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Themis Palpanas
Themistoklis Palpanas
Person information

- affiliation: Paris Descartes University, France
- affiliation (former): University of California, Riverside, USA
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2020 – today
- 2023
- [j88]Zeyu Wang, Qitong Wang, Peng Wang, Themis Palpanas, Wei Wang:
Dumpy: A Compact and Adaptive Index for Large Data Series Collections. Proc. ACM Manag. Data 1(1): 111:1-111:27 (2023) - [j87]Manos Chatzakis, Panagiota Fatourou, Eleftherios Kosmas, Themis Palpanas, Botao Peng:
Odyssey: A Journey in the Land of Distributed Data Series Similarity Search. Proc. VLDB Endow. 16(5): 1140-1153 (2023) - [j86]Ilias Azizi, Karima Echihabi, Themis Palpanas:
Elpis: Graph-Based Similarity Search for Scalable Data Science. Proc. VLDB Endow. 16(6): 1548-1559 (2023) - [j85]Georgios Chatzigeorgakidis
, Dimitrios Skoutas
, Kostas Patroumpas
, Themis Palpanas
, Spiros Athanasiou
, Spiros Skiadopoulos
:
Efficient Range and kNN Twin Subsequence Search in Time Series. IEEE Trans. Knowl. Data Eng. 35(6): 5794-5807 (2023) - [j84]Paul Boniol
, Michele Linardi, Federico Roncallo, Themis Palpanas, Mohammed Meftah, Emmanuel Remy:
Correction to: Unsupervised and scalable subsequence anomaly detection in large data series. VLDB J. 32(2): 469 (2023) - [c102]Paul Boniol, John Paparizzos, Themis Palpanas:
New Trends in Time Series Anomaly Detection. EDBT 2023: 847-850 - [i31]Manos Chatzakis, Panagiota Fatourou, Eleftherios Kosmas, Themis Palpanas, Botao Peng:
Odyssey: A Journey in the Land of Distributed Data Series Similarity Search. CoRR abs/2301.11049 (2023) - [i30]Zeyu Wang, Qitong Wang, Peng Wang, Themis Palpanas, Wei Wang:
Dumpy: A Compact and Adaptive Index for Large Data Series Collections. CoRR abs/2304.08264 (2023) - [i29]Adrien Petralia, Philippe Charpentier, Paul Boniol, Themis Palpanas:
Appliance Detection Using Very Low-Frequency Smart Meter Time Series. CoRR abs/2305.10352 (2023) - 2022
- [j83]John Paparrizos, Yuhao Kang, Paul Boniol, Ruey S. Tsay, Themis Palpanas, Michael J. Franklin:
TSB-UAD: An End-to-End Benchmark Suite for Univariate Time-Series Anomaly Detection. Proc. VLDB Endow. 15(8): 1697-1711 (2022) - [j82]Luca Gagliardelli, George Papadakis, Giovanni Simonini, Sonia Bergamaschi, Themis Palpanas:
Generalized Supervised Meta-blocking. Proc. VLDB Endow. 15(9): 1902-1910 (2022) - [j81]Karima Echihabi, Panagiota Fatourou, Kostas Zoumpatianos, Themis Palpanas, Houda Benbrahim:
Hercules Against Data Series Similarity Search. Proc. VLDB Endow. 15(10): 2005-2018 (2022) - [j80]John Paparrizos, Paul Boniol, Themis Palpanas, Ruey Tsay, Aaron J. Elmore, Michael J. Franklin:
Volume Under the Surface: A New Accuracy Evaluation Measure for Time-Series Anomaly Detection. Proc. VLDB Endow. 15(11): 2774-2787 (2022) - [j79]Wissam Mammar Kouadri, Salima Benbernou, Mourad Ouziri, Themis Palpanas, Iheb Ben Amor:
SA-Q: Observing, Evaluating, and Enhancing the Quality of the Results of Sentiment Analysis Tools. Proc. VLDB Endow. 15(12): 3658-3661 (2022) - [j78]Paul Boniol, John Paparrizos, Yuhao Kang, Themis Palpanas, Ruey S. Tsay, Aaron J. Elmore, Michael J. Franklin:
Theseus: Navigating the Labyrinth of Time-Series Anomaly Detection. Proc. VLDB Endow. 15(12): 3702-3705 (2022) - [j77]Qitong Wang, Stephen Whitmarsh, Vincent Navarro, Themis Palpanas:
iEDeaL: A Deep Learning Framework for Detecting Highly Imbalanced Interictal Epileptiform Discharges. Proc. VLDB Endow. 16(3): 480-490 (2022) - [c101]Karima Echihabi, Themis Palpanas:
Scalable Analytics on Large Sequence Collections. MDM 2022: 5-8 - [c100]Paul Boniol, Mohammed Meftah, Emmanuel Remy, Themis Palpanas:
dCAM: Dimension-wise Class Activation Map for Explaining Multivariate Data Series Classification. SIGMOD Conference 2022: 1175-1189 - [e5]Maya Ramanath, Themis Palpanas:
Proceedings of the Workshops of the EDBT/ICDT 2022 Joint Conference, Edinburgh, UK, March 29, 2022. CEUR Workshop Proceedings 3135, CEUR-WS.org 2022 [contents] - [i28]Luca Gagliardelli, George Papadakis, Giovanni Simonini, Sonia Bergamaschi, Themis Palpanas:
Generalized Supervised Meta-blocking (technical report). CoRR abs/2204.08801 (2022) - [i27]Paul Boniol, Mohammed Meftah, Emmanuel Remy, Themis Palpanas:
dCAM: Dimension-wise Class Activation Map for Explaining Multivariate Data Series Classification. CoRR abs/2207.12165 (2022) - [i26]Paul Boniol, Themis Palpanas:
Series2Graph: Graph-based Subsequence Anomaly Detection for Time Series. CoRR abs/2207.12208 (2022) - [i25]Karima Echihabi, Panagiota Fatourou, Kostas Zoumpatianos, Themis Palpanas, Houda Benbrahim:
Hercules Against Data Series Similarity Search. CoRR abs/2212.13297 (2022) - [i24]Karima Echihabi, Theophanis Tsandilas, Anna Gogolou, Anastasia Bezerianos, Themis Palpanas:
ProS: Data Series Progressive k-NN Similarity Search and Classification with Probabilistic Quality Guarantees. CoRR abs/2212.13310 (2022) - 2021
- [b3]George Papadakis, Ekaterini Ioannou, Emanouil Thanos, Themis Palpanas:
The Four Generations of Entity Resolution. Synthesis Lectures on Data Management, Morgan & Claypool Publishers 2021, pp. 1-170 - [j76]George Papadakis
, Dimitrios Skoutas
, Emmanouil Thanos, Themis Palpanas:
Blocking and Filtering Techniques for Entity Resolution: A Survey. ACM Comput. Surv. 53(2): 31:1-31:42 (2021) - [j75]Vassilis Christophides, Vasilis Efthymiou
, Themis Palpanas, George Papadakis
, Kostas Stefanidis
:
An Overview of End-to-End Entity Resolution for Big Data. ACM Comput. Surv. 53(6): 127:1-127:42 (2021) - [j74]Georgios M. Mandilaras, George Papadakis
, Luca Gagliardelli, Giovanni Simonini, Emmanouil Thanos
, George Giannakopoulos
, Sonia Bergamaschi, Themis Palpanas, Manolis Koubarakis
, Alicia Lara-Clares, Antonio Fariña
:
Reproducible experiments on Three-Dimensional Entity Resolution with JedAI. Inf. Syst. 102: 101830 (2021) - [j73]Loris Belcastro
, Fabrizio Marozzo
, Domenico Talia, Paolo Trunfio, Francesco Branda
, Themis Palpanas, Muhammad Imran:
Using social media for sub-event detection during disasters. J. Big Data 8(1): 79 (2021) - [j72]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) - [j71]Paul Boniol, John Paparrizos, Themis Palpanas, Michael J. Franklin:
SAND: Streaming Subsequence Anomaly Detection. Proc. VLDB Endow. 14(10): 1717-1729 (2021) - [j70]Paul Boniol, John Paparrizos, Themis Palpanas, Michael J. Franklin:
SAND in Action: Subsequence Anomaly Detection for Streams. Proc. VLDB Endow. 14(12): 2867-2870 (2021) - [j69]Karima Echihabi
, Themis Palpanas, Kostas Zoumpatianos:
New Trends in High-D Vector Similarity Search: AI-driven, Progressive, and Distributed. Proc. VLDB Endow. 14(12): 3198-3201 (2021) - [j68]Botao Peng
, Panagiota Fatourou
, Themis Palpanas
:
ParIS+: Data Series Indexing on Multi-Core Architectures. IEEE Trans. Knowl. Data Eng. 33(5): 2151-2164 (2021) - [j67]Paul Boniol
, Michele Linardi, Federico Roncallo, Themis Palpanas, Mohammed Meftah, Emmanuel Remy:
Unsupervised and scalable subsequence anomaly detection in large data series. VLDB J. 30(6): 909-931 (2021) - [j66]Botao Peng
, Panagiota Fatourou, Themis Palpanas:
Fast data series indexing for in-memory data. VLDB J. 30(6): 1041-1067 (2021) - [c99]Luka Jakovljevic, Dimitre Kostadinov, Armen Aghasaryan, Themis Palpanas:
Towards Building a Digital Twin of Complex System Using Causal Modelling. COMPLEX NETWORKS 2021: 475-486 - [c98]Georgios Chatzigeorgakidis, Dimitrios Skoutas
, Kostas Patroumpas, Themis Palpanas, Spiros Athanasiou, Spiros Skiadopoulos
:
Twin Subsequence Search in Time Series. EDBT 2021: 475-480 - [c97]Karima Echihabi
, Kostas Zoumpatianos, Themis Palpanas:
Big Sequence Management: Scaling up and Out. EDBT 2021: 714-717 - [c96]Pauline Laviron, Xueqi Dai, Bérénice Huquet, Themis Palpanas:
Electricity Demand Activation Extraction: From Known to Unknown Signatures, Using Similarity Search. e-Energy 2021: 148-159 - [c95]Wissam Maamar Kouadri, Salima Benbernou, Mourad Ouziri, Themis Palpanas, Iheb Ben Amor:
SentiQ: Une approche logique-probabiliste pour améliorer la qualité de l'analyse des sentiments. EGC 2021: 513-514 - [c94]Botao Peng, Panagiota Fatourou, Themis Palpanas:
SING: Sequence Indexing Using GPUs. ICDE 2021: 1883-1888 - [c93]Karima Echihabi
, Kostas Zoumpatianos, Themis Palpanas:
High-Dimensional Similarity Search for Scalable Data Science. ICDE 2021: 2369-2372 - [c92]Qitong Wang
, Themis Palpanas:
Deep Learning Embeddings for Data Series Similarity Search. KDD 2021: 1708-1716 - [i23]Georgios Chatzigeorgakidis
, Dimitrios Skoutas, Kostas Patroumpas, Themis Palpanas, Spiros Athanasiou, Spiros Skiadopoulos:
Twin Subsequence Search in Time Series. CoRR abs/2104.06874 (2021) - [i22]Georgios Chatzigeorgakidis, Dimitrios Skoutas, Kostas Patroumpas, Themis Palpanas, Spiros Athanasiou, Spiros Skiadopoulos:
Local Pair and Bundle Discovery over Co-Evolving Time Series. CoRR abs/2104.09417 (2021) - [i21]Georgios Chatzigeorgakidis, Dimitrios Skoutas, Kostas Patroumpas, Themis Palpanas, Spiros Athanasiou, Spiros Skiadopoulos:
Local Similarity Search on Geolocated Time Series Using Hybrid Indexing. CoRR abs/2104.09509 (2021) - [i20]Botao Peng, Panagiota Fatourou, Themis Palpanas:
Fast Data Series Indexing for In-Memory Data. CoRR abs/2110.07519 (2021) - 2020
- [j65]Michele Linardi
, Yan Zhu, Themis Palpanas, Eamonn J. Keogh:
Matrix profile goes MAD: variable-length motif and discord discovery in data series. Data Min. Knowl. Discov. 34(4): 1022-1071 (2020) - [j64]Remy Kusters, Dusan Misevic, Hugues Berry
, Antoine Cully
, Yann Le Cunff
, Loic Dandoy, Natalia Díaz Rodríguez
, Marion Ficher, Jonathan Grizou, Alice Othmani, Themis Palpanas, Matthieu Komorowski
, Patrick Loiseau, Clément Moulin-Frier, Santino Nanini, Daniele Quercia, Michèle Sebag, Françoise Fogelman-Soulié, Sofiane Taleb, Liubov Tupikina, Vaibhav Sahu, Jill-Jênn Vie, Fatima Wehbi:
Interdisciplinary Research in Artificial Intelligence: Challenges and Opportunities. Frontiers Big Data 3: 577974 (2020) - [j63]George Papadakis
, Georgios M. Mandilaras, Luca Gagliardelli, Giovanni Simonini, Emmanouil Thanos
, George Giannakopoulos, Sonia Bergamaschi, Themis Palpanas, Manolis Koubarakis:
Three-dimensional Entity Resolution with JedAI. Inf. Syst. 93: 101565 (2020) - [j62]Paul Boniol, Themis Palpanas:
Series2Graph: Graph-based Subsequence Anomaly Detection for Time Series. Proc. VLDB Endow. 13(11): 1821-1834 (2020) - [j61]Paul Boniol, Themis Palpanas, Mohammed Meftah, Emmanuel Remy:
GraphAn: Graph-based Subsequence Anomaly Detection. Proc. VLDB Endow. 13(12): 2941-2944 (2020) - [j60]Wissam Maamar Kouadri
, Mourad Ouziri, Salima Benbernou, Karima Echihabi
, Themis Palpanas, Iheb Ben Amor:
Quality of Sentiment Analysis Tools: The Reasons of Inconsistency. Proc. VLDB Endow. 14(4): 668-681 (2020) - [j59]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) - [j58]Michele Linardi
, Themis Palpanas:
Scalable data series subsequence matching with ULISSE. VLDB J. 29(6): 1449-1474 (2020) - [c91]George Papadakis, Leonidas Tsekouras, Emmanouil Thanos, Nikiforos Pittaras, Giovanni Simonini, Dimitrios Skoutas
, Paul Isaris
, George Giannakopoulos, Themis Palpanas, Manolis Koubarakis:
JedAI3 : beyond batch, blocking-based Entity Resolution. EDBT 2020: 603-606 - [c90]George Papadakis, Ekaterini Ioannou, Themis Palpanas:
Entity Resolution: Past, Present and Yet-to-Come. EDBT 2020: 647-650 - [c89]Botao Peng, Panagiota Fatourou, Themis Palpanas:
MESSI: In-Memory Data Series Indexing. ICDE 2020: 337-348 - [c88]Paul Boniol, Michele Linardi
, Federico Roncallo, Themis Palpanas:
SAD: An Unsupervised System for Subsequence Anomaly Detection. ICDE 2020: 1778-1781 - [c87]Paul Boniol, Michele Linardi
, Federico Roncallo, Themis Palpanas:
Automated Anomaly Detection in Large Sequences. ICDE 2020: 1834-1837 - [c86]Anna Gogolou, Theophanis Tsandilas, Karima Echihabi
, Anastasia Bezerianos
, Themis Palpanas:
Data Series Progressive Similarity Search with Probabilistic Quality Guarantees. SIGMOD Conference 2020: 1857-1873 - [c85]Karima Echihabi, Kostas Zoumpatianos, Themis Palpanas:
Scalable Machine Learning on High-Dimensional Vectors: From Data Series to Deep Network Embeddings. WIMS 2020: 1-6 - [c84]Matteo Lissandrini
, Davide Mottin
, Themis Palpanas, Yannis Velegrakis:
Graph-Query Suggestions for Knowledge Graph Exploration. WWW 2020: 2549-2555 - [i19]Karima Echihabi, Kostas Zoumpatianos, Themis Palpanas, Houda Benbrahim:
The Lernaean Hydra of Data Series Similarity Search: An Experimental Evaluation of the State of the Art. CoRR abs/2006.11454 (2020) - [i18]Karima Echihabi, Kostas Zoumpatianos, Themis Palpanas, Houda Benbrahim:
Return of the Lernaean Hydra: Experimental Evaluation of Data Series Approximate Similarity Search. CoRR abs/2006.11459 (2020) - [i17]Haridimos Kondylakis, Niv Dayan, Kostas Zoumpatianos, Themis Palpanas:
Coconut: sortable summarizations for scalable indexes over static and streaming data series. CoRR abs/2006.11474 (2020) - [i16]Haridimos Kondylakis, Niv Dayan, Kostas Zoumpatianos, Themis Palpanas:
Coconut Palm: Static and Streaming Data Series Exploration Now in your Palm. CoRR abs/2006.13079 (2020) - [i15]Haridimos Kondylakis, Niv Dayan, Kostas Zoumpatianos, Themis Palpanas:
Coconut: a scalable bottom-up approach for building data series indexes. CoRR abs/2006.13713 (2020) - [i14]Wissam Maamar Kouadri, Salima Benbernou, Mourad Ouziri, Themis Palpanas, Iheb Ben Amor:
SentiQ: A Probabilistic Logic Approach to Enhance Sentiment Analysis Tool Quality. CoRR abs/2008.08919 (2020) - [i13]Michele Linardi, Yan Zhu, Themis Palpanas, Eamonn J. Keogh:
VALMOD: A Suite for Easy and Exact Detection of Variable Length Motifs in Data Series. CoRR abs/2008.13432 (2020) - [i12]Michele Linardi, Yan Zhu, Themis Palpanas, Eamonn J. Keogh:
Matrix Profile Goes MAD: Variable-Length Motif And Discord Discovery in Data Series. CoRR abs/2008.13447 (2020) - [i11]Botao Peng, Panagiota Fatourou, Themis Palpanas:
ParIS+: Data Series Indexing on Multi-Core Architectures. CoRR abs/2009.00166 (2020) - [i10]Botao Peng, Panagiota Fatourou, Themis Palpanas:
MESSI: In-Memory Data Series Indexing. CoRR abs/2009.00786 (2020) - [i9]Michele Linardi, Themis Palpanas:
Scalable Data Series Subsequence Matching with ULISSE. CoRR abs/2009.10373 (2020)
2010 – 2019
- 2019
- [j57]Michele Dallachiesa, Charu C. Aggarwal, Themis Palpanas:
Improving Classification Quality in Uncertain Graphs. ACM J. Data Inf. Qual. 11(1): 3:1-3:20 (2019) - [j56]Karima Echihabi
, Kostas Zoumpatianos, Themis Palpanas, Houda Benbrahim:
Return of the Lernaean Hydra: Experimental Evaluation of Data Series Approximate Similarity Search. Proc. VLDB Endow. 13(3): 403-420 (2019) - [j55]Themis Palpanas, Volker Beckmann:
Report on the First and Second Interdisciplinary Time Series Analysis Workshop (ITISA). SIGMOD Rec. 48(3): 36-40 (2019) - [j54]George Papadakis, Leonidas Tsekouras, Emmanouil Thanos, George Giannakopoulos, Themis Palpanas, Manolis Koubarakis:
Domain- and Structure-Agnostic End-to-End Entity Resolution with JedAI. SIGMOD Rec. 48(4): 30-36 (2019) - [j53]Giovanni Simonini
, George Papadakis
, Themis Palpanas
, Sonia Bergamaschi
:
Schema-Agnostic Progressive Entity Resolution. IEEE Trans. Knowl. Data Eng. 31(6): 1208-1221 (2019) - [j52]Anna Gogolou, Theophanis Tsandilas, Themis Palpanas, Anastasia Bezerianos
:
Comparing Similarity Perception in Time Series Visualizations. IEEE Trans. Vis. Comput. Graph. 25(1): 523-533 (2019) - [j51]Haridimos Kondylakis
, Niv Dayan, Kostas Zoumpatianos, Themis Palpanas:
Coconut: sortable summarizations for scalable indexes over static and streaming data series. VLDB J. 28(6): 847-869 (2019) - [c83]Anna Gogolou, Theophanis Tsandilas, Themis Palpanas, Anastasia Bezerianos:
Progressive Similarity Search on Time Series Data. EDBT/ICDT Workshops 2019 - [c82]Georgios Chatzigeorgakidis
, Dimitrios Skoutas
, Kostas Patroumpas, Themis Palpanas, Spiros Athanasiou, Spiros Skiadopoulos
:
Local Similarity Search on Geolocated Time Series Using Hybrid Indexing. SIGSPATIAL/GIS 2019: 179-188 - [c81]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 - [c80]Matteo Lissandrini
, Davide Mottin
, Themis Palpanas, Yannis Velegrakis:
Example-based Search: a New Frontier for Exploratory Search. SIGIR 2019: 1411-1412 - [c79]Haridimos Kondylakis, Niv Dayan, Kostas Zoumpatianos, Themis Palpanas:
Coconut Palm: Static and Streaming Data Series Exploration Now in your Palm. SIGMOD Conference 2019: 1941-1944 - [c78]Davide Mottin
, Matteo Lissandrini
, Yannis Velegrakis, Themis Palpanas:
Exploring the Data Wilderness through Examples. SIGMOD Conference 2019: 2031-2035 - [c77]Georgios Chatzigeorgakidis, Dimitrios Skoutas
, Kostas Patroumpas, Themis Palpanas, Spiros Athanasiou, Spiros Skiadopoulos
:
Local Pair and Bundle Discovery over Co-Evolving Time Series. SSTD 2019: 160-169 - [i8]George Papadakis, Dimitrios Skoutas, Emmanouil Thanos, Themis Palpanas:
A Survey of Blocking and Filtering Techniques for Entity Resolution. CoRR abs/1905.06167 (2019) - [i7]Giovanni Simonini, George Papadakis, Themis Palpanas, Sonia Bergamaschi:
Schema-agnostic Progressive Entity Resolution (extended version). CoRR abs/1905.06385 (2019) - [i6]Vassilis Christophides, Vasilis Efthymiou, Themis Palpanas, George Papadakis, Kostas Stefanidis:
End-to-End Entity Resolution for Big Data: A Survey. CoRR abs/1905.06397 (2019) - [i5]Anthony J. Bagnall, Richard L. Cole, Themis Palpanas, Konstantinos Zoumpatianos:
Data Series Management (Dagstuhl Seminar 19282). Dagstuhl Reports 9(7): 24-39 (2019) - 2018
- [b2]Matteo Lissandrini, Davide Mottin
, Themis Palpanas, Yannis Velegrakis:
Data Exploration Using Example-Based Methods. Synthesis Lectures on Data Management, Morgan & Claypool Publishers 2018 - [j50]Haridimos Kondylakis, Niv Dayan, Kostas Zoumpatianos, Themis Palpanas:
Coconut: A Scalable Bottom-Up Approach for Building Data Series Indexes. Proc. VLDB Endow. 11(6): 677-690 (2018) - [j49]George Papadakis, Leonidas Tsekouras, Emmanouil Thanos, George Giannakopoulos
, Themis Palpanas, Manolis Koubarakis:
The return of JedAI: End-to-End Entity Resolution for Structured and Semi-Structured Data. Proc. VLDB Endow. 11(12): 1950-1953 (2018) - [j48]Matteo Lissandrini
, Davide Mottin
, Themis Palpanas, Yannis Velegrakis:
X2Q: Your Personal Example-based Graph Explorer. Proc. VLDB Endow. 11(12): 2026-2029 (2018) - [j47]Michele Linardi
, Themis Palpanas:
Scalable, Variable-Length Similarity Search in Data Series: The ULISSE Approach. Proc. VLDB Endow. 11(13): 2236-2248 (2018) - [j46]Karima Echihabi
, Kostas Zoumpatianos, Themis Palpanas, Houda Benbrahim:
The Lernaean Hydra of Data Series Similarity Search: An Experimental Evaluation of the State of the Art. Proc. VLDB Endow. 12(2): 112-127 (2018) - [j45]Kostas Zoumpatianos
, Yin Lou, Ioana Ileana, Themis Palpanas, Johannes Gehrke:
Generating data series query workloads. VLDB J. 27(6): 823-846 (2018) - [c76]Botao Peng, Panagiota Fatourou, Themis Palpanas:
ParIS: The Next Destination for Fast Data Series Indexing and Query Answering. IEEE BigData 2018: 791-800 - [c75]Alberto Cordioli, Themis Palpanas:
An Automated System for Internet Pharmacy Verification. EDBT 2018: 588-599 - [c74]Giovanni Simonini
, George Papadakis, Themis Palpanas, Sonia Bergamaschi:
Schema-Agnostic Progressive Entity Resolution. ICDE 2018: 53-64 - [c73]Matteo Lissandrini
, Davide Mottin
, Themis Palpanas, Yannis Velegrakis:
Multi-Example Search in Rich Information Graphs. ICDE 2018: 809-820 - [c72]Michele Linardi
, Themis Palpanas:
ULISSE: ULtra Compact Index for Variable-Length Similarity Search in Data Series. ICDE 2018: 1356-1359 - [c71]Kostas Zoumpatianos, Themis Palpanas:
Data Series Management: Fulfilling the Need for Big Sequence Analytics. ICDE 2018: 1677-1678 - [c70]Michele Linardi
, Yan Zhu, Themis Palpanas, Eamonn J. Keogh:
Matrix Profile X: VALMOD - Scalable Discovery of Variable-Length Motifs in Data Series. SIGMOD Conference 2018: 1053-1066 - [c69]Michele Linardi
, Yan Zhu, Themis Palpanas, Eamonn J. Keogh:
VALMOD: A Suite for Easy and Exact Detection of Variable Length Motifs in Data Series. SIGMOD Conference 2018: 1757-1760 - [r2]Sihem Amer-Yahia, Themis Palpanas, Mikalai Tsytsarau, Sofia Kleisarchaki, Ahlame Douzal, Vassilis Christophides:
Temporal Analytics in Social Media. Encyclopedia of Database Systems (2nd ed.) 2018 - [r1]Themis Palpanas, Panayiotis Tsaparas:
Rank-Join Indices. Encyclopedia of Database Systems (2nd ed.) 2018 - [i4]Cagatay Turkay, Nicola Pezzotti, Carsten Binnig, Hendrik Strobelt, Barbara Hammer, Daniel A. Keim, Jean-Daniel Fekete
, Themis Palpanas, Yunhai Wang, Florin Rusu:
Progressive Data Science: Potential and Challenges. CoRR abs/1812.08032 (2018) - 2017
- [j44]Katsiaryna Mirylenka, George Giannakopoulos
, Le Minh Do, Themis Palpanas:
On classifier behavior in the presence of mislabeling noise. Data Min. Knowl. Discov. 31(3): 661-701 (2017) - [j43]Vasilis Efthymiou
, George Papadakis
, George Papastefanatos
, Kostas Stefanidis
, Themis Palpanas:
Parallel meta-blocking for scaling entity resolution over big heterogeneous data. Inf. Syst. 65: 137-157 (2017) - [j42]Davide Mottin
, Matteo Lissandrini
, Yannis Velegrakis, Themis Palpanas:
New Trends on Exploratory Methods for Data Analytics. Proc. VLDB Endow. 10(12): 1977-1980 (2017) - [c68]Katsiaryna Mirylenka, Michele Dallachiesa, Themis Palpanas:
Correlation-Aware Distance Measures for Data Series. EDBT 2017: 502-505 - [c67]George Papadakis, Leonidas Tsekouras, Emmanouil Thanos, George Giannakopoulos
, Themis Palpanas, Manolis Koubarakis:
JedAI: The Force Behind Entity Resolution. ESWC (Satellite Events) 2017: 161-166 - [c66]George Papadakis, Konstantina Bereta
, Themis Palpanas, Manolis Koubarakis:
Multi-core Meta-blocking for Big Linked Data. SEMANTiCS 2017: 33-40 - [c65]Djamel Edine Yagoubi, Reza Akbarinia, Florent Masseglia, Themis Palpanas:
DPiSAX: Massively Distributed Partitioned iSAX. ICDM 2017: 1135-1140 - [c64]Pavlos Paraskevopoulos, Giovanni Pellegrini, Themis Palpanas:
TweeLoc: A System for Geolocalizing Tweets at Fine-Grain. ICDM Workshops 2017: 1178-1183 - [c63]Themis Palpanas:
The Parallel and Distributed Future of Data Series Mining. HPCS 2017: 916-920 - [c62]