• Journal of Internet Computing and Services
    ISSN 2287 - 1136 (Online) / ISSN 1598 - 0170 (Print)
    https://jics.or.kr/

Digital Library


Search: "[ keyword: Pattern mining ]" (11)
  1. 1. Recent Technique Analysis, Infant Commodity Pattern Analysis Scenario and Performance Analysis of Incremental Weighted Maximal Representative Pattern Mining
    Unil Yun, Eunmi Yun, Vol. 21, No. 2, pp. 39-48, Apr. 2020
    10.7472/jksii.2020.21.2.39
    Keywords: Weighted maximal pattern mining, Incremental mining, Representative pattern, Application scenario, Performance Evaluation
  2. 2. Performance Analysis of Siding Window based Stream High Utility Pattern Mining Methods
    Heungmo Ryang, Unil Yun, Vol. 17, No. 6, pp. 53-60, Dec. 2016
    10.7472/jksii.2016.17.6.53
    Keywords: Pattern mining, High utility pattern mining, sliding window model, resource-limited environments
  3. 3. Performance Analysis of Top-K High Utility Pattern Mining Methods
  4. 4. Analysis and Performance Evaluation of Pattern Condensing Techniques used in Representative Pattern Mining
  5. 5. A Weighted Frequent Graph Pattern Mining Approach considering Length-Decreasing Support Constraints
    Unil Yun, Gangin Lee, Vol. 15, No. 6, pp. 125-132, Dec. 2014
    10.7472/jksii.2014.15.6.125
    Keywords: Length-decreasing support constraint, weighted frequent pattern mining, graph pattern, Data Mining, Frequent pattern mining
  6. 6. Analysis and Evaluation of Frequent Pattern Mining Technique based on Landmark Window
    Gwangbum Pyun, Unil Yun, Vol. 15, No. 3, pp. 101-108, Jun. 2014
    10.7472/jksii.2014.15.3.101
    Keywords: Landmark Window, Frequent pattern mining, Online mining, Performance Evaluation, scalability
  7. 7. Performance Analysis of Frequent Pattern Mining with Multiple Minimum Supports
    Heungmo Ryang, Unil Yun, Vol. 14, No. 6, pp. 1-8, Dec. 2013
    10.7472/jksii.2013.14.6.01
    Keywords: Multiple minimum supports, Frequent pattern mining, Rare frequent patterns, Performance Evaluation, scalability
  8. 8. Performance evaluation of approximate frequent pattern mining based on probabilistic technique
  9. 9. Optimal Moving Pattern Mining using Frequency of Sequence and Weights
  10. 10. A Comparison of Performance between STMP/MST and Existing Spatio-Temporal Moving Pattern Mining Methods