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Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Performance Comparison of Collaborative-Filtering Approach with Implicit and Explicit Data
Digital Object Identifier (DOI) : 10.14569/IJACSA.2019.0101016
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 10, 2019.
Abstract: Challenge in developing a collaborative filtering (CF)-based recommendation system is the problem of cold-starting of items that causes the data to sparse and reduces the accuracy of the recommendations. Therefore, to produce high accuracy a match is needed between the types of data and the approach used. Two approaches in CF include user-based and item-based CFs, both of which can process two types of data; implicit and explicit data. This work aims to find a combination of approaches and data types that produce high accuracy. Cosine-similarity is used to measure the similarity between users and also between items. Mean Absolute Error is also measured to discover the accuracy of a recommendation. Testing of three groups of data based on sparseness results in the best accuracy in an explicit data-based approach that has the smallest MAE value. The result is that the average MAE value for user based (implicit data) is 0.1032, user based (explicit data) is 0.2320, item based (implicit data) is 0.3495, and item based (explicit data) is 0.0926. The best accuracy is in the item-based (explicit-data) approach which is the smallest average MAE value.
Keywords: Recommender system; collaborative-filtering; user-based; item-based; implicit-data; explicit-data
Fitri Marisa, Sharifah Sakinah Syed Ahmad, Zeratul Izzah Mohd Yusoh, Tubagus Mohammad Akhriza, Wiwin Purnomowati and Rakesh Kumar Pandey, “Performance Comparison of Collaborative-Filtering Approach with Implicit and Explicit Data” International Journal of Advanced Computer Science and Applications(IJACSA), 10(10), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0101016
@article{Marisa2019,
title = {Performance Comparison of Collaborative-Filtering Approach with Implicit and Explicit Data},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0101016},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0101016},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {10},
author = {Fitri Marisa and Sharifah Sakinah Syed Ahmad and Zeratul Izzah Mohd Yusoh and Tubagus Mohammad Akhriza and Wiwin Purnomowati and Rakesh Kumar Pandey}
}
