Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Teodora Sandra Buda"'
Publikováno v:
PLoS ONE, Vol 18, Iss 4, p e0284104 (2023)
A plethora of past studies have highlighted a negative association between phone use and well-being. Recent studies claimed that there is a lack of strong evidence on the deleterious effects of smartphones on our health, and that previous systematic
Externí odkaz:
https://doaj.org/article/a654399a9dfd4ee8a4352a01d54cfc37
Autor:
Teodora Sandra Buda, João Guerreiro, Jesus Omana Iglesias, Carlos Castillo, Oliver Smith, Aleksandar Matic
Publikováno v:
Frontiers in Digital Health, Vol 4 (2022)
Digital mental health applications promise scalable and cost-effective solutions to mitigate the gap between the demand and supply of mental healthcare services. However, very little attention is paid on differential impact and potential discriminati
Externí odkaz:
https://doaj.org/article/3fe45a0ebbc5411f9faef6cbc6a1533e
Publikováno v:
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies. 5:1-19
Enabling smartphones to understand our emotional well-being provides the potential to create personalised applications and highly responsive interfaces. However, this is by no means a trivial task - subjectivity in reporting emotions impacts the reli
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::72b674d26b20d9de59caf03095a64792
https://doi.org/10.1145/3448095
https://doi.org/10.1145/3448095
Autor:
Michael G. Madden, C. Lane, Marc Mellotte, Brett Drury, Teodora Sandra Buda, Ihsan Ullah, Haytham Assem
Publikováno v:
Information Management and Big Data ISBN: 9783030762278
SIMBig
SIMBig
Posting information on social media platforms is a popular activity through which personal and confidential information can leak into the public domain. Consequently, social media can contain information that provides an indication that an organizati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b1802798458733c0bf15f06505b263e3
https://doi.org/10.1007/978-3-030-76228-5_23
https://doi.org/10.1007/978-3-030-76228-5_23
Publikováno v:
ACM Transactions on Intelligent Systems and Technology. 8:1-30
During the past few years, the analysis of data generated from Location-Based Social Networks (LBSNs) have aided in the identification of urban patterns, understanding activity behaviours in urban areas, as well as producing novel recommender systems
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::779afc3bd635dfe663548f933e4b3957
https://doi.org/10.1145/3086636
https://doi.org/10.1145/3086636
Publikováno v:
Information Systems. 67:83-99
Generating synthetic data is useful in multiple application areas (e.g., database testing, software testing). Nevertheless, existing synthetic data generators are either limited to generating data that only respect the database schema constraints, or
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0e41edf0ffa47f3956b02b49a309926b
https://doi.org/10.1016/j.is.2017.03.001
https://doi.org/10.1016/j.is.2017.03.001
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783030109967
ECML/PKDD (3)
ECML/PKDD (3)
Network Demand Prediction is of great importance to network planning and dynamically allocating network resources based on the predicted demand, this can be very challenging as it is affected by many complex factors, including spatial dependencies, t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::113879a8bd64ac7264d1585516f22099
https://doi.org/10.1007/978-3-030-10997-4_14
https://doi.org/10.1007/978-3-030-10997-4_14
Autor:
Carlos Alzate, Anna Monreale, Haytham Assem, Albert Bifet, Teodora Sandra Buda, Bora Caglayan, Brett Drury, Eva García-Martín, Ricard Gavaldà, Irena Koprinska, Stefan Kramer, Niklas Lavesson, Michael Madden, Ian Molloy, Maria-Irina Nicolae, Mathieu Sinn
This book constitutes revised selected papers from the workshops Nemesis, UrbReas, SoGood, IWAISe, and Green Data Mining, held at the 18th European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018, in Dublin, Irelan
Publikováno v:
Personal and Ubiquitous Computing
The future Internet is expected to connect billions of people, things and services having the potential to deliver a new set of applications by deriving new insights from the data generated from these diverse data sources. This highly interconnected
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a2a70c56512c316bd9148336d3ee1c83
https://doi.org/10.1007/s00779-016-0963-3
https://doi.org/10.1007/s00779-016-0963-3