@article{ART003228325},
author={Soojung Lee},
title={Item-attribute-based Semantic Similarity for Data Sparsity in Collaborative Filtering},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2025},
volume={30},
number={7},
pages={171-179}
TY - JOUR
AU - Soojung Lee
TI - Item-attribute-based Semantic Similarity for Data Sparsity in Collaborative Filtering
JO - Journal of The Korea Society of Computer and Information
PY - 2025
VL - 30
IS - 7
PB - The Korean Society Of Computer And Information
SP - 171
EP - 179
SN - 1598-849X
AB - Neighbor-based collaborative filtering is a representative recommendation algorithm that predicts user preferences based on user or item similarity and it is known for its simplicity and interpretability.
However, this approach faces the data sparsity problem, in which the accuracy of similarity computation deteriorates when user rating data is insufficient. To address this limitation, this study proposes novel symmetric and asymmetric item-based similarity measures that rely solely on item attribute information.
The proposed measures do not require the number of co-rated items or the ratings distribution, but they compute semantic similarity based on common item attributes, which allows for robust performance even under sparse conditions. Experimental results using two public datasets demonstrate that the proposed method outperforms existing techniques in terms of average precision and coverage. The method is applicable even in systems with no explicit ratings provided, and if item attributes are static, similarity computation needs to be performed only once, offering strong system scalability advantages.
KW - Similarity Measure;Data Sparsity Problem;Item-based Collaborative Filtering;Recommender System
DO -
UR -
ER -
Soojung Lee. (2025). Item-attribute-based Semantic Similarity for Data Sparsity in Collaborative Filtering. Journal of The Korea Society of Computer and Information, 30(7), 171-179.
Soojung Lee. 2025, "Item-attribute-based Semantic Similarity for Data Sparsity in Collaborative Filtering", Journal of The Korea Society of Computer and Information, vol.30, no.7 pp.171-179.
Soojung Lee "Item-attribute-based Semantic Similarity for Data Sparsity in Collaborative Filtering" Journal of The Korea Society of Computer and Information 30.7 pp.171-179 (2025) : 171.
Soojung Lee. Item-attribute-based Semantic Similarity for Data Sparsity in Collaborative Filtering. 2025; 30(7), 171-179.
Soojung Lee. "Item-attribute-based Semantic Similarity for Data Sparsity in Collaborative Filtering" Journal of The Korea Society of Computer and Information 30, no.7 (2025) : 171-179.
Soojung Lee. Item-attribute-based Semantic Similarity for Data Sparsity in Collaborative Filtering. Journal of The Korea Society of Computer and Information, 30(7), 171-179.
Soojung Lee. Item-attribute-based Semantic Similarity for Data Sparsity in Collaborative Filtering. Journal of The Korea Society of Computer and Information. 2025; 30(7) 171-179.
Soojung Lee. Item-attribute-based Semantic Similarity for Data Sparsity in Collaborative Filtering. 2025; 30(7), 171-179.
Soojung Lee. "Item-attribute-based Semantic Similarity for Data Sparsity in Collaborative Filtering" Journal of The Korea Society of Computer and Information 30, no.7 (2025) : 171-179.
