modeling, J. Akoka, S. W. Liddle, I.-Y. Song, M. Bertolotto, I. Comyn-Wattiau, W.-J. Heuvel, et al. (Eds.). Lecture Notes in Computer Science, Vol. 3770. Springer, 259--269. Google ScholarGoogle ScholarDigital LibraryDigital Library
  176. Thomas Serre, Gabriel Kreiman, Minjoon Kouh, Charles Cadieu, Ulf Knoblich, and Tomaso Poggio. 2007. A quantitative theory of immediate visual recognition. Progress in Brain Research 165, (2007), 33--56.Google ScholarGoogle Scholar
  177. Karl Sims. 1991. Artificial evolution for computer graphics. ACM Computer Graphics 25 (1991), 319--328. Google ScholarGoogle ScholarDigital LibraryDigital Library
  178. Push Singh, Thomas Lin, Erik T. Mueller, Grace Lim, Travell Perkins, and Wanli Zhu. 2002. Open mind common sense: Knowledge acquisition from the general public. In On the Move to Meaningful Internet Systems 2002: CoopIS, DOA, and ODBASE, R. Meersman and Z. Tari (Eds.). Lecture Notes in Computer Science, Vol. 2519. Springer, 1223--1237. Google ScholarGoogle ScholarDigital LibraryDigital Library
  179. Josef Sivic, Bryan C. Russell, Alexei A. Efros, Andrew Zisserman, and William T. Freeman. 2005. Discovering objects and their location in images. In Proceedings of the 10th IEEE International Conference on Computer Vision (ICCV’05), Vol. 1. 370--377. Google ScholarGoogle ScholarDigital LibraryDigital Library
  180. Benjamin D. Smith and Guy E. Garnett. 2012. Improvising musical structure with hierarchical neural nets. In Proceedings of the 8th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE’12). 63--67.Google ScholarGoogle Scholar
  181. Rion Snow, Daniel Jurafsky, and Andrew Y. Ng. 2005. Learning syntactic patterns for automatic hypernym discovery. In Advances in Neural Information Processing Systems. MIT Press, Cambridge, MA, 1297--1304. Google ScholarGoogle ScholarDigital LibraryDigital Library
  182. Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D. Manning, Andrew Ng, et al. 2013. Recursive deep models for semantic compositionality over a sentiment treebank. In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing (EMNLP’13). 1631--1642.Google ScholarGoogle Scholar
  183. John F. Sowa. 1992. Semantic networks. In Encyclopedia of Artificial Intelligence (2nd ed.), S. C. Shapiro (Ed.). John Wiley 8 Sons, New York, NY.Google ScholarGoogle Scholar
  184. John F. Sowa. 2000. Knowledge Representation: Logical, Philosophical, and Computational Foundations. Brooks Cole Publishing Co., Pacific Grove, CA. Google ScholarGoogle ScholarDigital LibraryDigital Library
  185. John F. Sowa. 2010. Ontology. Retrieved June 1, 2014 from http://www.jfsowa.com/ontology.Google ScholarGoogle Scholar
  186. Karen Spärck Jones. 1972. A statistical interpretation of term specificity and its application in retrieval. Journal of Documentation 28, 1 (1972), 11--21.Google ScholarGoogle ScholarCross RefCross Ref
  187. Lee Spector and Adam Alpern. 1994. Criticism, culture, and the automatic generation of artworks. In Proceedings of the 12th National Conference on Artificial Intelligence (AAAI’94). 3--8. Google ScholarGoogle ScholarDigital LibraryDigital Library
  188. Carlo Strapparava, Alesandro Valitutti, and Oliviero Stock. 2007. Automatizing two creative functions for advertising. In Proceedings of the 4th International Joint Workshop on Computational Creativity. 99--108.Google ScholarGoogle Scholar
  189. Ron Sun. 2008. The Cambridge Handbook of Computational Psychology. Cambridge University Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  190. Yizhou Sun and Jiawei Han. 2012. Mining Heterogeneous Information Networks: Principles and Methodologies. Morgan 8 Claypool. Google ScholarGoogle ScholarDigital LibraryDigital Library
  191. Yizhou Sun and Jiawei Han. 2013. Mining heterogeneous information networks: A structural analysis approach. ACM SIGKDD Exploration Newsletter 14, 2 (2013), 20--28. Google ScholarGoogle ScholarDigital LibraryDigital Library
  192. Yizhou Sun, Yintao Yu, and Jiawei Han. 2009. Ranking-based clustering of heterogeneous information networks with star network schema. In Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’09). 797--806. Google ScholarGoogle ScholarDigital LibraryDigital Library
  193. Don R. Swanson. 1990. Medical literature as a potential source of new knowledge. Bulletin of the Medical Library Association 78, 1 (1990), 29--37.Google ScholarGoogle Scholar
  194. Asuka Terai and Masanori Nakagawa. 2009. A neural network model of metaphor generation with dynamic interaction. In Proceedings of the 23rd International Conference on Artificial Neural Networks (ICANN’09). 779--788. Google ScholarGoogle ScholarDigital LibraryDigital Library
  195. Miles Thorogood and Philippe Pasquier. 2013. Computationally created soundscapes with audio metaphor. In Proceedings of the 4th International Conference on Computational Creativity (ICCC’13). 1--7.Google ScholarGoogle Scholar
  196. Peter M. Todd. 1992. A connectionist system for exploring melody space. In Proceedings of the International Computer Music Conference (ICMC’92). 65--68.Google ScholarGoogle Scholar
  197. Hannu Toivonen and Oskar Gross. 2015. Data mining and machine learning in computational creativity. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 5, 6 (2015), 265--275. Google ScholarGoogle ScholarDigital LibraryDigital Library
  198. Nao Tokui and Hitoshi Iba. 2000. Music composition with interactive evolutionary computation. In Proceedings of the 3rd International Conference on Generative Art (GA’00), Vol. 17. 215--226.Google ScholarGoogle Scholar
  199. Peter D. Turney. 2007. Empirical Evaluation of Four Tensor Decomposition Algorithms. Technical Report ERB-1152. National Research Council, Institute for Information Technology.Google ScholarGoogle Scholar
  200. Peter D. Turney and Michael Littman. 2003. Measuring praise and criticism: Inference of semantic orientation from association. ACM Transactions on Information Systems 21, 4 (2003), 315--346. Google ScholarGoogle ScholarDigital LibraryDigital Library
  201. Peter D. Turney and Patrick Pantel. 2010. From frequency to meaning: Vector space models of semantics. Artificial Intelligence Research 37, 1 (2010), 141--188. Google ScholarGoogle ScholarDigital LibraryDigital Library
  202. Tatsuo Unemi. 1999. SBART2.4: Breeding 2D CG images and movies, and creating a type of collage. In Proceedings of the 3rd International Conference on Knowledge-Based Intelligent Information Engineering Systems (KES’99). 288--291.Google ScholarGoogle Scholar
  203. Frank van der Velde. 1993. Is the brain an effective turing machine or a finite-state machine? Psychological Research 55 (1993), 71--79.Google ScholarGoogle ScholarCross RefCross Ref
  204. Frank van der Velde. 2015. Communication, concepts and grounding. Neural Networks 62 (2015), 112--117. Google ScholarGoogle ScholarDigital LibraryDigital Library
  205. Frank van der Velde and Marc de Kamps. 2006. Neural blackboard architectures of combinatorial structures in cognition. Behavioral and Brain Sciences 29 (2006), 37--70.Google ScholarGoogle ScholarCross RefCross Ref
  206. Frank Van Harmelen, Vladimir Lifschitz, and Bruce Porter (Eds.). 2008. Handbook of Knowledge Representation. Elsevier, Amsterdam, Netherlands. Google ScholarGoogle ScholarDigital LibraryDigital Library
  207. Tony Veale. 2012. From conceptual ‘‘mash-ups’’ to ‘‘bad-ass’’ blends: A robust computational model of conceptual blending. In Proceedings of the 3rd International Conference on Computational Creativity (ICCC’12). 1--8.Google ScholarGoogle Scholar
  208. Paola Velardi, Stefano Faralli, and Roberto Navigli. 2013. OntoLearn reloaded: A graph-based algorithm for taxonomy induction.Computational Linguistics 39, 3 (2013), 665--707.Google ScholarGoogle Scholar
  209. Chris Venour, Graeme Ritchie, and Chris Mellish. 2010. Quantifying humorous lexical incongruity. In Proceedings of the 1st International Conference on Computational Creativity (ICCC’10). 268--277.Google ScholarGoogle Scholar
  210. Tsung-Hsien Wen, Milica Gašić, Nikola Mrkšić, Lina M. Rojas-Barahona, Pei-Hao Su, David Vandyke, et al. 2016. Multi-domain neural network language generation for spoken dialogue systems. In Proceedings of the 2016 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT’16).Google ScholarGoogle ScholarCross RefCross Ref
  211. Jianshu Weng, Ee-Peng Lim, Jing Jiang, and Qi He. 2010. Twitterrank: Finding topic-sensitive tnfluential twitterers. In Proceedings of the 3rd ACM International Conference on Web Search and Data Mining (WSDM’10). 261--270. Google ScholarGoogle ScholarDigital LibraryDigital Library
  212. Geraint A. Wiggins. 2006a. A preliminary framework for description, analysis and comparison of creative systems. Journal of Knowledge Based Systems 19, 7 (2006), 449--458. Google ScholarGoogle ScholarDigital LibraryDigital Library
  213. Geraint A. Wiggins. 2006b. Searching for computational creativity. New Generation Computing 24, 3 (2006), 209--222.Google ScholarGoogle ScholarDigital LibraryDigital Library
  214. M. Tsan Wong and A. Honwai Chun. 2008. Automatic haiku generation using VSM. In Proceedings of the 7th WSEAS International Conference on Applied Computer and Applied Computational Science (ACACOS’08). 318--323.Google ScholarGoogle Scholar
  215. S. K. M. Wong, W. Ziarko, and P. C. N. Wong. 1985. Generalized vector spaces model in information retrieval. In Proceedings of the 8th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR’85). 18--25. Google ScholarGoogle ScholarDigital LibraryDigital Library
  216. Ping Xiao and Josep Blat. 2013. Generating apt metaphor ideas for pictorial advertisements. In Proceedings of the 4th International Conference on Computational Creativity (ICCC’13). 8--15.Google ScholarGoogle Scholar
  217. Bo Yang, Dayou Liu, and Jiming Liu. 2010. Discovering communities from social networks: Methodologies and applications. In Handbook of Social Network Technologies and Applications, B. Furht (Ed.). Springer USA, 331--346.Google ScholarGoogle Scholar
  218. Dengyong Zhou, Olivier Bousquet, Thomas Navin Lal, Jason Weston, and Bernhard Schölkopf. 2003. Learning with local and global consistency. In Advances in Neural Information Processing Systems, Vol. 16. 321--328. Google ScholarGoogle ScholarDigital LibraryDigital Library
  219. Song-Chun Zhu and David Mumford. 2007. A stochastic grammar of images. Foundations and Trends® in Computer Graphics and Vision 2, 4 (2007), 259--362. Google ScholarGoogle ScholarDigital LibraryDigital Library
  220. Hai Zhuge. 2012. The semantic link network. In The Knowledge Grid: Toward Cyber-Physical Society (2nd ed.). World Scientific Publishing Co., 65--210.Google ScholarGoogle Scholar

Index Terms

  1. Conceptual Representations for Computational Concept Creation

          Recommendations

          Comments

          Login options

          Check if you have access through your login credentials or your institution to get full access on this article.

          Sign in

          Full Access

          • Published in

            cover image ACM Computing Surveys
            ACM Computing Surveys  Volume 52, Issue 1
            January 2020
            758 pages
            ISSN:0360-0300
            EISSN:1557-7341
            DOI:10.1145/3309872
            • Editor:
            • Sartaj Sahni
            Issue’s Table of Contents

            Copyright © 2019 Owner/Author

            This work is licensed under a Creative Commons Attribution International 4.0 License.

            Publisher

            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 25 February 2019
            • Accepted: 1 February 2018
            • Revised: 1 November 2017
            • Received: 1 September 2015
            Published in csur Volume 52, Issue 1

            Permissions

            Request permissions about this article.

            Request Permissions

            Check for updates

            Qualifiers

            • survey
            • Research
            • Refereed

          PDF Format

          View or Download as a PDF file.

          PDF

          eReader

          View online with eReader.

          eReader

          HTML Format

          View this article in HTML Format .

          View HTML Format