Effective Garbage Data Filtering Algorithm for SNS Big Data Processing by Machine Learning

@article{1704643,
      author = {B. Sravani, A. Sharanya, M. Akhila, G. Swathi},
      title = {Effective Garbage Data Filtering Algorithm for SNS Big Data Processing by Machine Learning},
      journal = {Iconic Research And Engineering Journals},
      year = {2023},
      volume = {6},
      number = {12},
      pages = {350-357},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1704643.pdf},
      abstract = {Recently, as the use of social network services (SNS) increases in modern daily life, the amount of SNS data has become enormous. In addition, more and more efforts are being made to extract different pieces of information by collecting, processing, and analysing large amounts of SNS data. Although various pieces of information can be extracted from SNS data through big data processing, this is a resource-intensive task. Therefore, extracting information from SNS data requires considerable time and material resources. In this paper, we propose a data filtering algorithm that filters out junk data that has no data meaning in SNS data. The proposed algorithm improves the filtering accuracy by iterative learning based on the initial learning data. Experimental results show that the proposed algorithm has a filtering effect of more than 70% on experimental keywords.},
      keywords = {Social network services, big data, machine learning, iterative learning.},
      month = {June},
  }