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X
Layfield, Colin
22  Ergebnisse:
Personensuche X
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1

Explainability and Interpretability in Decision Trees and A..:

, In: 2023 8th International Conference on Computational Intelligence and Applications (ICCIA),
Layfield, Colin ; Neri, Filippo - p. 42-46 , 2023
Link: https://doi.org/10.1109/..
 
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2

From Event Tracking to Event Modelling: Understanding as a ..:

, In: Communications in Computer and Information Science; Knowledge Discovery, Knowledge Engineering and Knowledge Management,
Mamo, Nicholas ; Layfield, Colin ; Azzopardi, Joel - p. 21-36 , 2023
Link: https://doi.org/10.1007/..
 
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3

The myth of reproducibility: A review of event tracking eva..:

Mamo, Nicholas ; Azzopardi, Joel ; Layfield, Colin
Frontiers in Big Data.  6 (2023)  - p. , 2023
Link: https://doi.org/10.3389/..
 
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4

An Automatic Participant Detection Framework for Event Trac..:

Mamo, Nicholas ; Azzopardi, Joel ; Layfield, Colin
Algorithms.  14 (2021)  3 - p. 92 , 2021
Link: https://doi.org/10.3390/..
 
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5

ELD: Event TimeLine Detection -- A Participant-Based Approa..:

, In: Proceedings of the 30th ACM Conference on Hypertext and Social Media,
Mamo, Nicholas ; Azzopardi, Joel ; Layfield, Colin - p. 267-268 , 2019
Link: https://dl.acm.org/doi/1..
 
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6

FAIRness at University of Novi Sad - Discoverability of PhD..:

Ivanović, Dragan ; Ivanović, Lidija ; Layfield, Colin
Procedia Computer Science.  146 (2019)  - p. 3-10 , 2019
Link: https://doi.org/10.1016/..
 
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7

The myth of reproducibility: A review of event tracking eva..:

Mamo, Nicholas ; Azzopardi, Joel ; Layfield, Colin
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10113524/.  , 2023
Link: http://www.ncbi.nlm.nih...
 
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8

The myth of reproducibility : a review of event tracking ev..:

Mamo, Nicholas ; Azzopardi, Joel ; Layfield, Colin
Mamo, N., Azzopardi, J. & Layfield, C. (2023). The myth of reproducibility: A review of event tracking evaluations on Twitter. Frontiers in Big Data, 6, 1067335..  , 2023
Link: https://www.um.edu.mt/li..
 
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9

An automatic participant detection framework for event trac..:

Mamo, Nicholas ; Azzopardi, Joel ; Layfield, Colin
Mamo, N., Azzopardi, J., & Layfield, C. (2021). An automatic participant detection framework for event tracking on Twitter. Algorithms, 14(3), 92..  , 2021
Link: https://www.um.edu.mt/li..
 
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10

"To trust a LIAR": does machine learning really classify fi..:

Mifsud, Mark ; Layfield, Colin ; Azzopardi, Joel..
Mifsud, M., Layfield, C., Azzopardi, J., & Abela, J. (2021). "To trust a LIAR": Does Machine Learning Really Classify Fine-grained, Fake News Statements?. In Proceedings of the 2nd Workshop on Online Misinformation-and Harm-Aware Recommender Systems (OHARS 2021), Amsterdam, Netherlands..  , 2021
Link: https://www.um.edu.mt/li..
 
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11

Vehicular traffic flow intensity detection and prediction t..:

Saliba, Maurice ; Abela, Charlie ; Layfield, Colin.
Saliba, M., Abela, C., & Layfield, C. (2018). Vehicular traffic flow intensity detection and prediction through mobile data usage. Proceedings for the 26th AIAI Irish Conference on Artificial Intelligence and Cognitive Science (AICS), Trinity College Dublin, 66-77..  , 2018
Link: https://www.um.edu.mt/li..
 
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12

Tablets report:

Dingli, Alexiei ; Garg, Lalit ; Layfield, Colin.
Dingli, A., Garg, L., Layfield, C., & Montebello, M. (2015). Tablets report. Msida.  , 2015
Link: https://www.um.edu.mt/li..
 
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13

The myth of reproducibility: A review of event tracking eva..:

Nicholas Mamo ; Joel Azzopardi ; Colin Layfield
https://www.frontiersin.org/articles/10.3389/fdata.2023.1067335/full.  , 2023
Link: https://doi.org/10.3389/..
 
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14

An Automatic Participant Detection Framework for Event Trac..:

Nicholas Mamo ; Joel Azzopardi ; Colin Layfield
https://www.mdpi.com/1999-4893/14/3/92.  , 2021
Link: https://doi.org/10.3390/..
 
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15

An Automatic Participant Detection Framework for Event Trac..:

Nicholas Mamo ; Joel Azzopardi ; Colin Layfield
https://dx.doi.org/10.3390/a14030092.  , 2021
Link: https://doi.org/10.3390/..
 
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