A Bisociated Domain-Based Serendipitous Novelty-Recommendation Technique for Recommender Systems

Traditional recommendation paradigms such as content-based filtering (CBF) tend to recommend items that are very similar to user profile characteristics and item input, resulting in the classical twin problem of overspecialization and concentration bias of recommendations. This twin problem is prevalent with CBF recommender systems due to the utilisation of accuracy metrics to retrieve similar items, and, limiting recommendation computations to single recognized user-centered domains, rather than cross-domains.  This paper proposes a Bisociated domain-based serendipitous novelty recommendation techniques using Bisolinkers exploratory creativity discovery technique. The use of Bisolinkers enables establishing unique links between two seemingly unrelated domains, to enhance recommendation accuracy and user satisfaction. The presence of similar terms in two habitually incompatible domains demonstrates that two seemingly unrelated domains contain elements that are related and may act as a link to connect these two domains. Keywords: recommender systems, novelty, machine learning, outlier detection, bisociation &nbsp

Towards creative information exploration based on Koestler's concept of bisociation

Creative information exploration refers to a novel framework for exploring large volumes of heterogeneous information. In particular, creative information exploration seeks to discover new, surprising and valuable relationships in data that would not be revealed by conventional information retrieval, data mining and data analysis technologies. While our approach is inspired by work in the field of computational creativity, we are particularly interested in a model of creativity proposed by Arthur Koestler in the 1960s. Koestler’s model of creativity rests on the concept of bisociation. Bisociative thinking occurs when a problem, idea, event or situation is perceived simultaneously in two or more “matrices of thought” or domains. When two matrices of thought interact with each other, the result is either their fusion in a novel intellectual synthesis or their confrontation in a new aesthetic experience. This article discusses some of the foundational issues of computational creativity and bisociation in the context of creative information exploration

The entrepreneurial mind - torn between beliefs, attitude, cognition, and behavior

Entrepreneurship is about making decisions: whether or not to exploit a recognized opportunity, how to interact with potential customers or competitors, which financial source to pursue, how to select a team, and many more. Most of these decisions are made under circumstances of imperfect information that involves a high level of uncertainty. Coping with such circumstances requires cognitive effort. While some individuals tend towards heartfelt cognition styles with intuitive decisions, others prefer analytical decisions from the head. This work investigates the relationship between cognition styles and decision-making logics and additionally places constructs such as problem-solving ability, self-efficacy, or reflection skills as crucial determinants for entrepreneurial decision-making. In a twofold study, this dissertation quantitatively and qualitatively investigates how the determinants relate to each other and which insights could be derived from that investigation. Both studies contribute to the understanding of cognition styles and decision-making logics in an entrepreneurial environment. By introducing novel determinants to the Theory of Planned Behavior, this dissertation opens the door for practical and educational implications

Applying blended conceptual spaces to variable choice and aesthetics in data visualisation

Computational creativity is an active area of research within the artificial intelligence domain that investigates what aspects of computing can be considered as an analogue to the human creative process. Computers can be programmed to emulate the type of things that the human mind can. Artificial creativity is worthy of study for two reasons. Firstly, it can help in understanding human creativity and secondly it can help with the design of computer programs that appear to be creative. Although the implementation of creativity in computer algorithms is an active field, much of the research fails to specify which of the known theories of creativity it is aligning with. The combination of computational creativity with computer generated visualisations has the potential to produce visualisations that are context sensitive with respect to the data and could solve some of the current automation problems that computers experience. In addition theories of creativity could theoretically compute unusual data combinations, or introducing graphical elements that draw attention to the patterns in the data. More could be learned about the creativity involved as humans go about the task of generating a visualisation. The purpose of this dissertation was to develop a computer program that can automate the generation of a visualisation, for a suitably chosen visualisation type over a small domain of knowledge, using a subset of the computational creativity criteria, in order to try and explore the effects of the introduction of conceptual blending techniques. The problem is that existing computer programs that generate visualisations are lacking the creativity, intuition, background information, and visual perception that enable a human to decide what aspects of the visualisation will expose patterns that are useful to the consumer of the visualisation. The main research question that guided this dissertation was, “How can criteria derived from theories of creativity be used in the generation of visualisations?”. In order to answer this question an analysis was done to determine which creativity theories and artificial intelligence techniques could potentially be used to implement the theories in the context of those relevant to computer generated visualisations. Measurable attributes and criteria that were sufficient for an algorithm that claims to model creativity were explored. The parts of the visualisation pipeline were identified and the aspects of visualisation generation that humans are better at than computers was explored. Themes that emerged in both the computational creativity and the visualisation literature were highlighted. Finally a prototype was built that started to investigate the use of computational creativity methods in the ‘variable choice’, and ‘aesthetics’ stages of the data visualisation pipeline.School of ComputingM. Sc. (Computing

Improving Entrepreneurial Opportunity Recognition through Web Content Analytics

The ability to recognize and develop an opportunity into a venture defines an entrepreneur. Factors such as prior knowledge, cognitive and creative capabilities are shown to affect opportunity recognition in entrepreneurs. Research also shows that experienced entrepreneurs search and scan for information to discover opportunities. Searching and scanning for information mediate the effect of prior knowledge on novice entrepreneurs and enable them to better identify and recognize opportunities even when lacking knowledge and experience. There is less focus in research on finding empirically proven techniques and methods to develop and enhance opportunity recognition in student entrepreneurs. The lack of knowledge has been linked to more likelihood of business failures. This study aims to develop a model for opportunity recognition by using web content mining for student entrepreneurs to better identify and recognize business opportunities. The model will be evaluated through qualitative and quantitative methods. A prototype of the model is planned to be built to evaluate the efficacy and usefulness of the model. This model is expected to enable graduate entrepreneurs to generate more business ideas that are more innovative and viable

Dance your way through entrepreneurial irrationality, errors, and rejection: unveiling entrepreneurial cognition, decisions, and learning under complex circumstances

The entrepreneurial journey is an emotional rollercoaster with unpredictable ups and downs, and entrepreneurial actions are performed in an ill-defined environment. For educational psychologists, the strengthening of students’ abilities to solve and reflect on ill-defined situations of the venturing process is the main learning objective. The discipline of entrepreneurship can benefit from research that enables clarification towards the entrepreneurial context and understanding of the individual’s behavior that promotes new venture formation. Hence, this dissertation contributes to establishing a better understanding of the complex and dynamic entrepreneurial context and particularly on the cognitive aspects that facilitate entrepreneurial activities. The focus lies particularly on promoting academic entrepreneurship. There is growing recognition that research on college students is central to the development of entrepreneurial activities and this group should receive higher attention. For this purpose, four studies have been carried out to provide novel insights into entrepreneurial cognition, learning, and academic entrepreneurship. The first study is dedicated to detangling the complex nature of the entrepreneurial environment. Literature calls for novel research that provides more clarity on the role of rationality that enables to unveil the relationship between the precarious circumstances and entrepreneurial action. More so, integrating the concept of rationality in entrepreneurship education can help prepare college students towards situations in which lack of information is dominant. While the first study strives to understand the contextual environment of entrepreneurial decisions, the second study investigates entrepreneurial activities from a cognitive-psychological point of view. A central concept for entrepreneurial activities is opportunity recognition. The second study focuses on cognitive factors that affect the process of opportunity recognition. The intention of this study is to explain the emergence of entrepreneurial opportunities and to contribute to differentiating between entrepreneurs and non-entrepreneurs. The third study continues with analyzing factors that influence entrepreneurial activities and examines the impact of entrepreneurial rejection on the individual’s decision to continue with the entrepreneurial opportunity. Finally, the last study is dedicated to understanding troubling concepts during the process of entrepreneurial learning. Entrepreneurship education bears the potential to equip future entrepreneurs with the entrepreneurial competencies required to deal with challenging situations during the venturing process. Thus, the final study investigates troublesome knowledge in entrepreneurship education in order to provide practical implications for dealing with these obstacles

Creativity, Innovation and life in the Lily-Pond: nurturing the design and technology family while keeping the alligators fed. DATA International Research Conference: International Keynote

Casting one’s net to capture understandings of creativity and innovation can produce a rich catch that includes: political and industrial ideal; cultural vogue; economic curative; educational whim; psychological theory; curriculum dream; a student’s right; or, a school’s duty. It would seem that everyone in the lily-pond has a claim but what is a reasonable balance and who should decide? If the whole business isn’t just a passing fad then practising design and technology (D&T) professionals have a challenge. The answer lies in a balanced diet of theory, experience, knowledge, history and foresight – and knowing when to chuck which alligator what chop.Key words creativity, innovation, design and technology, curriculum

Baseline Methods for Automated Fictional Ideation

The invention of fictional ideas (ideation) is often a central process in the creative production of artefacts such as poems, music and paintings, but has barely been studied in the Computational Creativity community. We present here three baseline approaches for automated fictional ideation, using methods which invert and alter facts from the ConceptNet and ReVerb databases, and perform bisociative discovery. For each method, we present a curation analysis, by calculating the proportion of ideas which pass a typicality evaluation. We further evaluate one ideation approach through a crowd- sourcing experiment in which participants were asked to rank ideas. The results from this study, and the baseline methods and methodologies presented here, constitute a firm basis on which to build more sophisticated models for automated ideation with evaluative capacity

Measurement scale of international opportunity identification in early internationalization firms

Purpose: The purpose of this paper is to develop the international opportunity identification (IOI) scale through psychometric evaluation in an emerging economy context. Design/methodology/approach: Samples consist of international firms operating in the apparel industry in Bangladesh. Exploratory factor analysis (EFA) was conducted on the first wave of responses to unfold the underlying dimensions of IOI. The second wave of data was used to confirm the validity of IOI scale through confirmatory factor analysis (CFA). Findings: EFA suggests a unidimensional scale, which is supported by CFA. The relationship between IOI and financial performance is significant and confirms nomological validity. Results also confirm the validity and reliability of the IOI scale. Originality/value: This study indicates that IOI is a reliable and valid scale to measure the strategic action of the international firms operating in emerging economies, and has a positive relationship with financial performance