TY - JOUR
T1 - Pattern-based and visual analytics for visitor analysis on websites
AU - Cervantes, Bárbara
AU - Gómez, Fernando
AU - Monroy, Raúl
AU - Loyola-González, Octavio
AU - Medina-Pérez, Miguel Angel
AU - Ramírez-Márquez, José
N1 - Publisher Copyright:
© 2019 by the authors.
PY - 2019/9/1
Y1 - 2019/9/1
N2 - In this paper, We present how we combined visualization and machine learning techniques to provide an analytic tool for web log data.We designed a visualization where advertisers can observe the visits to their different pages on a site, common web analytic measures and individual user navigation on the site. In this visualization, the users can get insights of the data by looking at key elements of the graph. Additionally, we applied pattern mining techniques to observe common trends in user segments of interest.
AB - In this paper, We present how we combined visualization and machine learning techniques to provide an analytic tool for web log data.We designed a visualization where advertisers can observe the visits to their different pages on a site, common web analytic measures and individual user navigation on the site. In this visualization, the users can get insights of the data by looking at key elements of the graph. Additionally, we applied pattern mining techniques to observe common trends in user segments of interest.
KW - Data visualization
KW - Log analysis
KW - Pattern mining
UR - https://www.scopus.com/pages/publications/85072376553
UR - https://www.scopus.com/inward/citedby.url?scp=85072376553&partnerID=8YFLogxK
U2 - 10.3390/app9183840
DO - 10.3390/app9183840
M3 - Article
AN - SCOPUS:85072376553
VL - 9
JO - Applied Sciences (Switzerland)
JF - Applied Sciences (Switzerland)
IS - 18
M1 - 3840
ER -