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Research Article | Open Access |

Recommendation using Rule based Implicative Rating Measure

Author 1: Lan Phuong Phan Author 2: Hung Huu Huynh Author 3: Hiep Xuan Huynh
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 9, No. 4 · Published 2018

DOI: https://doi.org/10.14569/IJACSA.2018.090428

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Abstract

The paper presents a rule based implicative rating measure to calculate the ratings of users on items. The paper also presents a new model using the ruleset with the rule length of 2 and the proposed measure to suggest to users the list of items with the highest ratings. The new model is compared to the three existing models that use items (such as the popular items, the items with highest similarities, and the items with strong relationships) to make the suggestion. The experiments on the MSWeb dataset and the MovieLens dataset indicate that the proposed recommendation model has the higher performace (via the Precision - Recall and the ROC curves) than the compared models for most of the given.

Keywords

Model evaluation recommendation model rule based implicative rating measure ruleset

How to Cite this Article

Phan, L. P., Huynh, H. H., & Huynh, H. X. (2018). Recommendation using Rule based Implicative Rating Measure. International Journal of Advanced Computer Science and Applications, 9(4). https://doi.org/10.14569/IJACSA.2018.090428

Phan, Lan Phuong, et al.. "Recommendation using Rule based Implicative Rating Measure." International Journal of Advanced Computer Science and Applications, vol. 9, no. 4, 2018, https://doi.org/10.14569/IJACSA.2018.090428.

@article{Phan2018,
  title     = {Recommendation using Rule based Implicative Rating Measure},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {9},
  number    = {4},
  year      = {2018},
  publisher = {The Science and Information Organization},
  author    = {Lan Phuong Phan and Hung Huu Huynh and Hiep Xuan Huynh},
  doi       = {10.14569/IJACSA.2018.090428},
  url       = {https://doi.org/10.14569/IJACSA.2018.090428}
}

Open Access — licensed under a Creative Commons Attribution 4.0 International License. Unrestricted use, distribution, and reproduction in any medium, even commercially, as long as the original work is properly cited.

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