ew 18: e3

Research Article

Frequent Pattern Retrieval on Data Streams by using Sliding Window

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  • @ARTICLE{10.4108/eai.13-1-2021.168091,
        author={P. Mahesh Kumar and P. Srinivasa Rao},
        title={Frequent Pattern Retrieval on Data Streams by using Sliding Window},
        journal={EAI Endorsed Transactions on Energy Web: Online First},
        keywords={Frequent Pattern Retrieval Algorithm, Information Extraction, Sliding Window Stream Data, Candidate Patterns},
  • P. Mahesh Kumar
    P. Srinivasa Rao
    Year: 2021
    Frequent Pattern Retrieval on Data Streams by using Sliding Window
    DOI: 10.4108/eai.13-1-2021.168091
P. Mahesh Kumar1,*, P. Srinivasa Rao2
  • 1: Assistant Professor of CSE, TKR College of Engineering and Technology, Hyderabad, External Research Scholar, CSE, JNTUK, Kakinada, India
  • 2: Associate Professor of CSE, MVGR College of Engineering, Vizianagaram, Andhrapradesh, India
*Contact email: maheshkumarp@tkrcet.com


In different applications like recommender frameworks and market examination, regular patterns play a significant role in useful mining data. Mining regular patterns from sliding windows over streaming information has become a complex task. In this examination, the sliding window is utilized to build the framework and FP tree applied to mine the dataset's valuable data. The sliding window has the arrangement of patterns put away in the Matrix, which contains the transaction in the sliding information and thenapplied to the FP tree. In this paper, the Frequent Pattern Retrieval strategy is planned by utilizing anFP tree approach and a sliding window model to extract noteworthy examples from data streams. The proposed technique accomplished less runtime with low memory use for the Breast disease dataset and different datasets to run the least utility edge contrasted with different existing procedures.