Personalization of Search Results Representation of a Digital Library
The process of discovering appropriate resources in digital libraries within universities is important, as it can have a big effect on whether retrieved works are useful to the requester. The improvement of the user experience with the digital library of the University of Novi Sad dissertations (PHD UNS) through the personalization of search results representation is the aim of the research presented in this paper. There are three groups of PHD UNS digital library users: users from the academic community, users outside the academic community, and librarians who are in charge of entering dissertation data. Different types of textual and visual representations were analyzed, and representations which needed to be implemented for the groups of users of PHD UNS digital library were selected. After implementing these representations and putting them into operation in April 2017, the user interface was extended with functionality that allows users to select their desired style for representing search results using an additional module for storing message logs. The stored messages represent an explicit change in the results representation by individual users. Using these message logs and ELK technology stack, we analyzed user behavior patterns depending on the type of query, type of device, and search mode. The analysis has shown that the majority of users of the PHD UNS system prefer using the textual style of representation rather than the visual. Some users have changed the style of results representation several times and it is assumed that different types of information require a different representation style. Also, it has been established that the most frequent change to the visual results representation occurs after users perform a query which shows all the dissertations from a certain time period and which is taken from the advanced search mode; however, there is no correlation between this change and the client’s device used.
A. F. Smeaton and J. Callan, “Personalisation and Recommender Systems in Digital Libraries,” International Journal on Digital Libraries 5, no. 4 (2005): 299–308, https://doi.org/10.1007/s00799-004-0100-1.
Byron Kuo, Thomas Hentrich, Benjamin Good, and Mark Wilkinson, “Tag Clouds for Summarizing Web Search Results,” in Proceedings of the 16th International Conference on World Wide Web (WWW '07) (2007): 1203–04, https://doi.org/10.1145/1242572.1242766.
Carmel McNaught and Paul Lam, “Using Wordle as a Supplementary Research Tool,” The Qualitative Report 15, no. 3 (2010): 630.
Cristiane Behnert and Dirk Lewandowski, “Ranking Search Results in Library Information Systems—Considering Ranking Approaches Adapted from Web Search Engines,” The Journal of Academic Librarianship 41 no. 6 (2015): 725–35, https://doi.org/10.1016/j.acalib.2015.07.010.
D. Ivanović, G. Milosavljević, B. Milosavljević, and D. Surla, “A CERIF-compatible Research Management System based on the MARC 21 Format,” Program: Electronic Library and Information Systems 44, no. 1 (2010): 229–51.
Daniel Scanfeld, Vanessa Scanfeld, and Elaine L. Larson, “Dissemination of Health Information through Social Networks: Twitter and Antibiotics,” American Journal of Infection Control 38, no. 3 (2010): 182–88, https://doi.org/10.1016/j.ajic.2009.11.004.
Dragan Ivanović and Branko Milosavljević, “Software Architecture of System of Bibliographic Data,” in Proceedings of the XXI Conference on Applied Mathematics PRIM 2009, 85–94.
Dragan Ivanović and Georgia Kapitsaki, “Personalisation of Keyword-based Search on Structured Data Sources,” in Proceedings of the 1st International KEYSTONE Conference (IKC 2015).
Dragan Ivanović, “A Scientific-research Activities Information System,” (PhD thesis, University of Novi Sad, 2010).
Dragan Ivanović, “Software Systems for Increasing Availability of Scientific-research Outputs,” Novi Sad Journal of Mathematics – NS JOM 42, no. 1 (2012): 37–48.
Dragan Ivanović, Dušan Surla, and Zora Konjović, “CERIF Compatible Data Model Based on MARC 21 Format,” The Electronic Library 29, no. 1 (2011): 52–70, https://doi.org/10.1108/02640471111111433.
Enrique Frias-Martinez, Chen Sherry, and Liu Xiaohui, “Evaluation of a Personalised Digital Library based on Cognitive Styles: Adaptivity vs. Aadaptability,” International Journal of Information Management 29 no. 1 (2009): 48–56, https://doi.org/10.1016/j.ijinfomgt.2008.01.012.
Enrique Frias-Martinez, George Magoulas, Chen Sherry, and Robert Macredie, “Automated User Modeling for Personalised Digital Libraries,” International Journal of Information Management 26 no. 3 (2006): 234–48, https://doi.org/10.1016/j.ijinfomgt.2006.02.006.
Frank H. Bowers and Stuart K. Card, “Method and Apparatus for Visualization of Database Search Results,” U.S. Patent no. 5,546,529.
Georgia Kapitsaki and Dragan Ivanović, “Representation with Word Clouds at the PHD UNS Digital Library,” Computer Science & Information Technology 21 (2017), https://doi.org/10.5121/csit.2017.71102.
Georgia M. Kapitsaki, George N. Prezerakos, Nikolaos D. Tselikas, and Iakovos S. Venieris, “Context-aware Service Engineering: A Survey,” Journal of Systems and Software 82 No. 8 (2009): 1285–97, https://doi.org/10.1016/j.jss.2009.02.026.
Gregory D. Abowd et al., “Towards a Better Understanding of Context and Context-awareness,” in Handheld and Ubiquitous Computing (Springer: Berlin/Heidelberg, 1999): 304–07, https://doi.org/10.1007/3-540-48157-5_29.
Hema Yoganarasimhan, “Search Personalization using Machine Learning,” Management Science 66 no. 3 (2020): 1045–70, https://doi.org/10.1287/mnsc.2018.3255.
Iris Xie, Soohyung Joo, and Krystyna K. Matusiak, “Multifaceted Evaluation Criteria of Digital Libraries in Academic Settings: Similarities and Differences from Different Stakeholders,” The Journal of Academic Librarianship 44, no. 6 (2018): 854–63, https://doi.org/10.1016/j.acalib.2018.09.002.
J. Brophy and D. Bawden, “Is Google Enough? Comparison of an Internet Search Engine with Academic Library Resources,” Aslib Proceedings 57, no. 6 (2005): 498–512, https://doi.org/10.1108/00012530510634235.
Joel Azzopardi, Dragan Ivanović and Georgia Kapitsaki, “Comparison of Collaborative and Content-Based Automatic Recommendation Approaches in a Digital Library of Serbian PhD Dissertations,” in Proceedings of the International KEYSTONE Conference 2016: 100–11, https://doi.org/10.1007/978-3-319-53640-8_9
Joel Azzopardi, Dragan Ivanović and Georgia Kapitsaki, “Comparison of Collaborative and Content-Based Automatic Recommendation Approaches in a Digital Library of Serbian PhD Dissertations,” in Proceedings of the International KEYSTONE Conference 2016: 100–11, https://doi.org/10.1007/978-3-319-53640-8_9.
Jong-yi Hong, Eui-ho Suh, and Sung-Jin Kim, “Context-aware Systems: A Literature Review and Classification,” Expert Systems with Applications 36, no. 4 (2009): 8509–22, https://doi.org/10.1016/j.eswa.2008.10.071.
Josef Fink and Alfred Kobsa, “A Review and Analysis of Commercial User Modeling Servers for Personalisation on the World Wide Web,” User Modeling and User-Adapted Interaction 10, no. 2 (2000): 209–49, https://doi.org/10.1023/A:1026597308943.
Lidija Ivanović and Dušan Surla, “A Software Module for Import of Theses and Dissertations to CRISs,” in Proceedings of the CRIS 2012 Conference, (Prague, June 6–9, 2012): 313–22.
Lidija Ivanovic, “Search of catalogues of theses and dissertations,” Novi Sad Journal of Mathematics – NS JOM, 43, no. 1 (2013): 155–65.
Lidija Ivanović, Dragan Ivanović and Dušan Surla, “Integration of a Research Management System and an OAI-PMH Compatible ETDs Repository at the University of Novi Sad, Republic of Serbia,” Library Resources & Technical Services 56, no. 2: 104–12, https://doi.org/10.5860/lrts.56n2.104.
Lidija Ivanović, Dragan Ivanović, and Dušan Surla, “A Data Model of Theses and Dissertations Compatible with CERIF, Dublin Core and EDT-MS,” Online Information Review 36, no. 4: 548–67, https://doi.org/10.1108/14684521211254068.
Lidija Ivanović, Dragan Ivanović, Dušan Surla and Zora Konjović, “User interface of web application for searching PhD dissertations of the University of Novi Sad,” in Proceedings of the Intelligent Systems and Informatics (SISY), 2013 IEEE 11th International Symposium: 117–22.
Magda El-Sherbini and George Klim, “Metadata and Cataloging Practices,” The Electronic Library 22 no. 3 (2004): 238–48, https://doi.org/10.1108/02640470410541633.
Mark M. Sebrechts et al., “Visualization of Search Results: A Comparative Evaluation of Text, 2D, and 3D Interfaces,” in Proceedings of the 22nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '99): 3–10, https://doi.org/10.1145/312624.312634.
Mika Raento, Antti Oulasvirta, Renaud Petit and Hannu Toivonen, “ContextPhone: A Prototyping Platform for Context-aware Mobile Applications,” IEEE Pervasive Computing 4 no. 2 (2005): 51–59, https://doi.org/10.1109/MPRV.2005.29.
Núria Ferran, Enric Mor, and Julià Minguillón, “Towards Personalization in Digital Libraries through Ontologies,” Library Management 26, no. 4/5 (2005): 206–17, https://doi.org/10.1108/01435120510596062.
Sai Deng and Terry Reese, “Customized Mapping and Metadata Transfer from DSpace to OCLC to Improve ETD Workflow,” New Library World, 2009, 110, no. 5/6 (2009): 249–64, https://doi.org/10.1108/03074800910954271.
Sara Saad Soliman, Maged F. El-Sayed, and Yasser F. Hassan, “Semantic Clustering of Search Engine Results,” The Scientific World Journal (2015), https://doi.org/10.1155/2015/931258.
Shawn Averkamp and Joanna Lee, “Repurposing ProQuest Metadata for Batch Ingesting ETDs into an Institutional Repository” (University Libraries Staff Publications, 2009): 38.
Steffen Lohmann, Jürgen Ziegler, and Lena Tetzlaff, “Comparison of Tag Cloud Layouts: Task-related Performance and Visual Exploration,” in Proceedings of the IFIP Conference on Human-Computer Interaction (2009): 392–404, https://doi.org/10.1007/978-3-642-03655-2_43.
Theodora Nanou, George Lekakos, and Konstantinos Fouskas, “The Effects of Recommendations’ Presentation on Persuasion and Satisfaction in a Movie Recommender System,” Multimedia Systems 16, No. 4–5 (August 2010): 219–30, https://doi.org/10.1007/s00530-010-0190-0.
Tien Nguyen and Jin Zhang, “A Novel Visualization Model for Web Search Results,” IEEE Transactions on Visualization and Computer Graphics, 12, no. 5 (2006), https://doi.org/10.1109/TVCG.2006.111.
Weiwei Cui et al., “Context Preserving Dynamic Word Cloud Visualization,” in IEEE Pacific Visualization Symposium (PacificVis) (2010): 121–28, https://doi.org/10.1109/PACIFICVIS.2010.5429600.
Yuping Jin, “Development of Word Cloud Generator Software based on Python,” Procedia Engineering 174 (2017): 788–92, https://doi.org/10.1016/j.proeng.2017.01.223.
Yusef Hassan-Montero and Herrero-Victor Solana, “Improving Tag-clouds as Visual Information Retrieval Iinterfaces,” in Proceedings of the International Conference on Multidisciplinary Information Sciences and Technologies (2006): 25–28.
Copyright (c) 2021 Ljubomir Paskali, Lidija Ivanovic, Georgia Kapitsaki, Dragan Ivanovic, Bojana Dimic Surla, Dusan Surla
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.