Research areas:
- Citizen Science
- Deep Learning
- Machine Learning
- Probabilistic Graphical Models
- Probabilistic Learning
- Case-Based Reasoning
Impact areas:
- Smart Cities
- Healthcare
SDGs:
- GOAL 13: Climate Action
- SDGs: General
- GOAL 11: Sustainable Cities and Communities
- GOAL 06: Clean Water and Sanitation
- GOAL 03: Good Health and Well-being
In Press
Carlo Bono,
Oguz Mulayim,
& Barbara Pernici
(In Press).
Learning early detection of emergencies from word usage patterns on social media.
Proceedings of ITDRR 2022, Kristiansand, Norway
.
[BibTeX]
[PDF]
2023
Carlo Bono,
Oguz Mulayim,
Cinzia Cappiello,
Mark James Carman,
Jesus Cerquides,
Jose Luis Fernandez Marquez,
Maria Rosa Mondardini,
Edoardo Ramalli,
& Barbara Pernici
(2023).
A Citizen Science Approach for Analyzing Social Media With Crowdsourcing.
IEEE Access, 11, 15329-15347.
https://doi.org/10.1109/ACCESS.2023.3243791.
[BibTeX]
[PDF]
2022
Fabio Murgese,
Gerard Alcaina,
Oguz Mulayim,
Jesus Cerquides,
& Jose Luis Fernandez Marquez
(2022).
Automatic Outdoor Image Geolocation with Focal Modulation Networks.
Atia Cortés, Francisco Grimaldo, & Tommaso Flaminio (Eds.),
Frontiers in Artificial Intelligence and Applications (pp 279--288).
IOS Press.
https://doi.org/10.3233/FAIA220349.
[BibTeX]
[PDF]
Carlo Bono,
Barbara Pernici,
Jose Luis Fernandez Marquez,
Amudha Ravi Shankar,
Oguz Mulayim,
& Edoardo Nemni
(2022).
TriggerCit: Early Flood Alerting using Twitter and Geolocation - a comparison with alternative sources.
Rob Grace, & Hossein Baharmand (Eds.),
ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management
(pp. 674--686).
[BibTeX]
[PDF]
2021
Jesus Cerquides,
Oguz Mulayim,
Jeronimo Hernandez-Gonzalez,
Amudha Ravi Shankar,
& Jose Luis Fernandez Marquez
(2021).
A Conceptual Probabilistic Framework for Annotation Aggregation of Citizen Science Data.
Mathematics, 9.
https://doi.org/10.3390/math9080875.
[BibTeX]
[PDF]
2020
Oguz Mulayim,
& Josep Lluis Arcos
(2020).
Fast anytime retrieval with confidence in large-scale temporal case bases.
Knowledge-Based Systems, 206, 106374.
https://doi.org/10.1016/j.knosys.2020.106374.
[BibTeX]
[PDF]
2019
David Sanchez-Pinsach,
Oguz Mulayim,
Jennifer Grau-Sánchez,
Emma Segura,
Berta Juan-Corbella,
Josep Lluis Arcos,
Jesus Cerquides,
Monique Messaggi-Sartor,
Esther Duarte,
& Antoni Rodriguez-Fornells
(2019).
Design of an AI Platform to Support Home-Based Self-Training Music Interventions for Chronic Stroke Patients.
Jordi Sabater-Mir, Vicenç Torra, Isabel Aguilo, & Manuel González-Hidalgo (Eds.),
Frontiers in Artificial Intelligence and Applications (pp 170--175).
IOS Press.
https://doi.org/10.3233/FAIA190120.
[BibTeX]
2018
Oguz Mulayim,
& Josep Lluis Arcos
(2018).
Perks of Being Lazy: Boosting Retrieval Performance.
Twenty-Sixth International Conference on Case-Based Reasoning
.
https://doi.org/10.1007/978-3-030-01081-2_21.
[BibTeX]
2011
Josep Lluis Arcos,
Oguz Mulayim,
& David Leake
(2011).
Using introspective reasoning to improve CBR system performance.
M. T. Cox, & A. Raja (Eds.),
Metareasoning: Thinking about Thinking (pp 167-182).
MIT Press.
https://doi.org/10.7551/mitpress/9780262014809.003.0011.
[BibTeX]
2010
Oguz Mulayim,
& Josep Lluis Arcos
(2010).
Predicting Dubiosity in CBR Systems.
Expert UPDATE, 10, 1-8.
https://doi.org/http://www.expertupdate.org/papers/10-2/1.pdf.
[BibTeX]
[PDF]
2008
Oguz Mulayim,
& Josep Lluis Arcos
(2008).
Understanding Dubious Future Problems.
D Althoff, R Bergmann, M Minor, & A Hanft (Eds.),
Advances in Case-Based Reasoning: 9th European Conference, ECCBR 2008. Lecture Notes in Artificial Intelligence
(pp. 385-399).
Springer Verlag.
https://doi.org/10.1007/978-3-540-85502-6_26.
[BibTeX]
[PDF]
Josep Lluis Arcos,
Oguz Mulayim,
& David Leake
(2008).
Using Introspective Reasoning to Improve CBR System Performance.
Michael T. Cox, & Anita Raja (Eds.),
AAAI Metareasoning Workshop
(pp. 21-28).
AAAI Press.
[BibTeX]
[PDF]
2007
Oguz Mulayim,
& Josep Lluis Arcos
(2007).
Exploring Dubious Future Problems.
Miltos Petridis (Eds.),
Twelfth UK Workshop on Case-Based Reasoning
(pp. 52-63).
CMS Press, University of Greenwich.
[BibTeX]
[PDF]