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ORCIDReza Akbarinia
- > Home > Persons > Reza Akbarinia
Publications
- 2023
[j26]Tanmoy Mondal
, Reza Akbarinia, Florent Masseglia:
kNN matrix profile for knowledge discovery from time series. Data Min. Knowl. Discov. 37(3): 1055-1089 (2023)- [j25]Lamia Djebour, Reza Akbarinia, Florent Masseglia:
Variable-Size Segmentation for Time Series Representation. Trans. Large Scale Data Knowl. Centered Syst. 53: 34-65 (2023) - [j24]Reza Akbarinia, Christophe Botella, Alexis Joly, Florent Masseglia, Marta Mattoso, Eduardo S. Ogasawara, Daniel de Oliveira, Esther Pacitti, Fábio Porto, Christophe Pradal, Dennis E. Shasha, Patrick Valduriez:
Life Science Workflow Services (LifeSWS): Motivations and Architecture. Trans. Large Scale Data Knowl. Centered Syst. 55: 1-24 (2023) - [i4]Rebecca Salles, Janio Lima, Rafaelli Coutinho, Esther Pacitti, Florent Masseglia, Reza Akbarinia, Chao Chen, Jonathan M. Garibaldi, Fábio Porto, Eduardo S. Ogasawara:
SoftED: Metrics for Soft Evaluation of Time Series Event Detection. CoRR abs/2304.00439 (2023) - 2022
- [c45]Lamia Djebour, Reza Akbarinia, Florent Masseglia:
Parallel Techniques for Variable Size Segmentation of Time Series Datasets. ADBIS 2022: 148-162 - [c44]Lamia Djebour, Reza Akbarinia, Florent Masseglia:
Variable size segmentation for efficient representation and querying of non-uniform time series datasets. SAC 2022: 395-402 - 2021
- [j23]Oleksandra Levchenko, Boyan Kolev, Djamel Edine Yagoubi, Reza Akbarinia, Florent Masseglia, Themis Palpanas, Dennis E. Shasha, Patrick Valduriez:
BestNeighbor: efficient evaluation of kNN queries on large time series databases. Knowl. Inf. Syst. 63(2): 349-378 (2021) - [j22]Heraldo Borges, Reza Akbarinia, Florent Masseglia:
Anomaly Detection in Time Series. Trans. Large Scale Data Knowl. Centered Syst. 50: 46-62 (2021) - 2020
- [j21]Djamel Edine Yagoubi, Reza Akbarinia, Florent Masseglia, Themis Palpanas:
Massively Distributed Time Series Indexing and Querying. IEEE Trans. Knowl. Data Eng. 32(1): 108-120 (2020) - 2019
- [c42]Boyan Kolev, Reza Akbarinia, Ricardo Jiménez-Peris, Oleksandra Levchenko, Florent Masseglia, Marta Patiño, Patrick Valduriez:
Parallel Streaming Implementation of Online Time Series Correlation Discovery on Sliding Windows with Regression Capabilities. CLOSER 2019: 681-687 - [c41]Boyan Kolev, Reza Akbarinia, Ricardo Jiménez-Peris, Oleksandra Levchenko, Florent Masseglia, Marta Patiño, Patrick Valduriez:
Pipelined Implementation of a Parallel Streaming Method for Time Series Correlation Discovery on Sliding Windows. DATA 2019: 431-436 - [c40]Oleksandra Levchenko, Boyan Kolev, Djamel Edine Yagoubi, Dennis E. Shasha, Themis Palpanas, Patrick Valduriez, Reza Akbarinia, Florent Masseglia:
Distributed Algorithms to Find Similar Time Series. ECML/PKDD (3) 2019: 781-785 - 2018
- [j19]Djamel Edine Yagoubi, Reza Akbarinia, Boyan Kolev, Oleksandra Levchenko, Florent Masseglia, Patrick Valduriez, Dennis E. Shasha:
ParCorr: efficient parallel methods to identify similar time series pairs across sliding windows. Data Min. Knowl. Discov. 32(5): 1481-1507 (2018) - [c38]Oleksandra Levchenko, Djamel Edine Yagoubi, Reza Akbarinia, Florent Masseglia, Boyan Kolev, Dennis E. Shasha:
Spark-parSketch: A Massively Distributed Indexing of Time Series Datasets. CIKM 2018: 1951-1954 - [c33]Mehdi Zitouni, Reza Akbarinia, Sadok Ben Yahia, Florent Masseglia:
Maximally informative k-itemset mining from massively distributed data streams. SAC 2018: 502-509 - [c32]Patrick Valduriez, Marta Mattoso, Reza Akbarinia, Heraldo Borges, José J. Camata, Alvaro L. G. A. Coutinho, Daniel Gaspar, Noel Moreno Lemus, Ji Liu, Hermano Lustosa, Florent Masseglia, Fabrício Nogueira da Silva, Vítor Silva, Renan Souza, Kary A. C. S. Ocaña, Eduardo S. Ogasawara, Daniel de Oliveira, Esther Pacitti, Fábio Porto, Dennis E. Shasha:
Scientific Data Analysis Using Data-Intensive Scalable Computing: The SciDISC Project. LADaS@VLDB 2018: 1-8 - 2017
- [j18]Saber Salah, Reza Akbarinia, Florent Masseglia:
A highly scalable parallel algorithm for maximally informative k-itemset mining. Knowl. Inf. Syst. 50(1): 1-26 (2017) - [j17]Saber Salah, Reza Akbarinia, Florent Masseglia:
Data placement in massively distributed environments for fast parallel mining of frequent itemsets. Knowl. Inf. Syst. 53(1): 207-237 (2017) - [c31]Mehdi Zitouni, Reza Akbarinia, Sadok Ben Yahia, Florent Masseglia:
Massively Distributed Environments and Closed Itemset Mining: The DCIM Approach. CAiSE 2017: 231-246 - [c29]Djamel Edine Yagoubi, Reza Akbarinia, Florent Masseglia, Dennis E. Shasha:
RadiusSketch: Massively Distributed Indexing of Time Series. DSAA 2017: 262-271 - [c28]Djamel Edine Yagoubi, Reza Akbarinia, Florent Masseglia, Themis Palpanas:
DPiSAX: Massively Distributed Partitioned iSAX. ICDM 2017: 1135-1140 - 2015
- [c27]Saber Salah, Reza Akbarinia, Florent Masseglia:
Data Partitioning for Fast Mining of Frequent Itemsets in Massively Distributed Environments. DEXA (1) 2015: 303-318 - [c25]Mehdi Zitouni, Reza Akbarinia, Sadok Ben Yahia, Florent Masseglia:
A Prime Number Based Approach for Closed Frequent Itemset Mining in Big Data. DEXA (1) 2015: 509-516 - [c24]Saber Salah, Reza Akbarinia, Florent Masseglia:
Fast Parallel Mining of Maximally Informative k-Itemsets in Big Data. ICDM 2015: 359-368 - [c23]Saber Salah, Reza Akbarinia, Florent Masseglia:
Optimizing the Data-Process Relationship for Fast Mining of Frequent Itemsets in MapReduce. MLDM 2015: 217-231 - [c22]Reza Akbarinia, Florent Masseglia:
Aggregation-Aware Compression of Probabilistic Streaming Time Series. MLDM 2015: 232-247 - 2013
- [c19]Reza Akbarinia, Florent Masseglia:
Fast and Exact Mining of Probabilistic Data Streams. ECML/PKDD (1) 2013: 493-508
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