Incremental learning for large scale classification systems

Athanasios Alexopoulos, Andreas Kanavos, Konstantinos Giotopoulos, Alaa Mohasseb, Mohamed Bader-El-Den, Athanasios Tsakalidis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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One of the main characteristics of our time is the growth of the data volumes. We collect data literally from everywhere; smart phones, smart devices, social media and the health care system, which defines a small portion of the sources of the big data. The big data growth poses two main difficulties, storing and processing them. For the former, there are certain new technologies that enable us to store large amounts of data in a fast and reliable way. For the latter, new application frameworks have been developed. In this paper, we perform classification analysis using Apache Spark in one real dataset. The classification algorithms that we have used are multiclass, and we are going to examine the effect of the dataset size and input features on the classification results.
Original languageEnglish
Title of host publicationArtificial Intelligence Applications and Innovations
Subtitle of host publicationAIAI 2018 IFIP WG 12.5 International Workshops, SEDSEAL, 5G-PINE, MHDW, and HEALTHIOT, Rhodes, Greece, May 25-27, 2018, Proceedings
EditorsLazaros Iliadis, Ilias Maglogiannis, Vassilis Plagianakos
Number of pages11
ISBN (Electronic)978-3-319-92016-0
ISBN (Print)978-3-319-92015-3
Publication statusPublished - Jun 2018
Event14th International Conference on Artificial Intelligence Applications and Innovations - Rhodes, Greece
Duration: 25 May 201827 May 2018

Publication series

NameIFIP Advances in Information and Communication Technology
ISSN (Print)1868-4238
ISSN (Electronic)1868-422X


Conference14th International Conference on Artificial Intelligence Applications and Innovations
Abbreviated titleAIAI 2018
Internet address


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