Determining the optimal session interval for transaction log analysis of an online library catalogue

Simon Wakeling, Paul Clough

Research output: Book chapter/Published conference paperConference paper

2 Citations (Scopus)

Abstract

Transaction log analysis at the level of a session is commonly used as a means of understanding user-system interactions. A key practical issue in the process of conducting session level analysis is the segmentation of the logs into appropriate user sessions (i.e., sessionisation). Methods based on time intervals are frequently used as a simple and convenient means of carrying out this segmentation task. However, little work has been carried out to determine whether the commonly applied 30-minute period is appropriate, particularly for the analysis of search logs from library catalogues. Comparison of a range session intervals with human judgements demonstrate that the overall accuracy of session segmentation is relatively constant for session intervals between 26 to 57 min. However, a session interval of between 25 and 30 min minimises the chances of one error type (incorrect collation or incorrect segmentation) predominating.
Original languageEnglish
Title of host publicationProceedings of the 38th European Conference on Information Retrieval (ECIR)
PublisherSpringer-Verlag London Ltd.
Pages703-708
Number of pages6
ISBN (Print)9783319306704
DOIs
Publication statusPublished - 2016
Event38th European Conference on Information Retrieval: ECIR 2016 - University of Padova, Padua, Italy
Duration: 20 Mar 201623 Mar 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9626

Conference

Conference38th European Conference on Information Retrieval
CountryItaly
CityPadua
Period20/03/1623/03/16

Cite this

Wakeling, S., & Clough, P. (2016). Determining the optimal session interval for transaction log analysis of an online library catalogue. In Proceedings of the 38th European Conference on Information Retrieval (ECIR) (pp. 703-708). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9626). Springer-Verlag London Ltd.. https://doi.org/10.1007/978-3-319-30671-1_56