The Analysis of the eLABa Virtual Libraries’ Users Data

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Session Abstract

The aim of this presentation is to demonstrate the possibilities and benefits of the Lithuanian Academic Electronic Library (eLABa) institutional virtual libraries’ (IVL) users’ data analysis. The results of this analysis could be later used in improving services provided by IVL. The behavior analysis of IVL users includes only the big data about the actions of users during IVL sessions automatically collected in IVL Apache logs. The analysis consists of the following parts: exploratory data analysis, segmentation, search and result filter analysis, and development of recommendation systems. Data mining methods and R programming language were used in the analysis of IVL users’ data. The results of user segmentation revealed the differences in behavior of various IVL users. This allowed to specify IVL areas for improvement and to better understand the needs of IVL users. For instance, to better organize the search result filters in IVL user interface.

Conference or Developers' Day

Track

Applicable Ex Libris Product

Target Audience Skill Level

Registration

Co-Presenters

Antanas Streimikis, Kaunas University of Technology

Co-presenter's job title

Head of Library Information Systems Office

Vytautas Janilionis, Kaunas University of Technology

Co-presenter's job title

Associate Professor

2020 Digital Conference and Developers Day

September 14–17, 2020