A study on hybrid recommend system combined sentiment analysis with matrix factorization

Vuong Quoc Nguyen; Kiet Nhan Tran; Thin Si Nguyen

doi:10.46223/HCMCOUJS.tech.en.14.2.3270.2024

14(2)2024

A study on hybrid recommend system combined sentiment analysis with matrix factorization

Author - Affiliation:

Vuong Quoc Nguyen - Dong A University, Danang , Vietnam

Kiet Nhan Tran - The University of Danang, Danang , Vietnam

Thin Si Nguyen - The University of Danang, Danang , Vietnam

Corresponding author: Thin Si Nguyen - nsthin@vku.udn.vn

DOI:10.46223/HCMCOUJS.tech.en.14.2.3270.2024

Submitted: 01-03-2024
Accepted: 21-04-2024
Published: 04-09-2024

Abstract

Contemporary research endeavors have evinced a substantial interest in integrating heterogeneous data sources within unified recommendation system frameworks. Concomitantly, the conventional two-dimensional product-user rating matrix ubiquitous in matrix factorization problems is being augmented by incorporating ancillary dimensions such as sentiment, temporality, and spatial characteristics. Concurrently, the challenge of surmounting limitations in capturing Vietnamese sentiment characteristics for data enrichment has garnered scholarly attention. Stemming from these two salient issues, the authors propound a hybrid model that amalgamates the factor matrix principle from collaborative filtering methodologies with sentiment analysis for prognosticating user rating propensities. Through empirical evaluation on a corpus of mobile application reviews, the proposed model has demonstrated its suitability for research purposes and exhibited superior predictive accuracy compared to simpler paradigms.

Keywords

activation; activated carbon; adsorption; Fe liquid waste; rubber seed shell

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Cite this paper as:

Nguyen, V. Q., Tran, K. N., & Nguyen, T. S. (2024). A study on hybrid recommend system combined sentiment analysis with matrix factorization. Ho Chi Minh City Open University Journal of Science – Engineering and Technology, 14(2), 48-58. doi:10.46223/HCMCOUJS.tech.en.14.2.3270.2024

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DOI: https://doi.org/10.46223/HCMCOUJS.tech.en.14.2.3270.2024