IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v13y2022i1d10.1007_s13198-021-01537-6.html
   My bibliography  Save this article

A recommender system based on collaborative filtering, graph theory using HMM based similarity measures

Author

Listed:
  • Anshul Gupta

    (NMIMS University)

  • Pravin Srinath

    (NMIMS University)

Abstract

Collaborative filtering (CF) is a widely used method in recommendation systems (RS). In the CF, similar users' interests and preferences are analyzed and items that they might be interested in are recommended. However, the RS suggests items without maintaining the proper order (sequence) assuming that in the next purchasing user may select any single item from the list of recommended items. This limits the scope of the RS to a single future event, which does not match with the natural behavior of the users who generally purchase multiple items together in a specific sequence. Therefore in this paper, a more realistic RS is proposed which suggests a list of items in a proper sequence that users may purchase together. Since making such RS also required to measure the similarity among the users considering their sequential (temporal) purchasing behavior. The temporal similarity among the users could be calculated using a graph-based approach. However, this could lead to an NP-complete computational problem. Hence, to overcome this limitation, we also proposed an HMM-based approach that utilized the EMISSION Matrix to estimate the sequential similarity among the users. The EMISSION Matrix used with the proposed algorithm is a part of HMM (Hidden Markov Model). In HMM the EMISSION matrix is used to estimate the possibility of emission of a particular symbol from a process. In the presented work, the process is mapped with the user and the symbol with the selected item. Matching the EMISSION matrix of users' item selection process provides an improved similarity measure which also includes the sequential preferences. The performance of the proposed approach is measured for different configurations using the MovieLens dataset and several evaluation metrics. The proposed approach also overcomes the limitations of the previous algorithm which restricts the prediction domain to the user’s browsing history only.

Suggested Citation

  • Anshul Gupta & Pravin Srinath, 2022. "A recommender system based on collaborative filtering, graph theory using HMM based similarity measures," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 533-545, March.
    • Handle: RePEc:spr:ijsaem:v:13:y:2022:i:1:d:10.1007_s13198-021-01537-6
    DOI: 10.1007/s13198-021-01537-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-021-01537-6
    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/s13198-021-01537-6?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. Chenbin Dou & Lan Zheng & Wenjuan Wang & Mohammad Shabaz & Dr. Dilbag Singh, 2021. "Evaluation of Urban Environmental and Economic Coordination Based on Discrete Mathematical Model," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-11, May.
    2. Chenbin Dou & Lan Zheng & Mohammad Shabaz, 2021. "Corrigendum to “Evaluation of Urban Environmental and Economic Coordination Based on Discrete Mathematical Model”," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-1, August.
    3. Manik Rakhra & Ramandeep Singh & Tarun Kumar Lohani & Mohammad Shabaz, 2021. "Metaheuristic and Machine Learning-Based Smart Engine for Renting and Sharing of Agriculture Equipment," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-13, February.
    4. Chirag Sharma & Amandeep Bagga & Bhupesh Kumar Singh & Mohammad Shabaz, 2021. "A Novel Optimized Graph-Based Transform Watermarking Technique to Address Security Issues in Real-Time Application," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-27, April.
    Full references (including those not matched with items on IDEAS)

    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. Subhash Tatale & V. Chandra Prakash, 2022. "Combinatorial test case generation from sequence diagram using optimization algorithms," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 642-657, March.
    2. Arber Hoti & Lulzim Krasniqi, 2022. "Impact of international financial reporting standards adoption on the perception of investors to invest in small-to-medium enterprise adopting transparency in disclosure policies," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 506-515, March.
    3. Qian Wang & Deepika Koundal, 2022. "Dynamics of food nutrient loss and prediction of nutrient loss under variable temperature conditions," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 225-235, March.
    4. Guoyong Wang & Lokanayaki Karnan & Faez M. Hassan, 2022. "Face feature point detection based on nonlinear high-dimensional space," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 312-321, March.
    5. Jianwei Chen & Longlong Bian & Ajit kumar & Rahul Neware, 2022. "A research based on application of dimension reduction technology in data visualization using machine learning," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 291-297, March.
    6. Wenzhong Xia & Rahul Neware & S. Deva Kumar & Dimitrios A. Karras & Ali Rizwan, 2022. "An optimization technique for intrusion detection of industrial control network vulnerabilities based on BP neural network," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 576-582, March.
    7. Max Cichocki & Christian Landschützer & Hannes Hick, 2022. "Development of a Sharing Concept for Industrial Compost Turners Using Model-Based Systems Engineering, under Consideration of Technical and Logistical Aspects," Sustainability, MDPI, vol. 14(17), pages 1-22, August.
    8. Fei Peng & Yanmei Wang & Haiyang Xuan & Tien V. T. Nguyen, 2022. "Efficient road traffic anti-collision warning system based on fuzzy nonlinear programming," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 456-461, March.
    9. Qiu Guo & Hechun Liu & Faez M. Hassan & Mohammed Wasim Bhatt & Ahmed Mateen Buttar, 2022. "Application of UAV tilt photogrammetry in 3D modeling of ancient buildings," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 424-436, March.
    10. Gurpreet Singh Panesar & Kuldeep Narayan Tripathi & Jyoti L. Bangare & Rahul Neware & Skanda Moda Gururajarao, 2022. "Handling research issues for big data extraction in the application of Internet of Vehicles (IoV)," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 751-756, March.
    11. Hassan A. A. Sayed & Qishuo Ding & Mahmoud A. Abdelhamid & Joseph O. Alele & Alfadhl Y. Alkhaled & Mohamed Refai, 2022. "Application of Machine Learning to Study the Agricultural Mechanization of Wheat Farms in Egypt," Agriculture, MDPI, vol. 13(1), pages 1-18, December.
    12. Qian Wang & Kandhasamy Sivakumar & Sugumar Mohanasundaram, 2022. "Impacts of extrusion processing on food nutritional components," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 364-374, March.

    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:ijsaem:v:13:y:2022:i:1:d:10.1007_s13198-021-01537-6. 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.