Models of virtual library users’ behavior analysis
In this paper, we present models for the analysis of the behavior of the virtual library (VL) users. Unlike the models presented in the literature, they use only the big data that is stored in the log files of virtual library servers and methods of statistics, association rules, and recommendation...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Vilnius University Press
2021-02-01
|
Series: | Lietuvos Matematikos Rinkinys |
Subjects: | |
Online Access: | https://www.zurnalai.vu.lt/LMR/article/view/22521 |
id |
doaj-98859d1e6e8d4e9081f41efae6f017ad |
---|---|
record_format |
Article |
spelling |
doaj-98859d1e6e8d4e9081f41efae6f017ad2021-02-19T09:21:52ZengVilnius University PressLietuvos Matematikos Rinkinys0132-28182335-898X2021-02-0161A10.15388/LMR.2020.22521Models of virtual library users’ behavior analysisGytis Vievesis0Vytautas Janilionis1Antanas Štreimikis2Kaunas University of TechnologyKaunas University of TechnologyKaunas University of Technology In this paper, we present models for the analysis of the behavior of the virtual library (VL) users. Unlike the models presented in the literature, they use only the big data that is stored in the log files of virtual library servers and methods of statistics, association rules, and recommendation systems. The proposed models were implemented with R software. Using the proposed models, the analysis of the behavior of VL users of Lithuanian research and study of higher education institutions was performed for the first time. The results showed that the proposed models allow to operatively analyze the behavior of virtual library users using advanced search filters, facets, and provide suggestions for improvement of service quality. https://www.zurnalai.vu.lt/LMR/article/view/22521virtual librarybehavior of usersstatisticsbig dataassociation rulesrecommender systems |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Gytis Vievesis Vytautas Janilionis Antanas Štreimikis |
spellingShingle |
Gytis Vievesis Vytautas Janilionis Antanas Štreimikis Models of virtual library users’ behavior analysis Lietuvos Matematikos Rinkinys virtual library behavior of users statistics big data association rules recommender systems |
author_facet |
Gytis Vievesis Vytautas Janilionis Antanas Štreimikis |
author_sort |
Gytis Vievesis |
title |
Models of virtual library users’ behavior analysis |
title_short |
Models of virtual library users’ behavior analysis |
title_full |
Models of virtual library users’ behavior analysis |
title_fullStr |
Models of virtual library users’ behavior analysis |
title_full_unstemmed |
Models of virtual library users’ behavior analysis |
title_sort |
models of virtual library users’ behavior analysis |
publisher |
Vilnius University Press |
series |
Lietuvos Matematikos Rinkinys |
issn |
0132-2818 2335-898X |
publishDate |
2021-02-01 |
description |
In this paper, we present models for the analysis of the behavior of the virtual library (VL) users. Unlike the models presented in the literature, they use only the big data that is stored in the log files of virtual library servers and methods of statistics, association rules, and recommendation systems. The proposed models were implemented with R software. Using the proposed models, the analysis of the behavior of VL users of Lithuanian research and study of higher education institutions was performed for the first time. The results showed that the proposed models allow to operatively analyze the behavior of virtual library users using advanced search filters, facets, and provide suggestions for improvement of service quality.
|
topic |
virtual library behavior of users statistics big data association rules recommender systems |
url |
https://www.zurnalai.vu.lt/LMR/article/view/22521 |
work_keys_str_mv |
AT gytisvievesis modelsofvirtuallibraryusersbehavioranalysis AT vytautasjanilionis modelsofvirtuallibraryusersbehavioranalysis AT antanasstreimikis modelsofvirtuallibraryusersbehavioranalysis |
_version_ |
1724261410451488768 |