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Publisher: IBM   (Total: 1 journals)   [Sort alphabetically]

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IBM J. of Research and Development     Hybrid Journal   (Followers: 18, SJR: 0.275, CiteScore: 1)
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IBM Journal of Research and Development
Journal Prestige (SJR): 0.275
Citation Impact (citeScore): 1
Number of Followers: 18  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0018-8646
Published by IBM Homepage  [1 journal]
  • Preface: Advances in Computational Creativity Technology
    • Pages: 1 - 2
      PubDate: Jan.-Feb. 2019
      Issue No: Vol. 63, No. 1 (2019)
       
  • A computational theory of evaluation in creative design
    • Authors: B. J. Wiltgen;A. K. Goel;
      Pages: 1:1 - 1:11
      Abstract: Creative problems are ill-defined, and thus experimentation, evaluation, and iteration are key elements of creative problem solving. We present a computational theory of evaluation in creative design. Our technique evaluates a design concept by analogically comparing it with alternative articulations of the concept. We operationalize this theory of analogical comparison in the context of biologically inspired design that uses biological analogies for conceptual design of technological systems. Our technique of analogical comparison supports evaluation of prior technological designs, biological source cases, as well as candidate conceptual designs through analogical mapping between alternative functional models of these design concepts. Given a functional model of a design concept and an alternative functional model of the same design concept, analogical comparison leverages a novel hierarchically organized analogical mapping technique to align the two models and identify the differences between them. Our technique is implemented in an operational artificial intelligence agent called Design Evaluation through Simulation and Comparison (DESC). We evaluate DESC through computational experimentation across several models to illustrate its strengths and limits and to highlight areas for future research.
      PubDate: Jan.-Feb. 2019
      Issue No: Vol. 63, No. 1 (2019)
       
  • Mathematical limit theorems for computational creativity
    • Authors: L. R. Varshney;
      Pages: 2:1 - 2:12
      Abstract: Creativity is the generation of an idea or artifact judged to be novel and high-quality by a knowledgeable social group, and is often said to be the pinnacle of intelligence. Several computational creativity systems of various designs are now being demonstrated and deployed. These myriad design possibilities raise the natural question: Are there fundamental limits to creativity' Here, we define a mathematical abstraction to capture key aspects of combinatorial creativity and study fundamental tradeoffs between novelty and quality. The functional form of this fundamental limit resembles the capacity-cost relationship in information theory, especially when measuring novelty using Bayesian surprise—the relative entropy between the empirical distribution of an inspiration set and that set updated with the new idea or artifact. As such, we show how information geometry techniques provide insight into the limits of creativity and find that the maturity of the creative domain directly parameterizes the fundamental limit. This result is extended to the case when there is a diverse audience for creativity and when the quality function is not known but must be estimated from samples.
      PubDate: Jan.-Feb. 2019
      Issue No: Vol. 63, No. 1 (2019)
       
  • What is deemed computationally creative'
    • Authors: S. Agrawal;A. Sankaran;A. Laha;S. A. Chemmengath;D. Shrivastava;K. Sankaranarayanan;
      Pages: 3:1 - 3:12
      Abstract: In this new era of computational creativity, where artificial intelligence (AI) systems are attempting to achieve human-level creativity, a set of golden questions needs to be answered, such as “What kind of systems are creative systems'” and “When does a system qualify as truly creative'” The existing generation of AI-driven cognitive systems is based on the goal of achieving human-level intelligence, not human-level creativity. Creativity is considered subjective with respect to both the application domains and the perceiving end-user. In this paper, we postulate the dimensions and factors that distinguish creativity and intelligence, such as novelty, value, surprise, influence, coherence, correctness, and comprehensibility. We group the application domains into time-dependent and time-independent ones and define a framework to describe these dimensions in each application. In addition to defining the factors that determine creativity, we also suggest ideas on how to evaluate these factors. We strongly believe that the proposed framework would act as the basis for building and evaluating creative systems and also provide us with the ultimate goal for achieving human-level creativity.
      PubDate: Jan.-Feb. 2019
      Issue No: Vol. 63, No. 1 (2019)
       
  • Cognitive color palette creation using client message and color psychology
    • Authors: E. Khabiri;Y. Li;P. Mazzoleni;D. Vadgama;
      Pages: 4:1 - 4:10
      Abstract: Color psychology is the study of the effect of colors on human behavior. This area of study is interesting and challenging because there is no simple “one-size-fits all” mapping between a color and the message that color can evoke in a particular person. Nevertheless, many of our daily decisions are influenced by the color palettes being presented to us. In this paper, we propose a novel computational algorithm to create color palettes that convey certain messages. It starts by constructing a weighted graph of color categories and messages that are based on semantic similarities between vector representation of the messages and delta-E color similarities between colors. The color selection process for a given message includes applying a Personalized PageRank algorithm on the graph, treating the message nodes as the personalizing factors. As a result, we have a distribution of probabilities over all the color nodes that have higher probabilities for the nodes neighboring to given messages. Finally, palettes are ranked on the basis of visual aesthetics, novelty, and the conflicting/reinforcing messages they evoke. We have applied this work to several interesting use cases where artists and fashion designers used the resulting color palettes to assist their creation process.
      PubDate: Jan.-Feb. 2019
      Issue No: Vol. 63, No. 1 (2019)
       
  • A computational model for visual conceptual blends
    • Authors: P. Karimi;M. L. Maher;K. Grace;N. Davis;
      Pages: 5:1 - 5:10
      Abstract: Computational creative systems have the potential to augment the creative design process, particularly in co-creative contexts. We present a computational model for generating visual conceptual blends in the domain of sketching. Our system is motivated by the desire to encourage curiosity, facilitate creative ideation, and overcome design fixation. We start with a model for “conceptual shift”: when a sketch recognized as belonging to one category is visually similar to a sketch from a semantically distinct category. Identifying a potential conceptual shift enables visual analogy and/or conceptual blending. The intent is that these conceptually shifted or blended sketches could be presented to designers to encourage analogical reasoning and creative outcomes. We define and demonstrate our model for the conceptual shift task and alternative approaches for enabling conceptual blends. We describe future plans for evaluation in co-creative contexts.
      PubDate: Jan.-Feb. 2019
      Issue No: Vol. 63, No. 1 (2019)
       
  • Creative tagline generation framework for product advertisement
    • Authors: A. Ray;P. Agarwal;C. K. Maurya;G. B. Dasgupta;
      Pages: 6:1 - 6:10
      Abstract: The ubiquitous nature of the Internet and its applicability as an inexpensive advertising media has resulted in Web and mobile platforms to be on target for product advertising. Existing advertising approaches on different social media platforms include sponsored search, e-mail advertising, banner ads, etc., to attract customers. The current systems for advertising on these platforms require the advertisers to manually come up with a catchy tagline, which is time-consuming and a challenging task. To overcome this problem, we propose a novel framework to automatically generate novel and catchy taglines tailored for advertisers' products. The framework consists of a domain-specific knowledge graph, a novel modified long short-term memory (LSTM) (we call it CopyLSTM), and a neural paraphrase model. We also curate and build a database of fashion products with 100K input product features and 300K sentences (three sentences per product data). This dataset is used to populate the knowledge graph and learn the modified LSTM to generate taglines. The proposed framework is evaluated on different metrics for sentence quality and compared with the state-of-art methods for tagline generation. Subjective evaluation was performed to understand the novelty and creativity of the generated tagline.
      PubDate: Jan.-Feb. 2019
      Issue No: Vol. 63, No. 1 (2019)
       
  • A big data approach to computational creativity: The curious case of Chef
           Watson
    • Authors: L. R. Varshney;F. Pinel;K. R. Varshney;D. Bhattacharjya;A. Schörgendorfer;Y.-M. Chee;
      Pages: 7:1 - 7:18
      Abstract: Computational creativity is an emerging branch of artificial intelligence that places computers in the center of the creative process. Broadly, creativity involves a generative step to produce many ideas and a selective step to determine the ones that are the best. Many previous attempts at computational creativity, however, have not been able to achieve a valid selective step. This paper shows how bringing data sources from the creative domain and from hedonic psychophysics together with machine learning and data analytics techniques can overcome this shortcoming to yield a system that can produce novel and high-quality creative artifacts. To demonstrate our data-driven approach, we developed and deployed a computational creativity system for culinary recipes and menus, Chef Watson, which can operate either autonomously or semiautonomously with human interaction. We present the basic system architecture, data engineering, and algorithms that are involved. Experimental results demonstrate the system passes the test for creativity based on the consensual assessment technique, producing a novel and flavorful recipe. Large-scale deployments are also discussed.
      PubDate: Jan.-Feb. 2019
      Issue No: Vol. 63, No. 1 (2019)
       
  • The long path to narrative generation
    • Authors: P. Gervás;E. Concepción;C. León;G. Méndez;P. Delatorre;
      Pages: 8:1 - 8:10
      Abstract: Narrative generation, understood as the task of constructing computational models of the way in which humans build stories, has been shown to involve a number of separate processes, related to different purposes to which it can be applied, and focusing on specific features that make stories valuable. This paper reviews a set of story generation systems developed by the authors of this contribution, each focusing on different aspects and functions of stories. These systems provide an initial breakdown of how the term “storytelling” might be either instantiated or broken down into component processes. The systems cover functionalities such as generating valid plot structures, simulating character's behaviors or the evolution of affinities between them, either reporting or fictionalizing events observed in real life, and revising a story draft to maximize the suspense it induces in its readers. These functionalities are not intended to exhaust the set of possible operations involved in storytelling, but they constitute an initial set to understand the complexity of the task. The paper also includes two proposals—one theoretical and one technological—for understanding how a set of such functionalities might be composed into a broader operational process that produces more elaborate stories.
      PubDate: Jan.-Feb. 2019
      Issue No: Vol. 63, No. 1 (2019)
       
  • Computational creativity infrastructure for online software composition: A
           conceptual blending use case
    • Authors: P. Martins;H. Gonçalo Oliveira;J. C. Gonçalves;A. Cruz;F. A. Cardoso;M. Žnidaršič;N. Lavrač;S. Linkola;H. Toivonen;R. Hervás;G. Méndez;P. Gervás;
      Pages: 9:1 - 9:17
      Abstract: Computational creativity (CC) is a multidisciplinary research field, studying how to engineer software that exhibits behavior that would reasonably be deemed creative. This paper shows how composition of software solutions in this field can effectively be supported through a CC infrastructure that supports user-friendly development of CC software components and workflows, their sharing, execution, and reuse. The infrastructure allows CC researchers to build workflows that can be executed online and be easily reused by others through the workflow web address. Moreover, it enables the building of procedures composed of software developed by different researchers from different laboratories, leading to novel ways of software composition for computational purposes that were not expected in advance. This capability is illustrated on a workflow that implements a Concept Generator prototype based on the Conceptual Blending framework. The prototype consists of a composition of modules made available as web services, and is explored and tested through experiments involving blending of texts from different domains, blending of images, and poetry generation.
      PubDate: Jan.-Feb. 2019
      Issue No: Vol. 63, No. 1 (2019)
       
 
 
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