Browsing Computer Science by OzU Authors "Şensoy, Murat"
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A 2020 perspective on “A generalized stereotype learning approach and its instantiation in trust modeling”
Fang, H.; Zhang, J.; Şensoy, Murat (Elsevier, 2020-03)Owing to the rapid increase of user data and development of machine learning techniques, user modeling has been explored in depth and exploited by both academia and industry. It has prominent impacts in e-commercerelated ... -
Agent-based semantic collaborative search
Şensoy, Murat (Executive Committee, Taiwan Academic Network, Ministry of Education, 2013)Next generation of the Web builds upon technologies such as Semantic Web and Intelligent Software Agents. These technologies aim at knowledge representation that allows both humans and software agents to understand and ... -
Agilely assigning sensing assets to mission tasks in a coalition context
Preece, A.; Norman, T.; de Mel, G.; Pizzocaro, D.; Şensoy, Murat; Pham, T. (IEEE, 2013)When managing intelligence, surveillance, and reconnaissance (ISR) operations in a coalition context, assigning available sensing assets to mission tasks can be challenging. The authors' approach to ISR asset assignment ... -
Campaign participation prediction with deep learning
Ayvaz, Demet; Aydoğan, Reyhan; Akçura, Munir Tolga; Şensoy, Murat (Elsevier, 2021-08)Increasingly, on-demand nature of customer interactions put pressure on companies to build real-time campaign management systems. Instead of having managers to decide on the campaign rules, such as, when, how and whom to ... -
Combining semantic web and IoT to reason with health and safety policies
Göynügür, Emre; Şensoy, Murat; Mel, G. de (IEEE, 2018-01-12)Monitoring and following health and safety regulations are especially important - but made difficult - in hazardous work environments such as underground mines to prevent work place accidents and illnesses. Even though ... -
Cooperation and trust in the presence of bias
Şensoy, Murat (2014)Stereotypes may influence the attitudes that individuals have towards others. Stereotypes, therefore, represent biases toward and against others. In this paper, we formalise stereotypical bias within trust evaluations. ... -
Discovering frequent patterns to bootstrap trust
Şensoy, Murat; Yilmaz, B.; Norman, T. J. (Springer International Publishing, 2013)When a new agent enters to an open multiagent system, bootstrapping its trust becomes a challenge because of the lack of any direct or reputational evidence. To get around this problem, existing approaches assume the same ... -
Enabling smart environments through scalable policy reasoning and Internet of Things
Göynügür, Emre; Şensoy, Murat; de Mel, G. (Wiley, 2019-04)In this paper, we discuss how to combine ontology-based policy reasoning mechanisms with in-use Internet of Things applications to customize and automate device behaviors. We discuss how the policy framework can be extended ... -
Evidential deep learning to quantify classification uncertainty
Şensoy, Murat; Kaplan, L.; Kandemir, M. (Neural Information Processing Systems Foundation, 2018)Deterministic neural nets have been shown to learn effective predictors on a wide range of machine learning problems. However, as the standard approach is to train the network to minimize a prediction loss, the resultant ... -
FUSE-BEE: Fusion of subjective opinions through behavior estimation
Şensoy, Murat; Kaplan, L.; Ayci, Gönül; de Mel, G. (IEEE, 2015)Information is critical in almost all decision making processes. Therefore, it is important to get the right information at the right time from the right sources. However, information sources may behave differently while ... -
A generalized stereotype learning approach and its instantiation in trust modeling
Fang, H.; Zhang, J.; Şensoy, Murat (Elsevier, 2018-08)Owing to the lack of historical data regarding an entity in online communities, a user may rely on stereotyping to estimate its behavior based on historical data about others. However, these stereotypes cannot accurately ... -
Goal directed policy conflict detection and prioritisation: an empirical evaluation
Aphale, M. S.; Norman, T. J.; Şensoy, Murat (Springer Science+Business Media, 2014)We address the problem of developing effective automated reasoning support for the detection and resolution of conflicts between plans and policies (or norms). How automated reasoning mechanisms can effectively support ... -
Handling epistemic and aleatory uncertainties in probabilistic circuits
Cerutti, F.; Kaplan, L. M.; Kimmig, A.; Şensoy, Murat (Springer, 2022-04)When collaborating with an AI system, we need to assess when to trust its recommendations. If we mistakenly trust it in regions where it is likely to err, catastrophic failures may occur, hence the need for Bayesian ... -
How to trust a few among many
Etuk, A.; Norman, T. J.; Şensoy, Murat; Srivatsa, M. (Springer International Publishing, 2017)The presence of numerous and disparate information sources available to support decision-making calls for efficient methods of harnessing their potential. Information sources may be unreliable, and misleading reports can ... -
A hybrid reasoning mechanism for effective sensor selection for tasks
de Mel, G.; Şensoy, Murat; Vasconcelos, W.; Norman, T. J. (Elsevier, 2013-02)In this paper, we present Ontological Logic Programming (OLP), a novel approach that combines logic programming with ontological reasoning. OLP enables the use of ontological terms (i.e., individuals, classes and properties) ... -
Inference management, trust and obfuscation principles for quality of information in emerging pervasive environments
Bisdikian, C.; Gibson, C.; Chakraborty, S.; Srivastava, M. B.; Şensoy, Murat; Norman, T. J. (Elsevier, 2014-04)The emergence of large scale, distributed, sensor-enabled, machine-to-machine pervasive applications necessitates engaging with providers of information on demand to collect the information, of varying quality levels, to ... -
Interest-based negotiation for policy-regulated asset sharing
Parizas, C.; de Mel, G.; Preece, A. D.; Şensoy, Murat; Calo, S. B.; Pham, T. (Springer Nature, 2016)Resources sharing is an important but complex problem to be solved. The problem is exacerbated in a coalition context due to policy constraints, that reflect concerns regarding security, privacy and performance to name a ... -
Interpretability of deep learning models: a survey of results
Chakraborty, S.; Tomsett, R.; Raghavendra, R.; Harborne, D.; Alzantot, M.; Cerutti, F.; Srivastava, M.; Preece, A.; Julier, S.; Rao, R. M.; Kelley, T. D.; Braines, D.; Şensoy, Murat; Willis, C. J.; Gurram, P. (IEEE, 2018-06-26)Deep neural networks have achieved near-human accuracy levels in various types of classification and prediction tasks including images, text, speech, and video data. However, the networks continue to be treated mostly as ... -
A knowledge driven policy framework for internet of things
Goynugur, Emre; De Mel, G.; Şensoy, Murat; Talamadupula, K.; Calo, S. (ScitePress, 2017)With the proliferation of technology, connected and interconnected devices (henceforth referred to as IoT) are fast becoming a viable option to automate the day-to-day interactions of users with their environment—be it ...
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