Open Access   Article Go Back

Enhancing Prediction in Collaborative Filtering-Based Recommender Systems

M. Hatami1 , S. Pashazadeh2

Section:Research Paper, Product Type: Journal Paper
Volume-2 , Issue-1 , Page no. 48-51, Jan-2014

Online published on Feb 04, 2014

Copyright © M. Hatami, S. Pashazadeh . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

XML View
PDF Download

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: M. Hatami, S. Pashazadeh, “Enhancing Prediction in Collaborative Filtering-Based Recommender Systems,” International Journal of Computer Sciences and Engineering, Vol.2, Issue.1, pp.48-51, 2014.

MLA Style Citation: M. Hatami, S. Pashazadeh "Enhancing Prediction in Collaborative Filtering-Based Recommender Systems." International Journal of Computer Sciences and Engineering 2.1 (2014): 48-51.

APA Style Citation: M. Hatami, S. Pashazadeh, (2014). Enhancing Prediction in Collaborative Filtering-Based Recommender Systems. International Journal of Computer Sciences and Engineering, 2(1), 48-51.

BibTex Style Citation:
@article{Hatami_2014,
author = {M. Hatami, S. Pashazadeh},
title = {Enhancing Prediction in Collaborative Filtering-Based Recommender Systems},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {1 2014},
volume = {2},
Issue = {1},
month = {1},
year = {2014},
issn = {2347-2693},
pages = {48-51},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=39},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=39
TI - Enhancing Prediction in Collaborative Filtering-Based Recommender Systems
T2 - International Journal of Computer Sciences and Engineering
AU - M. Hatami, S. Pashazadeh
PY - 2014
DA - 2014/02/04
PB - IJCSE, Indore, INDIA
SP - 48-51
IS - 1
VL - 2
SN - 2347-2693
ER -

VIEWS PDF XML
4126 3827 downloads 3768 downloads
  
  
           

Abstract

Recommender systems (RS) are introduced to help users with finding the desired information. Collaborative filtering (CF) approach is one of the most widely used techniques in recommender systems. Prediction is the main part of all recommender systems. In this paper we propose an enhanced prediction formula which could be employed in all CF-based methods. We used Resnick prediction formula as a base because it�s the most well-known and employed formula in CF-based RS. In the formula we have used not only the average of active user�s ratings, but also the collective average of similar users� ratings and the average of all ratings given to the target item. The results are promising and satisfying. We compared the results of enhanced prediction formula to the unenhanced version to verify the effectiveness of our proposed method.

Key-Words / Index Term

Collaborative Filtering, Recommender Systems, Prediction Formula, Enhancement

References

[1] P. Resnick, H. R. Varian, �Recommender systems,� Commun. ACM 40 (3) (1997) 56-58.
[2] D. H. Park, H. K. Kim, I. Y. Choi, J. K. Kim, �A literature review and classification of recommender systems research,� Expert Systems with Applications 39 (11) (2012) 10059-10072.
[3] D. Goldberg, D. Nichols, B. M. Oki, D. Terry, �Using collaborative filtering to weave an information tapestry,� Commun. ACM 35 (12) (1992) 61-70.
[4] R. Burke, �Hybrid recommender systems: Survey and experiments,� User Modeling and User-Adapted Interaction 12 (4) (2002) 331-370.
[5] P. Resnick, N. Iacovou, M. Suchak, P. Bergstrom, J. Riedl, �GroupLens: an open architecture for collaborative filtering of netnews,� In proceedings of the 1994 ACM Conference on Computer supported cooperative work, Sharing Information and Creating Meaning, pages 175�186, 1994.
[6] O�Donovan, John, and Barry Smyth. �Trust in recommender systems.� In Proceedings of the 10th international conference on Intelligent user interfaces, pp. 167-174. ACM, 2005.
[7] J. Bobadilla, A. Hernando, F. Ortega, J. Bernal, �A framework for collaborative filtering recommender systems,� Expert Systems with Applications 38 (12) (2011) 14609-14623.
[8] J. Bobadilla, F. Ortega, A. Hernando, A. Gutirrez, �Recommender systems survey�, Knowledge-Based Systems 46 (0) (2013) 109-132.