1. //
  2. Start
  3. //
  4. Publications
  5. Artificial Intelligence Algorithms for C...
  6. Output formats
  7. //

Artificial Intelligence Algorithms for Collaborative Book Recommender Systems

Research output: Journal contributions › Journal articles › Research › peer-review

Standard

Artificial Intelligence Algorithms for Collaborative Book Recommender Systems. / Tegetmeier, Clemens; Johannssen, Arne; Chukhrova, Nataliya.
In: Annals of Data Science, Vol. 11, No. 5, 10.2024, p. 1705-1739.

Research output: Journal contributions › Journal articles › Research › peer-review

Harvard

Tegetmeier, C, Johannssen, A & Chukhrova, N 2024, 'Artificial Intelligence Algorithms for Collaborative Book Recommender Systems', Annals of Data Science, vol. 11, no. 5, pp. 1705-1739. https://doi.org/10.1007/s40745-023-00474-4

APA

Tegetmeier, C., Johannssen, A., & Chukhrova, N. (2024). Artificial Intelligence Algorithms for Collaborative Book Recommender Systems. Annals of Data Science, 11(5), 1705-1739. https://doi.org/10.1007/s40745-023-00474-4

Vancouver

Tegetmeier C, Johannssen A, Chukhrova N. Artificial Intelligence Algorithms for Collaborative Book Recommender Systems. Annals of Data Science. 2024 Oct;11(5):1705-1739. doi: 10.1007/s40745-023-00474-4

Bibtex

@article{bf8002f62fe74f88a5b962f083f87b07,
title = "Artificial Intelligence Algorithms for Collaborative Book Recommender Systems",
abstract = "Book recommender systems provide personalized recommendations of books to users based on their previous searches or purchases. As online trading of books has become increasingly important in recent years, artificial intelligence (AI) algorithms are needed to recommend suitable books to users and encourage them to make purchasing decisions in the short and the long run. In this paper, we consider AI algorithms for so called collaborative book recommender systems, especially the matrix factorization algorithm using the stochastic gradient descent method and the book-based k-nearest-neighbor algorithm. We perform a comprehensive case study based on the Book-Crossing benchmark data set, and implement various variants of both AI algorithms to predict unknown book ratings and to recommend books to individual users based on the highest predicted ratings. This study aims to evaluate the quality of the implemented methods in recommending books by using selected evaluation metrics for AI algorithms.",
keywords = "Artificial intelligence, Book recommender systems, knn algorithm, Machine learning, Matrix factorization algorithm, Stochastic gradient descent method, Management studies",
author = "Clemens Tegetmeier and Arne Johannssen and Nataliya Chukhrova",
note = "Publisher Copyright: {\textcopyright} The Author(s) 2023.",
year = "2024",
month = oct,
doi = "10.1007/s40745-023-00474-4",
language = "English",
volume = "11",
pages = "1705--1739",
journal = "Annals of Data Science",
issn = "2198-5804",
publisher = "Springer Science and Business Media Deutschland",
number = "5",

}

RIS

TY - JOUR

T1 - Artificial Intelligence Algorithms for Collaborative Book Recommender Systems

AU - Tegetmeier, Clemens

AU - Johannssen, Arne

AU - Chukhrova, Nataliya

N1 - Publisher Copyright: © The Author(s) 2023.

PY - 2024/10

Y1 - 2024/10

N2 - Book recommender systems provide personalized recommendations of books to users based on their previous searches or purchases. As online trading of books has become increasingly important in recent years, artificial intelligence (AI) algorithms are needed to recommend suitable books to users and encourage them to make purchasing decisions in the short and the long run. In this paper, we consider AI algorithms for so called collaborative book recommender systems, especially the matrix factorization algorithm using the stochastic gradient descent method and the book-based k-nearest-neighbor algorithm. We perform a comprehensive case study based on the Book-Crossing benchmark data set, and implement various variants of both AI algorithms to predict unknown book ratings and to recommend books to individual users based on the highest predicted ratings. This study aims to evaluate the quality of the implemented methods in recommending books by using selected evaluation metrics for AI algorithms.

AB - Book recommender systems provide personalized recommendations of books to users based on their previous searches or purchases. As online trading of books has become increasingly important in recent years, artificial intelligence (AI) algorithms are needed to recommend suitable books to users and encourage them to make purchasing decisions in the short and the long run. In this paper, we consider AI algorithms for so called collaborative book recommender systems, especially the matrix factorization algorithm using the stochastic gradient descent method and the book-based k-nearest-neighbor algorithm. We perform a comprehensive case study based on the Book-Crossing benchmark data set, and implement various variants of both AI algorithms to predict unknown book ratings and to recommend books to individual users based on the highest predicted ratings. This study aims to evaluate the quality of the implemented methods in recommending books by using selected evaluation metrics for AI algorithms.

KW - Artificial intelligence

KW - Book recommender systems

KW - knn algorithm

KW - Machine learning

KW - Matrix factorization algorithm

KW - Stochastic gradient descent method

KW - Management studies

UR - http://www.scopus.com/inward/record.url?scp=85161371455&partnerID=8YFLogxK

U2 - 10.1007/s40745-023-00474-4

DO - 10.1007/s40745-023-00474-4

M3 - Journal articles

AN - SCOPUS:85161371455

VL - 11

SP - 1705

EP - 1739

JO - Annals of Data Science

JF - Annals of Data Science

SN - 2198-5804

IS - 5

ER -

DOI

Recently viewed

Researchers

  1. Benjamin Schulz

Activities

  1. Three steps forward, two steps backward: How distributed field governance causes incremental practice change in the case of integrated health care in Germany
  2. 11th Conference on Intelligent Computation in Manufacturing Engineering - CIRP ICME 2017
  3. Walter de Gruyter (Verlag)
  4. 6th IFAC Workshop on Periodic Control Systems (PSYCO)
  5. Co-creation in Open Strategy and Entrepreneurship
  6. The use of digital communication media in cross-border knowledge transfer processes: A competitive advantage for multinational companies?
  7. Journal of Applied Linguistics and Professional Practice (Zeitschrift)
  8. Going Green - A Hands-On Look at the Project
  9. “Holidaily”: Development Of A Smartphone Application For Better Recovery From Stressful Work Before, During And After A Vacation
  10. Applied Linguistics (Fachzeitschrift)
  11. The city as anthropo-scene? Art and urban spaces of possibility in the Anthropocene
  12. Participatory research from the ‘Sentipensar’ concept: towards the plurality of knowledge
  13. A screening biodegradation Water Sediment Test
  14. Towards a European Program on Entrepreneurship, Humanities and Social Sciences
  15. Public Lecture Series "Global Politics" 2014
  16. Detecting Schooling Markets in the Federal State of Hamburg
  17. IEEE Global Engineering Education Conference - EDUCON 2014
  18. Swets & Zeitglinger (Verlag)
  19. Was ist nachhaltige Entwicklung?
  20. J. Pedro Lorente
  21. Sensors (Fachzeitschrift)
  22. Perspectives on digital teaching and learning and AI in education II
  23. Annual Conference of the Forum for Acces and Continuiting Education - FACE conference 2012
  24. Fakultät Management und Technologie (Organisation)

Publications

  1. Mapping Amazon's logistical footprint on the Ruhr
  2. Organizing for innovation through accelerators: An introduction
  3. Trans pixelate substitution scheme for denoising computed tomography images towards high diagnosis accuracy
  4. Modeling of microstructural pattern formation in crystal plasticity
  5. The Influence of Adjustment Costs on Labour Adjustment: An Analysis Using Panel Data for Manufacturing Establishments in Lower Saxony
  6. Calibrated Passive Sampling - Multi-plot Field Measurements of NH3 Emissions with a Combination of Dynamic Tube Method and Passive Samplers
  7. Anticipated imitation of multiple agents
  8. Motion-decoupled internal force control in grasping with visco-elastic contacts
  9. Differential mortality rates in major and subthreshold depression
  10. Against and with the silence: Language, relations, and methods in qualitative research on pregnancy loss and perinatal bereavement
  11. In search of maturity models in agritechs
  12. INFLEXIBLE COMMODITY PRICES AS A RESULT OF PROFIT MAXIMIZATION - REPLY TO A COMMENT BY MAUSSNER,A.
  13. Legacy effects of land-use modulate tree growth responses to climate extremes
  14. “Self-centered, self-promoting, and self-legitimizing”
  15. Inter- und Transdisziplinarität
  16. Physiological evidence of interpersonal dynamics in a cooperative production task
  17. Walking Backward
  18. Ein Code, eine Kunst ?
  19. Understanding the bright side and the dark side of telework