IDEAS home Printed from https://ideas.repec.org/a/spr/elmark/v29y2019i2d10.1007_s12525-018-0297-2.html
   My bibliography  Save this article

Fractional stochastic gradient descent for recommender systems

Author

Listed:
  • Zeshan Aslam Khan

    (International Islamic University)

  • Naveed Ishtiaq Chaudhary

    (International Islamic University)

  • Syed Zubair

    (International Islamic University)

Abstract

Recently, recommender systems are getting popular in the e-commerce industry for retrieving and recommending most relevant information about items for users from large amounts of data. Different stochastic gradient descent (SGD) based adaptive strategies have been proposed to make recommendations more precise and efficient. In this paper, we propose a fractional variant of the standard SGD, named as fractional stochastic gradient descent (FSGD), for recommender systems. We compare its convergence and estimated accuracy with standard SGD against a number of features with different learning rates and fractional orders. The performance of our proposed method is evaluated using the root mean square error (RMSE) as a quantitative evaluation measure. We examine that the proposed strategy is more accurate in terms of RMSE than the standard SGD for all values of fractional orders and different numbers of features. The contribution of fractional calculus has not been explored yet to solve the recommender systems problem; therefore, we exploit FSGD for solving this problem. The results show that our proposed method performs significantly well in terms of estimated accuracy and convergence as compared to the standard SGD.

Suggested Citation

  • Zeshan Aslam Khan & Naveed Ishtiaq Chaudhary & Syed Zubair, 2019. "Fractional stochastic gradient descent for recommender systems," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(2), pages 275-285, June.
  • Handle: RePEc:spr:elmark:v:29:y:2019:i:2:d:10.1007_s12525-018-0297-2
    DOI: 10.1007/s12525-018-0297-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12525-018-0297-2
    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/s12525-018-0297-2?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. Heimbach, Irina & Gottschlich, Jörg & Hinz, Oliver, 2015. "The Value of User's Facebook Profile Data for Product Recommendation Generation," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 77135, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    2. Chen, Dali & Chen, YangQuan & Xue, Dingyu, 2015. "Fractional-order total variation image denoising based on proximity algorithm," Applied Mathematics and Computation, Elsevier, vol. 257(C), pages 537-545.
    3. Hasan Bulut & Haci Mehmet Baskonus & Yusuf Pandir, 2013. "The Modified Trial Equation Method for Fractional Wave Equation and Time Fractional Generalized Burgers Equation," Abstract and Applied Analysis, Hindawi, vol. 2013, pages 1-8, September.
    4. Sebastian Köhler & Thomas Wöhner & Ralf Peters, 2016. "The impact of consumer preferences on the accuracy of collaborative filtering recommender systems," Electronic Markets, Springer;IIM University of St. Gallen, vol. 26(4), pages 369-379, November.
    5. 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. Chaudhary, Naveed Ishtiaq & Khan, Zeshan Aslam & Kiani, Adiqa Kausar & Raja, Muhammad Asif Zahoor & Chaudhary, Iqra Ishtiaq & Pinto, Carla M.A., 2022. "Design of auxiliary model based normalized fractional gradient algorithm for nonlinear output-error systems," Chaos, Solitons & Fractals, Elsevier, vol. 163(C).
    2. Yin Zhang & Haider Abbas & Yi Sun, 2019. "Smart e-commerce integration with recommender systems," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(2), pages 219-220, June.
    3. Khan, Zeshan Aslam & Chaudhary, Naveed Ishtiaq & Raja, Muhammad Asif Zahoor, 2022. "Generalized fractional strategy for recommender systems with chaotic ratings behavior," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    4. Yunqi Jiang & Huaqing Zhang & Kai Zhang & Jian Wang & Shiti Cui & Jianfa Han & Liming Zhang & Jun Yao, 2022. "Reservoir Characterization and Productivity Forecast Based on Knowledge Interaction Neural Network," Mathematics, MDPI, vol. 10(9), pages 1-22, May.
    5. Chaudhary, Naveed Ishtiaq & Raja, Muhammad Asif Zahoor & Khan, Zeshan Aslam & Mehmood, Ammara & Shah, Syed Muslim, 2022. "Design of fractional hierarchical gradient descent algorithm for parameter estimation of nonlinear control autoregressive systems," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    6. Ravi S. Sharma & Aijaz A. Shaikh & Eldon Li, 2021. "Designing Recommendation or Suggestion Systems: looking to the future," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(2), pages 243-252, June.
    7. Naveed Ahmed Malik & Ching-Lung Chang & Naveed Ishtiaq Chaudhary & Muhammad Asif Zahoor Raja & Khalid Mehmood Cheema & Chi-Min Shu & Sultan S. Alshamrani, 2022. "Knacks of Fractional Order Swarming Intelligence for Parameter Estimation of Harmonics in Electrical Systems," Mathematics, MDPI, vol. 10(9), pages 1-20, May.
    8. Farah Tawfiq Abdul Hussien & Abdul Monem S. Rahma & Hala B. Abdulwahab, 2021. "An E-Commerce Recommendation System Based on Dynamic Analysis of Customer Behavior," Sustainability, MDPI, vol. 13(19), pages 1-21, September.
    9. Khan, Zeshan Aslam & Chaudhary, Naveed Ishtiaq & Khan, Taimoor Ali & Farooq, Umair & Pinto, Carla M.A. & Raja, Muhammad Asif Zahoor, 2023. "Enhanced fractional prediction scheme for effective matrix factorization in chaotic feedback recommender systems," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).

    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. 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.
    2. Payam Hanafizadeh & Mahdi Barkhordari Firouzabadi & Khuong Minh Vu, 2021. "Insight monetization intermediary platform using recommender systems," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(2), pages 269-293, June.
    3. Khan, Zeshan Aslam & Chaudhary, Naveed Ishtiaq & Raja, Muhammad Asif Zahoor, 2022. "Generalized fractional strategy for recommender systems with chaotic ratings behavior," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    4. Ravi S. Sharma & Aijaz A. Shaikh & Eldon Li, 2021. "Designing Recommendation or Suggestion Systems: looking to the future," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(2), pages 243-252, June.
    5. 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.
    6. Xiao-Bai Li & Jialun Qin, 2017. "Anonymizing and Sharing Medical Text Records," Information Systems Research, INFORMS, vol. 28(2), pages 332-352, June.
    7. Knox, George & Datta, Hannes, 2020. "Streaming Services and the Homogenization of Music Consumption," Other publications TiSEM 0e4d6202-dcc5-4834-ba93-a, Tilburg University, School of Economics and Management.
    8. Dimitrov, Kiril, 2012. "Natural analogies among organizational culture models," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 5(1), pages 99-125.
    9. Fanjuan Shi & Jean-Luc Marini, 2014. "Do we need to believe Data/Tangible or Emotional/Intuition?," Post-Print halshs-01065283, HAL.
    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. Oana TUGULEA, 2015. "Different Web Credibility Assessment As A Result Of One Year Difference In Education. A Study On The Dimensions Of Credibility Of Commercial Presentation Websites," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 16, pages 117-133, December.
    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. Perkmann, Markus & Salandra, Rossella & Tartari, Valentina & McKelvey, Maureen & Hughes, Alan, 2021. "Academic engagement: A review of the literature 2011-2019," Research Policy, Elsevier, vol. 50(1).
    14. Yan Chen & F. Maxwell Harper & Joseph Konstan & Sherry Xin Li, 2010. "Social Comparisons and Contributions to Online Communities: A Field Experiment on MovieLens," American Economic Review, American Economic Association, vol. 100(4), pages 1358-1398, September.
    15. 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.
    16. Fischer, Leonie & Heckemeyer, Jost H. & Spengel, Christoph & Steinbrenner, Daniela, 2021. "Tax policies in a transition to a knowledge-based economy: The effective tax burden of companies and highly skilled labour," ZEW Discussion Papers 21-096, ZEW - Leibniz Centre for European Economic Research.
    17. 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.
    18. 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.
    19. 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.
    20. Voxi Amavilah & Antonio R. Andrés, 2014. "Globalization, Peace & Stability, Governance, and Knowledge Economy," Research Africa Network Working Papers 14/012, Research Africa Network (RAN).

    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:elmark:v:29:y:2019:i:2:d:10.1007_s12525-018-0297-2. 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.