Frequent Pattern Retrieval on Data Streams by using Sliding Window

Authors

  • P. Mahesh Kumar TKR College of Engineering and Technology
  • P. Srinivasa Rao Maharaj Vijayaram Gajapathi Raj College of Engineering image/svg+xml

DOI:

https://doi.org/10.4108/eai.13-1-2021.168091

Keywords:

Frequent Pattern Retrieval Algorithm, Information Extraction, Sliding Window Stream Data, Candidate Patterns

Abstract

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.

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Published

13-01-2021

How to Cite

1.
Mahesh Kumar P, Srinivasa Rao P. Frequent Pattern Retrieval on Data Streams by using Sliding Window. EAI Endorsed Trans Energy Web [Internet]. 2021 Jan. 13 [cited 2024 Dec. 22];8(35):e3. Available from: https://publications.eai.eu/index.php/ew/article/view/770