IDEAS home Printed from https://ideas.repec.org/a/spr/infosf/v12y2010i5d10.1007_s10796-009-9199-3.html
   My bibliography  Save this article

Personalisation in web computing and informatics: Theories, techniques, applications, and future research

Author

Listed:
  • Min Gao

    (Chongqing University)

  • Kecheng Liu

    (University of Reading)

  • Zhongfu Wu

    (Chongqing University)

Abstract

Recently, personalised search engines and recommendation systems have been widely adopted by users who require assistance in searching, classifying, and filtering information. This paper presents an overview of the field of personalisation systems and describes current state-of-the-art methods and techniques. It reviews approaches for (1) user profiling, including behaviour, preference, and intention modelling; (2) content modelling, comprising content representation, analysis, and classification; and (3) filtering methods for recommendation, classified into four main categories: rule-based, content-based, collaborative, and hybrid filtering. The paper also discusses personalisation systems in different domains, and various techniques and their limitations. Finally, it identifies several issues and possible directions for further research that can improve recommendation capabilities and enhance personalised systems.

Suggested Citation

  • Min Gao & Kecheng Liu & Zhongfu Wu, 2010. "Personalisation in web computing and informatics: Theories, techniques, applications, and future research," Information Systems Frontiers, Springer, vol. 12(5), pages 607-629, November.
    • Handle: RePEc:spr:infosf:v:12:y:2010:i:5:d:10.1007_s10796-009-9199-3
    DOI: 10.1007/s10796-009-9199-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10796-009-9199-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10796-009-9199-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. B. P. S. Murthi & Sumit Sarkar, 2003. "The Role of the Management Sciences in Research on Personalization," Management Science, INFORMS, vol. 49(10), pages 1344-1362, October.
    2. Trf, 1999. "Table of contents," 41st Annual Transportation Research Forum, Washington, D.C., September 30-October 1, 1999 311984, Transportation Research Forum.
    3. de Moor, A. & Keeler, M. & Richmond, G., 2002. "Towards a pragmatic web," Other publications TiSEM 1267c5f6-e734-4e1f-8e0f-a, Tilburg University, School of Economics and Management.
    4. Chong Ju Choi & Carla C. J. M. Millar & Caroline Y. L. Wong, 2005. "Knowledge and the State," Palgrave Macmillan Books, in: Knowledge Entanglements, chapter 0, pages 19-38, Palgrave Macmillan.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Geissler, Dominik & Beiderbeck, Daniel & Schmidt, Sascha L. & Schreyer, Dominik, 2024. "Emerging technologies and shifting consumer motives: Projecting the future of the top-tier sports media product," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    2. Jun Sun, 2020. "Ubiquitous Computing Capabilities and User-System Interaction Readiness: An Activity Perspective," Information Systems Frontiers, Springer, vol. 22(1), pages 259-271, February.
    3. Felipe Thomaz & Carolina Salge & Elena Karahanna & John Hulland, 2020. "Learning from the Dark Web: leveraging conversational agents in the era of hyper-privacy to enhance marketing," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 43-63, January.
    4. Wang, Wei-Tsong & Ou, Wei-Ming & Chen, Wen-Yin, 2019. "The impact of inertia and user satisfaction on the continuance intentions to use mobile communication applications: A mobile service quality perspective," International Journal of Information Management, Elsevier, vol. 44(C), pages 178-193.
    5. Chulhwan Chris Bang, 2015. "Information systems frontiers: Keyword analysis and classification," Information Systems Frontiers, Springer, vol. 17(1), pages 217-237, February.
    6. Elnivan Moreira de Souza & Paulo César de Sousa Batista, 2017. "Strategic Antecedents and Consequents for the Performance of E-Business Companies," Brazilian Business Review, Fucape Business School, vol. 14(1), pages 59-85, January.
    7. Bipul Kumar & Pradip Kumar Bala, 2020. "Cosine based latent factor model for ranking the recommendation," Operational Research, Springer, vol. 20(1), pages 297-317, March.
    8. Wei-Tsong Wang & Wen-Hung Chang, 2014. "A study of virtual product consumption from the expectancy disconfirmation and symbolic consumption perspectives," Information Systems Frontiers, Springer, vol. 16(5), pages 887-908, November.
    9. Vinodh Krishnaraju & Saji K Mathew & Vijayan Sugumaran, 2016. "Web personalization for user acceptance of technology: An empirical investigation of E-government services," Information Systems Frontiers, Springer, vol. 18(3), pages 579-595, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shuk Ying Ho & David Bodoff & Kar Yan Tam, 2011. "Timing of Adaptive Web Personalization and Its Effects on Online Consumer Behavior," Information Systems Research, INFORMS, vol. 22(3), pages 660-679, September.
    2. Felipe Thomaz & Carolina Salge & Elena Karahanna & John Hulland, 2020. "Learning from the Dark Web: leveraging conversational agents in the era of hyper-privacy to enhance marketing," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 43-63, January.
    3. Kartik Hosanagar & Daniel Fleder & Dokyun Lee & Andreas Buja, 2014. "Will the Global Village Fracture Into Tribes? Recommender Systems and Their Effects on Consumer Fragmentation," Management Science, INFORMS, vol. 60(4), pages 805-823, April.
    4. Huosong Xia & Xiang Wei & Wuyue An & Zuopeng Justin Zhang & Zelin Sun, 2021. "Design of electronic-commerce recommendation systems based on outlier mining," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(2), pages 295-311, June.
    5. Daniel Fleder & Kartik Hosanagar & Andreas Buja, 2008. "Recommender Systems and their Effects on Consumers: The Fragmentation Debate," Working Papers 08-44, NET Institute, revised Mar 2010.
    6. Arup Roy & Soumya Banerjee & Chintan Bhatt & Youakim Badr & Saurav Mallik, 2018. "Hybrid Group Recommendation Using Modified Termite Colony Algorithm: A Context Towards Big Data," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 17(02), pages 1-31, June.
    7. Yicheng Song & Nachiketa Sahoo & Elie Ofek, 2019. "When and How to Diversify—A Multicategory Utility Model for Personalized Content Recommendation," Management Science, INFORMS, vol. 65(8), pages 3737-3757, August.
    8. Oliver Hinz & Jochen Eckert, 2010. "The Impact of Search and Recommendation Systems on Sales in Electronic Commerce," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 2(2), pages 67-77, April.
    9. Xiao-Bai Li & Jialun Qin, 2017. "Anonymizing and Sharing Medical Text Records," Information Systems Research, INFORMS, vol. 28(2), pages 332-352, June.
    10. Lawrence Bunnell & Kweku-Muata Osei-Bryson & Victoria Y. Yoon, 0. "RecSys Issues Ontology: A Knowledge Classification of Issues for Recommender Systems Researchers," Information Systems Frontiers, Springer, vol. 0, pages 1-42.
    11. Xi Chen & Zachary Owen & Clark Pixton & David Simchi-Levi, 2022. "A Statistical Learning Approach to Personalization in Revenue Management," Management Science, INFORMS, vol. 68(3), pages 1923-1937, March.
    12. Martinovici, A., 2019. "Revealing attention - how eye movements predict brand choice and moment of choice," Other publications TiSEM 7dca38a5-9f78-4aee-bd81-c, Tilburg University, School of Economics and Management.
    13. Joanna Sokolowska & Patrycja Sleboda, 2015. "The Inverse Relation Between Risks and Benefits: The Role of Affect and Expertise," Risk Analysis, John Wiley & Sons, vol. 35(7), pages 1252-1267, July.
    14. Donald R. Haurin & Stuart S. Rosenthal, 2009. "Language, Agglomeration and Hispanic Homeownership," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 37(2), pages 155-183, June.
    15. Jong Won Min, 2019. "The Influence of Stigma and Views on Mental Health Treatment Effectiveness on Service Use by Age and Ethnicity: Evidence From the CDC BRFSS 2007, 2009, and 2012," SAGE Open, , vol. 9(3), pages 21582440198, September.
    16. Zhan (Michael) Shi & T. S. Raghu, 2020. "An Economic Analysis of Product Recommendation in the Presence of Quality and Taste-Match Heterogeneity," Information Systems Research, INFORMS, vol. 31(2), pages 399-411, June.
    17. Voxi Amvilah & Simplice Anutechia Asongu & Antonio Andrés, 2014. "Globalization, Peace & Stability, Governance, and Knowledge Economy," AAYE Policy Research Working Paper Series 14_024, Association of African Young Economists, revised Dec 2014.
    18. Alwang, Jeffrey & Larochelle, Catherine & Barrera, Victor, 2017. "Farm Decision Making and Gender: Results from a Randomized Experiment in Ecuador," World Development, Elsevier, vol. 92(C), pages 117-129.
    19. Yanina Welp & Ferran Urgell & Eduard Aibar, 2007. "From Bureaucratic Administration to Network Administration? An Empirical Study on E-Government Focus on Catalonia," Public Organization Review, Springer, vol. 7(4), pages 299-316, December.
    20. Fay, Scott & Mitra, Deb & Wang, Qiong, 2009. "Ask or infer? Strategic implications of alternative learning approaches in customization," International Journal of Research in Marketing, Elsevier, vol. 26(2), pages 136-152.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:infosf:v:12:y:2010:i:5:d:10.1007_s10796-009-9199-3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.