Machine Learning Platform for Extreme Scale Computing on Compressed IoT Data

Autor: Seshu Tirupathi, Dhaval Salwala, Giulio Zizzo, Ambrish Rawat, Mark Purcell, Soren Kejser Jensen, Christian Thomsen, Nguyen Ho, Carlos E. Muniz Cuza, Jonas Brusokas, Torben Bach Pedersen, Giorgos Alexiou, Giorgos Giannopoulos, Panagiotis Gidarakos, Alexandros Kalimeris, Stavros Maroulis, George Papastefanatos, Ioannis Psarros, Vassilis Stamatopoulos, Manolis Terrovitis

Publikováno v: Tirupathi, S, Salwala, D, Zizzo, G, Rawat, A, Purcell, M, Jensen, S K, Thomsen, C, Ho, N, Cuza, C E M, Brusokas, J, Pedersen, T B, Alexiou, G, Giannopoulos, G, Gidarakos, P, Kalimeris, A, Maroulis, S, Papastefanatos, G, Psarros, I, Stamatopoulos, V & Terrovitis, M 2022, Machine Learning Platform for Extreme Scale Computing on Compressed IoT Data . in S Tsumoto, Y Ohsawa, L Chen, D Van den Poel, X Hu, Y Motomura, T Takagi, L Wu, Y Xie, A Abe & V Raghavan (eds), 2022 IEEE International Conference on Big Data (Big Data) ., 10020540, IEEE Communications Society, pp. 3179-3185, 2022 IEEE International Conference on Big Data (Big Data), 17/12/2022 . https://doi.org/10.1109/BigData55660.2022.10020540

With the lowering costs of sensors, high-volume and high-velocity data are increasingly being generated and analyzed, especially in IoT domains like energy and smart homes. Consequently, applications that require accurate short-term forecasts and pre

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6a2118a8cdcd489e5491601b574f9032
https://vbn.aau.dk/da/publications/771ac3a1-1afc-44d3-b442-4f64c86ec4e0

Query Driven Entity Resolution in Data Lakes

Autor: George Papastefanatos, Giorgos Alexiou

Publikováno v: Communications in Computer and Information Science ISBN: 9783030448998
ISIP

Entity Resolution (ER) constitutes a core task for data integration which aims at matching different representations of entities coming from various sources. Due to its quadratic complexity, it typically scales to large datasets through approximate,

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::359bf3f6547e9365288db35c9e610cdc
https://doi.org/10.1007/978-3-030-44900-1_8

Introducing Solon: A Semantic Platform for Managing Legal Sources

Autor: Marios Meimaris, George Papastefanatos, Giorgos Alexiou, Marios Koniaris

Publikováno v: Research and Advanced Technology for Digital Libraries ISBN: 9783319670072
TPDL

In this paper we introduce Solon, a legal document management platform aiming to improve access to legal sources by offering advanced modelling, managing and mining functions. It utilizes a novel method for extracting semantic representations of lega

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::dd15a3b1d69dadd0924b7b9da3ff6def
https://doi.org/10.1007/978-3-319-67008-9_53

OpenAIRE LOD Services: Scholarly Communication Data as Linked Data

Autor: George Papastefanatos, Giorgos Alexiou, Steffen Lohmann, Sahar Vahdati, Christoph Lange

Publikováno v: Semantics, Analytics, Visualization. Enhancing Scholarly Data ISBN: 9783319536361

OpenAIRE, the Open Access Infrastructure for Research in Europe, enables search, discovery and monitoring of publications and datasets from more than 100,000 research projects. Increasing the reusability of the OpenAIRE research metadata, connecting

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::91b915edcf35441300fb2f20cdde8c6e
https://doi.org/10.1007/978-3-319-53637-8_6

Public Spending as LOD: The Case of Greece

Autor: Ioannis Anagnostopoulos, Ioannis Xidias, Giorgos Vafeiadis, Michailis Klonaras, Vasilis Loumos, Marios Meimaris, Giorgos Alexiou, Agis Papantoniou, Michalis Vafopoulos

Publikováno v: SSRN Electronic Journal.

The PSGR project is the first attempt to generate, curate, interlink and distribute daily updated public spending data in LOD formats that can be useful to both expert (i.e. scientists and professionals) and naive users. The PSGR ontology is based on

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::68c69a63eab9fde9183d425c427265bb
https://doi.org/10.2139/ssrn.2233998