Author  |
Title |
Year |
Publication |
Volume |
Pages |
| Canessa, E, Chaigneau, S.E, Moreno, S. |
Describing and understanding the time course of the Property Listing Task |
2023 |
Cognitive Processing |
Early Access |
|
| Canessa, E.; Chaigneau, S.E.; Moreno, S. |
Using agreement probability to study differences in types of concepts and conceptualizers |
2022 |
Behavior Research Methods |
Early Access |
|
| Canessa, E.; Chaigneau, S.E.; Moreno, S. |
Language processing differences between blind and sighted individuals and the abstract versus concrete concept difference |
2021 |
Cognitive Science |
45 |
e13044 |
| Canessa, E.; Chaigneau, S.E.; Moreno, S.; Lagos, R. |
CPNCoverageAnalysis: An R package for parameter estimation in conceptual properties norming studies |
2023 |
Behavior Research Methods |
55 |
554–569 |
| Canessa, E.; Chaigneau, S.E.; Moreno, S.; Lagos, R. |
Informational content of cosine and other similarities calculated from high-dimensional Conceptual Property Norm data |
2020 |
Cognitive Processing |
21 |
601-614 |
| Heredia, C.; Moreno, S.; Yushimito, W. |
ODMeans: An R package for global and local cluster detection for Origin–Destination GPS data |
2024 |
SoftwareX |
26 |
101732 |
| Heredia, C.; Moreno, S.; Yushimito, W.F. |
Characterization of Mobility Patterns with a Hierarchical Clustering of Origin-Destination GPS Taxi Data |
2022 |
IEEE Transactions on Intelligent Transportation Systems |
23 |
12700-12710 |
| Hughes, S.; Moreno, S.; Yushimito, W.F.; Huerta-Canepa, G. |
Evaluation of machine learning methodologies to predict stop delivery times from GPS data |
2019 |
Transportation Research Part C-Emerging Technologies |
109 |
289-304 |
| Lagos, F.; Moreno, S.; Yushimito, W.F.; Brstilo, T. |
Urban Origin–Destination Travel Time Estimation Using K-Nearest-Neighbor-Based Methods |
2024 |
Mathematics |
12 |
1255 |
| Moreno, S.; Bórquez-Paredes, D.; Martínez, V. |
Analysis of the Characteristics and Speed of Spread of the 'FUNA' on Twitter |
2023 |
Mathematics |
11 |
1749 |
| Moreno, S.; Neville, J.; Kirshner, S. |
Tied Kronecker Product Graph Models to Capture Variance in Network Populations |
2018 |
Acm Transactions On Knowledge Discovery From Data |
12 |
40 pp |
| Moreno, S.; Pereira, J.; Yushimito, W. |
A hybrid K-means and integer programming method for commercial territory design: a case study in meat distribution |
2020 |
Annals Of Operations Research |
286 |
87-117 |
| Moreno, S.; Pfeiffer, J.J.; Neville, J. |
Scalable and exact sampling method for probabilistic generative graph models |
2018 |
Data Mining And Knowledge Discovery |
32 |
1561-1596 |
| Opazo, D.; Moreno, S.; Alvarez-Miranda, E.; Pereira, J. |
Analysis of First-Year University Student Dropout through Machine Learning Models: A Comparison between Universities |
2021 |
Mathematics |
20 |
2599 |
| Poirrier, M., Moreno, S., Huerta-Canepa, G. |
Robust h-index |
2021 |
Scientometrics |
126 |
1969-1981 |
| Ramos, D.; Moreno, S.; Canessa, E.; Chaigneau, S.E.; Marchant, N. |
AC-PLT: An algorithm for computer-assisted coding of semantic property listing data |
2023 |
Behavior Research Methods |
Early Access |
|
| Salas, R.; Allende, H.; Moreno, S.; Saavedra, C. |
Flexible Architecture of Self Organizing Maps for changing environments |
2005 |
Lecture Notes in Computer Sciences |
3773 |
642-653 |
| Wiener, M.; Moreno, S.; Jafvert, C.; Nies, L. |
Time Series Analysis of Water Use and Indirect Reuse within a HUC-4 Basin (Wabash) over a Nine Year Period |
2020 |
Science of the Total Environment |
738 |
140221 |
| Yushimito, W.F.; Moreno, S.; Miranda, D. |
The Potential of Battery Electric Taxis in Santiago de Chile |
2023 |
Sustainability |
15 |
8689 |
