Learning algorithms in AI system and services

Young Sik Jeong, Jong Hyuk Park

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

In recent years, artificial intelligence (AI) services have become one of the most essential parts to extend human capabilities in various fields such as face recognition for security, weather prediction, and so on. Various learning algorithms for existing AI services are utilized, such as classification, regression, and deep learning, to increase accuracy and efficiency for humans. Nonetheless, these services face many challenges such as fake news spread on social media, stock selection, and volatility delay in stock prediction systems and inaccurate moviebased recommendation systems. In this paper, various algorithms are presented to mitigate these issues in different systems and services. Convolutional neural network algorithms are used for detecting fake news in Korean language with a Word-Embedded model. It is based on k-clique and data mining and increased accuracy in personalized recommendation-based services stock selection and volatility delay in stock prediction. Other algorithms like multi-level fusion processing address problems of lack of real-time database.

Original languageEnglish
Pages (from-to)1029-1035
Number of pages7
JournalJournal of Information Processing Systems
Volume15
Issue number5
DOIs
StatePublished - 2019

Keywords

  • Blockchain and Crypto Currency
  • Cloud Computing
  • Internet of Things
  • Sentiment Analysis

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