Relevant bibliographies by topics / Contextual intelligence

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Contextual intelligence'

Author: Grafiati
Published: 4 June 2021
Last updated: 3 February 2022

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Journal articles on the topic "Contextual intelligence"

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Bolwell, Brian J. "Contextual Intelligence." Oncology Times 40, no. 9 (May 2018): 26. http://dx.doi.org/10.1097/01.cot.0000533693.68948.71.

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Ooi, Beng Chin, Kian Lee Tan, Quoc Trung Tran, James W. L. Yip, Gang Chen, Zheng Jye Ling, Thi Nguyen, Anthony K. H. Tung, and Meihui Zhang. "Contextual crowd intelligence." ACM SIGKDD Explorations Newsletter 16, no. 1 (September 25, 2014): 39–46. http://dx.doi.org/10.1145/2674026.2674032.

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Brown, Charles H., Dan Gould, and Sandra Foster. "A Framework for Developing Contextual Intelligence (CI)." Sport Psychologist 19, no. 1 (March 2005): 51–62. http://dx.doi.org/10.1123/tsp.19.1.51.

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This article reviews the emerging concept of Contextual Intelligence (CI) and its relevance to sport psychology. Interviews with expert performance consultants suggest that CI is a key factor in successful consultations. Although CI has often been considered a tacit process learned indirectly through experience, systems theory and institutional research offer models for assessing organizations and developing contextual “maps.” By having a framework and language for assessing context, sport psychologists can more effectively develop contextually intelligent and culturally appropriate interventions. The authors offer a framework for assessing context and developing contextual “maps.” Specific guidelines and principles for designing contextually intelligent interventions are provided.
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Ling, Foo Choi, Jugindar Singh Kartar Singh, and Thilageswary Arumugam. "Employee Contextual Performance, Social Intelligence, Spiritual Intelligence: A quantitative Study in Malaysia." International Journal of Psychosocial Rehabilitation 24, no. 02 (February 12, 2020): 968–81. http://dx.doi.org/10.37200/ijpr/v24i2/pr200404.

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Khanna, Tarun. "A Case for Contextual Intelligence." Management International Review 55, no. 2 (March 25, 2015): 181–90. http://dx.doi.org/10.1007/s11575-015-0241-z.

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Salthouse, Timothy A., Jeffrey E. Pink, and Elliot M. Tucker-Drob. "Contextual analysis of fluid intelligence." Intelligence 36, no. 5 (September 2008): 464–86. http://dx.doi.org/10.1016/j.intell.2007.10.003.

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Choi ling, Foo, Jugindar Singh Kartar Singh, and Thilageswary Arumugam. "Spiritual Intelligence, Emotional Intelligence and Contextual Performance: An Empirical Study in the Services Sector in Malaysia." International Journal of Psychosocial Rehabilitation 24, no. 02 (February 12, 2020): 939–51. http://dx.doi.org/10.37200/ijpr/v24i2/pr200402.

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Weidenbach, Christoph, and Patrick Wischnewski. "Subterm contextual rewriting." AI Communications 23, no. 2-3 (2010): 97–109. http://dx.doi.org/10.3233/aic-2010-0459.

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Suan, Chin, Susan Tee, and Rosman Md Yusoff. "ROLE OF EMOTIONAL INTELLIGENCE IN ENHANCING CONTEXTUAL PERFORMANCE." PEOPLE: International Journal of Social Sciences 3, no. 2 (October 11, 2017): 205–11. http://dx.doi.org/10.20319/pijss.2017.32.

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Chin, Susan Tee Suan,, and Rosman Md Yusoff. "ROLE OF EMOTIONAL INTELLIGENCE IN ENHANCING CONTEXTUAL PERFORMANCE." PEOPLE: International Journal of Social Sciences 3, no. 2 (October 20, 2018): 2532–43. http://dx.doi.org/10.20319/pijss.2017.32.25322543.

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Dissertations / Theses on the topic "Contextual intelligence"

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Arara, Ahmed. "Towards contextual ontologies requirements and formalization." Lyon 1, 2005. http://www.theses.fr/2005LYO10027.

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Les ontologies de domaine sont prévues pour fournir une compréhension généralement partagée parmi plusieurs communautés d'utilisateur. Les ontologies comportent des concepts, des instances, des liens entre concepts, et des axiomes. Ces derniers sont employés pour modéliser explicitement les phénomènes du monde réel d'un domaine spécifique. En réalité, un ensemble d'applications d'un domaine spécifique emploie différentes ontologies. Par conséquent, les différentes représentations de la même entité du monde réel existent en raison de divers mécanismes abstraits, des points de vue, du niveau de détails, et d'intérêt de l'utilisateur. Dans les dernières décennies, la notion du contexte a été utilisée par l'Intelligence Artificielle (IA) et l'informatique en tant qu'élément pour abstraire et établir les modèles conceptuels, systèmes de représentation de la connaissance, et très récemment dans les applications contextuelles. Dans notre recherche, l'information contextuelle est prise en compte en adoptant la notion du contexte et en l'intégrant dans la description des éléments ontologiques (concepts, rôles, objets, attributs, etc. ). Notre objectif est d'exprimer les éléments ontologiques dépendants du contexte comme un ensemble de données avec des perspectives multiples en utilisant les logiques de description. Plus précisément, nous étudions une approche pour décrire les ontologies qui partagent l'entité du monde réel avec des représentations multiples. Notre recherche est focalisée sur deux secteurs : (i) les besoins des ontologies avec des représentations multiples et (ii) un formalisme pour exprimer les ontologies de domaine qui peuvent exister dans différents contextes. Cette recherche a été motivée par le fait que les représentations peuvent changer selon différents critères tels que le point de vue, la granularité d'information disponible, la classification des concepts, le temps, l'espace, etc. En fait, les repréeentations multiples des phénomènes du monde réel sont de plus en plus standardisés
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Gopalakrishnan, Arjun. "Probabilistic Analysis of Contracting Ebola Virus Using Contextual Intelligence." Thesis, University of North Texas, 2017. https://digital.library.unt.edu/ark:/67531/metadc984182/.

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The outbreak of the Ebola virus was declared a Public Health Emergency of International Concern by the World Health Organisation (WHO). Due to the complex nature of the outbreak, the Centers for Disease Control and Prevention (CDC) had created interim guidance for monitoring people potentially exposed to Ebola and for evaluating their intended travel and restricting the movements of carriers when needed. Tools to evaluate the risk of individuals and groups of individuals contracting the disease could mitigate the growing anxiety and fear. The goal is to understand and analyze the nature of risk an individual would face when he/she comes in contact with a carrier. This thesis presents a tool that makes use of contextual data intelligence to predict the risk factor of individuals who come in contact with the carrier.
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Koh, Yi Mien. "Contextual intelligence and chief executive strategic decision making in the NHS." Thesis, Cranfield University, 2012. http://dspace.lib.cranfield.ac.uk/handle/1826/10451.

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CEO competence and development is a continuing concern in the NHS. As a key feature of any CEO leadership role is responsibility for organisationally critical decisions, and there is an increasing recognition of the role context plays in effective leadership behaviour. This study examines the role of contextual intelligence in relation to PCT CEO decision making behaviour. To do this, the research addresses four questions: a) what does the literature say about CEO contextual intelligence? b) what factors do PCT CEOs say they take into account in different decision making contexts? c) what contextual factors do they actually take into account? and d) what impact do the contextual factors have on their decision making behaviour. A systematic literature review resulted in a model of CEO contextual intelligence for CEO decision making. Semi-structured interviews with 24 PCT CEOs in a NHS region about factors influencing their decisions on generic strategies, national policies, regional strategies and local plans revealed a hierarchy among contextual factors applying to different decision strata. Semi-structured interviews and analysis of CEO diaries two months later of the same focal decisions show the real critical factors to be:- national policies themselves, the Strategic Health Authority and the decision making process, for regional strategies; and Top Management Team and structure for local plans. Altogether, the research reveals that the PCT CEO’s decision making context is rationally bounded; the relevant contextual factors differed significantly from the literature derived model; the actual factors in practice differed from what were espoused; choice of factors vary depending on decision trigger strata which links to degrees of CEO autonomy; and macro level factors which were indicated as significant from the systematic review were in fact ignored in practice. A PCT CEO model of contextual intelligence is developed together with a two dimensional model of underlying structures guiding PCT CEO decision making behaviour. The findings have implications for governance structures in the NHS, CEO decision making and senior leader development in ii the NHS in the context of the 2012 Health and Social Care Act. Areas for further research in public sector, NHS and contextual intelligence are also identified.
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Mahari, Veronica. "Contextual intelligence for leading and managing curriculum change in primary schools." Thesis, University of Pretoria, 2021. http://hdl.handle.net/2263/80463.

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South Africa has gone through a myriad of curriculum changes to correct the imbalances brought about by apartheid education policies. The global changes in politics, economy, the green environment and advances in technology have made a huge impact on the effective implementation of curriculum change. Principals working in this dynamic environment need to study the internal and external context in which they are operating in order to adapt to the new situation. This study sought to examine school principals’ use of contextual intelligence in leading and managing curriculum change. The study is underpinned by the interpretivist worldview and a qualitative case study approach was followed in collecting data. The sample consisted of principals, deputy principals and heads of departments from six Tshwane East schools. The schools involved were three township schools and three former model C schools from Tshwane East. The schools were purposively selected to improve the credibility and transferability of the findings, and 30 participants were involved in the study. For triangulation purposes data were collected using semi-structured face-to-face and focus group interviews and document analysis. Data were analysed using inductive thematic analysis and the findings were analysed using a contextual intelligence leadership construct. The findings reveal that principals are aware of the contextual factors that influence curriculum implementation. However most principals are not making use of contextual intelligence to deal with the challenges in their contexts. The study recommends training for principals on how they can use contextual intelligence in leading and managing curriculum change. There is a clear need to involve all stakeholders in the formulation and implementation of curriculum change.
Thesis (PhD)--University of Pretoria, 2021.
pt2021
Education Management and Policy Studies
PhD
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Roberts, Camrin. "Exploring dominant logic's enablement between contextual leadership intelligence and diversification strategy." Diss., University of Pretoria, 2017. http://hdl.handle.net/2263/59760.

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Purpose - Diversification is a popular sought-after growth strategy for organisations in response to the dynamic and rapid changes of a VUCA economy. However, there has been limited exploration into the leadership required to ensure its success. This exploratory study looks at how dominant logic, through its mechanism of mental maps known as schemata and information filtering system, enables the dimensions of Contextual Leadership Intelligence, such as contextual awareness, 3D thinking and meta-competencies to enable a diversification strategy. Design methodology - Following the recommendations of Saunders and Lewis (Saunders & Lewis, 2012), a qualitative study was conducted collecting data through semi-structured interviews from 15 senior executives, with an average experience of 21 years in a senior management role, who had been involved in a diversification strategy. Findings - It was concluded, through the development of a de facto model that there is a relationship between dominant logic and contextual intelligence, in terms of the awareness given to operating within context and the process of filtering information to effectively operate within dynamic contexts. Through the awareness given to the mental maps of dominant logic and 3D thinking, learning and unlearning of bias occurs, providing a leader with the ability to act with contextual intelligence to enable a diversification strategy.
Mini Dissertation (MBA)--University of Pretoria, 2017.
pa2017
Gordon Institute of Business Science (GIBS)
MBA
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Ramoly, Nathan. "Contextual integration of heterogeneous data in an open and opportunistic smart environment : application to humanoid robots." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLL003/document.

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L'association de robots personnels et d’intelligences ambiantes est une nouvelle voie pour l’aide à domicile. Grâce aux appareils intelligents de l'environnement, les robots pourraient fournir un service de haute qualité. Cependant, des verrous existent pour la perception, la cognition et l’action.En effet, une telle association cause des problèmes de variétés, qualités et conflits, engendrant des données hétérogènes et incertaines. Cela complique la perception du contexte et la cognition, i.e. le raisonnement et la prise de décision. La connaissance du contexte est utilisée par le robot pour effectuer des actions. Cependant, il se peut qu’il échoue, à cause de changements de contexte ou par manque de connaissance. Ce qui annule ou retarde son plan. La littérature aborde ces sujets, mais n’offre aucune solution viable et complète. Face à ces verrous, nous avons proposé des contributions, autour à la fois du raisonnement et de l’apprentissage. Nous avons d’abord conçu un outil d'acquisition de contexte qui gère et modélise l’incertitude. Puis, nous avons proposé une technique de détection de situations anormales à partir de données incertaines. Ensuite, un planificateur dynamique, qui considère les changements de contexte, a été proposé. Enfin, nous avons développé une méthode d'apprentissage par renforcement et expérience pour éviter proactivement les échecs.Toutes nos contributions ont été implémentées et validées via simulation ou à l’aide d’un robot dans une plateforme d’espaces intelligents
Personal robots associated with ambient intelligence are an upcoming solution for domestic care. In fact, helped with devices dispatched in the environment, robots could provide a better care to users. However, such robots are encountering challenges of perception, cognition and action.In fact, such an association brings issues of variety, data quality and conflicts, leading to the heterogeneity and uncertainty of data. These are challenges for both perception, i.e. context acquisition, and cognition, i.e. reasoning and decision making. With the knowledge of the context, the robot can intervene through actions. However, it may encounter task failures due to a lack of knowledge or context changes. This causes the robot to cancel or delay its agenda. While the literature addresses those topics, it fails to provide complete solutions. In this thesis, we proposed contributions, exploring both reasoning and learning approaches, to cover the whole spectrum of problems. First, we designed novel context acquisition tool that supports and models uncertainty of data. Secondly, we proposed a cognition technique that detects anomalous situation over uncertain data and takes a decision in accordance. Then, we proposed a dynamic planner that takes into consideration the last context changes. Finally, we designed an experience-based reinforcement learning approach to proactively avoid failures.All our contributions were implemented and validated through simulations and/or with a small robot in a smart home platform
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Blomfield, Daniel. "Contextual intelligence : a leadership model for engineering and construction management companies in South Africa." Diss., University of Pretoria, 2015. http://hdl.handle.net/2263/52336.

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This research was undertaken to test an existing model of contextual intelligence in the engineering and construction industry of South Africa. It similarly attempted to determine the contributing elements within the defined categories of the contextual intelligence construct that include skills and abilities, types of leadership, intelligence and types of thinking. A qualitative exploratory research method was used whereby sixteen semi-structured, in-depth interviews were held with leaders in the engineering and construction sector of South Africa. A number of existing categories and elements of the contextual intelligence model were found to be relevant, albeit incomplete. A revised Contextual Intelligence Model was developed utilising both highly relevant and relevant elements within the four categories. New elements contributing towards the revised model included having the ability to listen, being collaborative, displaying authentic, participative, organisational and transformational leadership abilities, utilising system thinking and conscious thinking structures, and lastly utilising both emotional and technical intelligence.
Mini Dissertation (MBA)--University of Pretoria, 2015.
ms2016
Gordon Institute of Business Science (GIBS)
MBA
Unrestricted
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Kővári, Edit Mária. "Don't worry, be emotionally intelligent : hotel functional managers' trait emotional intelligence and its relation to task and contextual performance within organisational culture in Hungary." Thesis, University of Derby, 2016. http://hdl.handle.net/10545/614995.

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Ali, Mazin. "360? View Camera Based Visual Assistive Technology for Contextual Scene Information." Thesis, Rochester Institute of Technology, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10621991.

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In this research project, a system is proposed to aid the visually impaired by providing partial contextual information of the surroundings using 360° view camera combined with deep learning is proposed. The system uses a 360° view camera with a mobile device to capture surrounding scene information and provide contextual information to the user in the form of audio. The system could also be used for other applications such as logo detection which visually impaired users can use for shopping assistance.

The scene information from the spherical camera feed is classified by identifying objects that contain contextual information of the scene. That is achieved using convolutional neural networks (CNN) for classification by leveraging CNN transfer learning properties using the pre-trained VGG-19 network. There are two challenges related to this paper, a classification and a segmentation challenge. As an initial prototype, we have experimented with general classes such restaurants, coffee shops and street signs. We have achieved a 92.8% classification accuracy in this research project.

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Eaneff, Charles S. "The impact of contextual background fusion on perceived value and quality of unclassified terrorism intelligence." Thesis, Monterey, Calif. : Naval Postgraduate School, 2007. http://bosun.nps.edu/uhtbin/hyperion.exe/07Mar%5FEaneff.pdf.

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Thesis (M.A. in Security Studies (Homeland Security and Defense))--Naval Postgraduate School, March 2007.
Thesis Advisor(s): Richard Bergin. "March 2007." Includes bibliographical references (p. 125-132). Also available in print.
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Books on the topic "Contextual intelligence"

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Kutz, Matthew. Contextual Intelligence. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-44998-2.

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Market-driven thinking: Achieving contextual intelligence. Amsterdam: Elsevier Butterworth-Heinemann, 2005.

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service), SpringerLink (Online, ed. Contextual Computing: Models and Applications. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2011.

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Borzyh, Stanislav. Theory of Mind. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1088340.

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This book deals with the problem of human reason and thinking from a somewhat unexpected angle. Its main idea is that both are the product of evolution, and therefore they bear the imprint of their history, and they are mostly reduced to them, although they are not entirely limited to them. This means that they are by no means universal, on the contrary, they are conditioned by their very formation and the circumstances within which they developed and which literally created them as we know them. In practical terms, this suggests that they are aimed at solving the problems and the type that faced our species during its rather long formation, and they are not able to answer any other questions, no matter how much effort we put into it. Even what seems to us an exceptional attribute of modernity or rationality, such as science or politics, fits within the framework of what is available to us, as well as what we are able to formulate and articulate in principle. That is, our intelligence is purely animal and contextual, it never goes beyond the limits set for it, despite the fact that we see it differently. In this regard, questions of their definition, origin, history and current state are considered, and among other things, alternative options that are potentially possible in the field of intelligence, both on Earth and in general, are studied. The text consists of five chapters, a preface and an afterword, is provided with illustrative examples and is aimed at the widest possible adult readership, who likes to think and who is not afraid of debunking some of the ingrained myths that accompany our lives.
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Porzel, Robert. Contextual Computing. Springer, 2011.

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Marishane, Ramodikoe Nylon. Contextual Intelligence in School Leadership: Responding to the Dynamics of Change. BRILL, 2020.

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Marishane, Ramodikoe Nylon. Contextual Intelligence in School Leadership: Responding to the Dynamics of Change. BRILL, 2020.

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Realworld Reasoning Toward Scalable Uncertain Spatiotemporal Contextual And Causal Inference. Atlantis Press, 2011.

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Kutz, Matthew. Contextual Intelligence: How Thinking in 3D Can Help Resolve Complexity, Uncertainty and Ambiguity. Palgrave Macmillan, 2016.

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Kutz, Matthew. Contextual Intelligence: How Thinking in 3D Can Help Resolve Complexity, Uncertainty and Ambiguity. Palgrave Macmillan, 2018.

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Book chapters on the topic "Contextual intelligence"

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Kutz, Matthew. "Implementing Contextual Intelligence." In Contextual Intelligence, 121–27. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-44998-2_10.

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Kutz, Matthew. "What Is Contextual Intelligence?" In Contextual Intelligence, 9–20. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-44998-2_2.

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Kutz, Matthew. "Overcoming the Obstacles to Contextual Intelligence." In Contextual Intelligence, 139–48. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-44998-2_12.

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Kutz, Matthew. "Putting the Contextual Intelligence Model Together." In Contextual Intelligence, 31–51. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-44998-2_4.

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Kutz, Matthew. "Disruptors of 3D Thinking." In Contextual Intelligence, 131–38. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-44998-2_11.

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Kutz, Matthew. "Recommendations and Action Steps for Implementing Contextual Intelligence." In Contextual Intelligence, 149–56. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-44998-2_13.

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Kutz, Matthew. "Erratum to: 3D Thinking: A Different Orientation to Time." In Contextual Intelligence, E1. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-44998-2_14.

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Kutz, Matthew. "Using Contextual Intelligence at Work and in Life." In Contextual Intelligence, 21–29. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-44998-2_3.

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Kutz, Matthew. "Embracing Complexity." In Contextual Intelligence, 55–70. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-44998-2_5.

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Kutz, Matthew. "Reframing Experience." In Contextual Intelligence, 71–77. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-44998-2_6.

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Conference papers on the topic "Contextual intelligence"

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Shroff, Gautam, Lipika Dey, and Hiranmay Ghosh. "Enterprise Contextual Intelligence." In 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT). IEEE, 2014. http://dx.doi.org/10.1109/wi-iat.2014.99.

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Seabolt, Ed, Eser Kandogan, and Mary Roth. "Contextual Intelligence for Unified Data Governance." In SIGMOD/PODS '18: International Conference on Management of Data. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3211954.3211955.

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Liu, Ninghao, Donghwa Shin, and Xia Hu. "Contextual Outlier Interpretation." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/341.

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While outlier detection has been intensively studied in many applications, interpretation is becoming increasingly important to help people trust and evaluate the developed detection models through providing intrinsic reasons why the given outliers are identified. It is a nontrivial task for interpreting the abnormality of outliers due to the distinct characteristics of different detection models, complicated structures of data in certain applications, and imbalanced distribution of outliers and normal instances. In addition, contexts where outliers locate, as well as the relation between outliers and the contexts, are usually overlooked in existing interpretation frameworks. To tackle the issues, in this paper, we propose a Contextual Outlier INterpretation (COIN) framework to explain the abnormality of outliers spotted by detectors. The interpretability of an outlier is achieved through three aspects, i.e., outlierness score, attributes that contribute to the abnormality, and contextual description of its neighborhoods. Experimental results on various types of datasets demonstrate the flexibility and effectiveness of the proposed framework.
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Chen, Jim Q. "Contextual Binding and Intelligent Targeting." In 2016 IEEE/WIC/ACM International Conference on Web Intelligence (WI). IEEE, 2016. http://dx.doi.org/10.1109/wi.2016.0125.

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Liu, Qian, Bei Chen, Jiaqi Guo, Jian-Guang Lou, Bin Zhou, and Dongmei Zhang. "How Far are We from Effective Context Modeling? An Exploratory Study on Semantic Parsing in Context." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/495.

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Recently semantic parsing in context has received a considerable attention, which is challenging since there are complex contextual phenomena. Previous works verified their proposed methods in limited scenarios, which motivates us to conduct an exploratory study on context modeling methods under real-world semantic parsing in context. We present a grammar-based decoding semantic parser and adapt typical context modeling methods on top of it. We evaluate 13 context modeling methods on two large complex cross-domain datasets, and our best model achieves state-of-the-art performances on both datasets with significant improvements. Furthermore, we summarize the most frequent contextual phenomena, with a fine-grained analysis on representative models, which may shed light on potential research directions. Our code is available at https://github.com/microsoft/ContextualSP.
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Abdolmaleki, Abbas, Bob Price, Nuno Lau, Luis Paulo Reis, and Gerhard Neumann. "Contextual Covariance Matrix Adaptation Evolutionary Strategies." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/191.

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Many stochastic search algorithms are designed to optimize a fixed objective function to learn a task, i.e., if the objective function changes slightly, for example, due to a change in the situation or context of the task, relearning is required to adapt to the new context. For instance, if we want to learn a kicking movement for a soccer robot, we have to relearn the movement for different ball locations. Such relearning is undesired as it is highly inefficient and many applications require a fast adaptation to a new context/situation. Therefore, we investigate contextual stochastic search algorithms that can learn multiple, similar tasks simultaneously. Current contextual stochastic search methods are based on policy search algorithms and suffer from premature convergence and the need for parameter tuning. In this paper, we extend the well known CMA-ES algorithm to the contextual setting and illustrate its performance on several contextual tasks. Our new algorithm, called contextual CMA-ES, leverages from contextual learning while it preserves all the features of standard CMA-ES such as stability, avoidance of premature convergence, step size control and a minimal amount of parameter tuning.
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"Ontology Integration with Contextual Information." In International Conference on Agents and Artificial Intelligence. SCITEPRESS - Science and and Technology Publications, 2014. http://dx.doi.org/10.5220/0004820504850490.

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Rodrigues, Luiz, Armando M. Toda, Wilk Oliveira, Paula T. Palomino, and Seiji Isotani. "Just beat it: Exploring the influences of competition and task-related factors in gamified learning environments." In Simpósio Brasileiro de Informática na Educação. Sociedade Brasileira de Computação, 2020. http://dx.doi.org/10.5753/cbie.sbie.2020.461.

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Abstract:
Understanding how each game element in isolation affects learners' motivation and contextual factors' moderator effects is needed to improve gamified interventions. Thus, this paper explored the impact of one of the most used game elements - Competition - on motivation and whether task-related contextual factors (e.g., familiarity with the task's subject) moderate that impact. In a within-subject quasi-experimental design, graduate students from an Artificial Intelligence course created a reflexive intelligent agent for a console-based fight simulator in a non-gamified condition. Then, they improved their agents to compete against their peers agents (gamified condition). Based on motivation levels measured in both conditions, we found that Competition was positive for students and that task-related contextual factors influenced that effect. Therefore, suggesting i) Competition alone can be positive for motivation and ii) contextual moderators should be considered in defining gamified designs.
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Chichti, Fatma Turki, Abir Besbes, and Ibticem Benzammel. "The impact of contextual factors on business intelligence." In 2016 International Conference on Digital Economy (ICDEc). IEEE, 2016. http://dx.doi.org/10.1109/icdec.2016.7563148.

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Guo, Xueying, Xiaoxiao Wang, and Xin Liu. "AdaLinUCB: Opportunistic Learning for Contextual Bandits." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/336.

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In this paper, we propose and study opportunistic contextual bandits - a special case of contextual bandits where the exploration cost varies under different environmental conditions, such as network load or return variation in recommendations. When the exploration cost is low, so is the actual regret of pulling a sub-optimal arm (e.g., trying a suboptimal recommendation). Therefore, intuitively, we could explore more when the exploration cost is relatively low and exploit more when the exploration cost is relatively high. Inspired by this intuition, for opportunistic contextual bandits with Linear payoffs, we propose an Adaptive Upper-Confidence-Bound algorithm (AdaLinUCB) to adaptively balance the exploration-exploitation trade-off for opportunistic learning. We prove that AdaLinUCB achieves O((log T)^2) problem-dependent regret upper bound, which has a smaller coefficient than that of the traditional LinUCB algorithm. Moreover, based on both synthetic and real-world dataset, we show that AdaLinUCB significantly outperforms other contextual bandit algorithms, under large exploration cost fluctuations.
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