Browsing by Author "Şensoy, Murat"
Now showing items 41-60 of 61
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Reputation mechanism for e-commerce in virtual reality environments
Fang, H.; Zhang, J.; Şensoy, Murat; Magnenat-Thalmann, N. (Elsevier, 2014)The interest in 3D technology and virtual reality (VR) is growing both from academia and industry, promoting the quick development of virtual marketplaces (VMs) (i.e. e-commerce systems in VR environments). VMs have inherited ... -
Risk-calibrated evidential classifiers
Saleki, Maryam (2020-01-17)In some applications, intelligent agents rely on classifiers in order to make their decisions and accuracy of their predictions may play a significant role in performing their tasks successfully. Although deep neural ... -
A semantic policy framework for internet of things
Göynügür, Emre (2018-10-31)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 environments. However, ... -
Semantic reasoning with uncertain information from unreliable sources
Şensoy, Murat; Kaplan, L.; de Mel, G. (Springer International Publishing, 2016)Intelligent software agents may significantly benefit from semantic reasoning. However, existing semantic reasoners are based on Description Logics, which cannot handle vague, incomplete, and unreliable knowledge. In this ... -
SHACL constraints with inference rules
Pareti, P.; Konstantinidis, G.; Norman, T. J.; Şensoy, Murat (Springer Nature, 2019)The Shapes Constraint Language (SHACL) has been recently introduced as a W3C recommendation to define constraints that can be validated against RDF graphs. Interactions of SHACL with other Semantic Web technologies, such ... -
SOBE: Source behavior estimation for subjective opinions In multiagent systems
Şensoy, Murat; Kaplan, L.; Mel, G. de; Gunes, Taha Doğan (International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), 2016)In cooperative or hostile environments, agents communicate their subjective opinions about various phenomenon. However, sources of these opinions may not always be competent and honest but more likely erroneous or even ... -
Source behavior discovery for fusion of subjective opinions
Şensoy, Murat; Kaplan, L.; Mel, G. de; Gunes, Taha (IEEE, 2016)Information is at the center of decision making in many systems and use-cases. In cooperative or hostile environments, agents communicate their subjective opinions about various phenomenon. However, sources of these opinions ... -
Spoofing and anti-spoofing techniques for text-independent speaker verification systems
Khodabakhsh, Ali (2015-10)There has been substantial progress in the speaker verification field in recent years. I-vector based approach in particular received significant attention due to its high performance. Improvements in the verification ... -
Stage: stereotypical trust assessment through graph extraction
Şensoy, Murat; Yilmaz, B.; Norman, T. J. (Wiley, 2016-02)Bootstrapping trust assessment where there is little or no evidence regarding a subject is a significant challenge for existing trust and reputation systems. When direct or indirect evidence is absent, existing approaches ... -
Strategies for truth discovery under resource constraints
Etuk, A.; Norman, T. J.; Oren, N.; Şensoy, Murat (ACM, 2015)We present a decision-theoretic approach for sampling information sources in resource-constrained environments, where there is uncertainty regarding source trustworthiness. We exploit diversity among sources to stratify ... -
Subjective bayesian networks and human-in-the-loop situational understanding
Braines, D.; Thomas, A.; Kaplan, L.; Şensoy, Murat; Bakdash, J. Z.; Ivanovska, M.; Preece, A.; Cerutti, F. (Springer, 2018-03-21)In this paper we present a methodology to exploit human-machine coalitions for situational understanding. Situational understanding refers to the ability to relate relevant information and form logical conclusions, as well ... -
TIDY: A trust-based approach to information fusion through diversity
Etuk, A.; Norman, T. J.; Şensoy, Murat; Bisdikian, C.; Srivatsa, M. (IEEE, 2013)Trust and reputation are significant components in open dynamic systems for making informed and reliable decisions. State-of-the-art information fusion models that exploit these mechanisms generally rely on reports from ... -
Tractable policy management framework for IoT
Goynugur, Emre; De Mel, G.; Şensoy, Murat; Calo, S. (SPIE, 2017)Due to the advancement in the technology, hype of connected devices (hence forth referred to as IoT) in support of automating the functionality of many domains, be it intelligent manufacturing or smart homes, have become ... -
TRIBE: Trust revision for information based on evidence
Şensoy, Murat; de Mel, G.; Kaplan, L.; Pham, T.; Norman, T. J. (IEEE, 2013)In recent years, the number of information sources available to support decision-making has increased dramatically. However, more information sources do not always mean higher precision in the fused information. This is ... -
Trust estimation and fusion of uncertain information by exploiting consistency
Kaplan, L.; Şensoy, Murat; de Mel, G. (IEEE, 2014)Agents may cooperate by communicating their opinions about various phenomena. These opinions are then fused by agents and used for informed decision-making. However, fusing opinions from diverse sources is not trivial - ... -
Trust estimation of sources over correlated propositions
Kaplan, L.; Şensoy, Murat (IEEE, 2018-09-05)This work analyzes the impact of correlated propositions when estimating the reporting behavior of information sources. These behavior estimates are critical for fusion, and traditional methods assume the propositions are ... -
Trust-based fusion of classifiers for static code analysis
Yüksel, U.; Sözer, Hasan; Şensoy, Murat (IEEE, 2014)Static code analysis tools automatically generate alerts for potential software faults that can lead to failures. However, developers are usually exposed to a large number of alerts. Moreover, some of these alerts are ... -
Uncertainty-aware deep classifiers using generative models
Şensoy, Murat; Kaplan, L.; Cerutti, F.; Saleki, Maryam (Association for the Advancement of Artificial Intelligence, 2020)Deep neural networks are often ignorant about what they do not know and overconfident when they make uninformed predictions. Some recent approaches quantify classification uncertainty directly by training the model to ... -
Uncertainty-aware situational understanding
Tomsett, R.; Kaplan, L.; Cerutti, F.; Sullivan, P.; Vente, D.; Vilamala, M. R.; Kimmig, A.; Preece, A.; Şensoy, Murat (SPIE, 2019)Situational understanding is impossible without causal reasoning and reasoning under and about uncertainty, i.e. prob-abilistic reasoning and reasoning about the confidence in the uncertainty assessment. We therefore ... -
Using eigenvoices and nearest-neighbours in HMM-based cross-lingual speaker adaptation with limited data
Sarfjoo, Seyyed Saeed (2017-08)Thesis abstract: Cross-lingual speaker adaptation for speech synthesis has many applications, such as use in speech-to-speech translation systems. Here, we focus on cross-lingual adaptation for statistical speech synthesis ...
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