Obtaining subject data from log files using deep log analysis: case study OhioLINK

被引:8
|
作者
Huntington, Paul [1 ]
Nicholas, David [1 ]
Jamali, Hamid R. [1 ]
Watkinson, Anthony [1 ]
机构
[1] UCL, SLAIS, London WC1E 6BT, England
关键词
transaction log analysis; electronic periodicals; use statistics; OhioLINK; user behaviour;
D O I
10.1177/0165551506065782
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Traditionally web site statistics and analysis focus on the organization and location information of Internet Protocol addresses and do not analyse sub-network and computer-label information. This paper aims to extract and make use of the information content of sub-network labels in transactional server log files and add an additional level to transaction log analysis. The authors apply microanalytical procedures (i.e. analysis of small segments and sections of log files) to the analysis of log files of the OhioLINK electronic journal service. The authors demonstrate an analysis based on extracted sub-network information and argue that these names can be interpreted as departmental (subject) names. They present an analysis between journal subject groupings and departments based on sub-network labels and find a degree of correlation between department name and subject of journal use. Further, the authors break down journal usage by sub-network label information. The analyses show that sub-network names reflect the physical location of the computer. This presents another possibility of analysing what journals are being used by which academic department.
引用
收藏
页码:299 / 308
页数:10
相关论文
共 50 条
  • [41] Automatic discovery of the sequential accesses from web log data files via a genetic algorithm
    Tug, Emine
    Sakiroglu, Merve
    Arslan, Ahmet
    KNOWLEDGE-BASED SYSTEMS, 2006, 19 (03) : 180 - 186
  • [42] Case of Process Mining from Business Execution Log Data
    Bae, Joonsoo
    Kang, Young Ki
    INTELLIGENT DECISION TECHNOLOGIES (IDT'2012), VOL 1, 2012, 15 : 419 - 425
  • [43] Analysis of visitor's behavior from Web Log using Web Log Expert Tool
    Kumar, Manoj
    Meenu
    2017 INTERNATIONAL CONFERENCE OF ELECTRONICS, COMMUNICATION AND AEROSPACE TECHNOLOGY (ICECA), VOL 2, 2017, : 296 - 301
  • [44] Classification of Well Log Data Using Vanishing Component Analysis
    Umar Hayat
    Aamir Ali
    Ghulam Murtaza
    Matee Ullah
    Ikram Ullah
    Álvaro Nolla de Celis
    Nasir Rajpoot
    Pure and Applied Geophysics, 2020, 177 : 2719 - 2737
  • [45] A Study on Log Analysis Approaches Using Sandia Dataset
    Pritom, Mir Mehedi A.
    Li, Chuqin
    Chu, Bill
    Niu, Xi
    2017 26TH INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATION AND NETWORKS (ICCCN 2017), 2017,
  • [46] Classification of Well Log Data Using Vanishing Component Analysis
    Hayat, Umar
    Ali, Aamir
    Murtaza, Ghulam
    Ullah, Matee
    Ullah, Ikram
    Nolla de Celis, Alvaro
    Rajpoot, Nasir
    PURE AND APPLIED GEOPHYSICS, 2020, 177 (06) : 2719 - 2737
  • [47] Prediction and classification of VMAT dosimetric accuracy using plan complexity and log-files analysis
    Cilla, Savino
    Viola, Pietro
    Romano, Carmela
    Craus, Maurizio
    Buwenge, Milly
    Macchia, Gabriella
    Valentini, Vincenzo
    Deodato, Francesco
    Morganti, Alessio G.
    PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS, 2022, 103 : 76 - 88
  • [48] Analysis of delivered dose differences due to MLC errors using dynamic MLC log files
    Onses, A.
    Puxeu, J.
    Sancho, I.
    Picon, C.
    RADIOTHERAPY AND ONCOLOGY, 2015, 115 : S784 - S784
  • [49] Response to Discussion of "Analysis of Radial Consolidation Test Data Using a Log-Log Method" by Robinson, RG
    Robinson, Retnamony G.
    GEOTECHNICAL TESTING JOURNAL, 2010, 33 (02): : 169 - 169
  • [50] Analysis of Log Files to Enable Smart-Troubleshooting in Industry 4.0: A Systematic Mapping Study
    Partovian, Sania
    Bucaioni, Alessio
    Flammini, Francesco
    Thornadtsson, Johan
    IEEE ACCESS, 2024, 12 : 147640 - 147658