All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

A novel approach for mining closed clickstream patterns

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F21%3A63544038" target="_blank" >RIV/70883521:28140/21:63544038 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.tandfonline.com/doi/full/10.1080/01969722.2020.1871225" target="_blank" >https://www.tandfonline.com/doi/full/10.1080/01969722.2020.1871225</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1080/01969722.2020.1871225" target="_blank" >10.1080/01969722.2020.1871225</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    A novel approach for mining closed clickstream patterns

  • Original language description

    Closed sequential pattern (CSP) mining is an optimization technique in sequential pattern mining because they produce more compact representations. Additionally, the runtime and memory usage required for mining CSPs is much lower than the sequential pattern mining. This task has fascinated numerous researchers. In this study, we propose a novel approach for closed clickstream pattern mining using C-List (CCPC) data structure. Closed clickstream pattern mining is a more specific task of CSP mining that has been lacking in research investment; nevertheless, it has promising applications in various fields. CCPC consists of two key steps: It initially builds the SPPC-tree and the C-List for each frequent 1-pattern and then determines all frequently closed clickstream 1-patterns; next, it constructs the C-List for each frequent k-pattern and mines the remaining frequently closed k-patterns. The proposed method is optimized by modifying the SPPC-tree structure and a new property is added into each node element in both the SPPC-tree and C-Lists to quickly prune nonclosed clickstream. Experimental results conducted on several datasets show that the proposed method is better than the previous techniques and improves the runtime and memory usage in most cases, especially when using low minimum support thresholds on the huge databases. © 2021 Taylor &amp; Francis Group, LLC.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

  • Continuities

    V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Others

  • Publication year

    2021

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Cybernetics and Systems

  • ISSN

    0196-9722

  • e-ISSN

  • Volume of the periodical

    52

  • Issue of the periodical within the volume

    5

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    12

  • Pages from-to

    328-349

  • UT code for WoS article

    000606927900001

  • EID of the result in the Scopus database

    2-s2.0-85099369902