A multi-criteria recommendation system using dimensionality reduction and Neuro-Fuzzy techniques
| LEADER | caa a22 4500 | ||
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| 001 | 60547091X | ||
| 003 | CHVBK | ||
| 005 | 20210128100330.0 | ||
| 007 | cr unu---uuuuu | ||
| 008 | 210128e20151101xx s 000 0 eng | ||
| 024 | 7 | 0 | |a 10.1007/s00500-014-1475-6 |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s00500-014-1475-6 | ||
| 245 | 0 | 2 | |a A multi-criteria recommendation system using dimensionality reduction and Neuro-Fuzzy techniques |h [Elektronische Daten] |c [Mehrbakhsh Nilashi, Othman Ibrahim, Norafida Ithnin, Rozana Zakaria] |
| 520 | 3 | |a Multi-criteria collaborative filtering (MC-CF) presents a possibility to provide accurate recommendations by considering the user preferences in multiple aspects of items. However, scalability and sparsity are two main problems in MC-CF which this paper attempts to solve them using dimensionality reduction and Neuro-Fuzzy techniques. Considering the user behavior about items' features which is frequently vague, imprecise and subjective, we solve the sparsity problem using Neuro-Fuzzy technique. For the scalability problem, higher order singular value decomposition along with supervised learning (classification) methods is used. Thus, the objective of this paper is to propose a new recommendation model to improve the recommendation quality and predictive accuracy of MC-CF and solve the scalability and alleviate the sparsity problems in the MC-CF. The experimental results of applying these approaches on Yahoo!Movies and TripAdvisor datasets with several comparisons are presented to show the enhancement of MC-CF recommendation quality and predictive accuracy. The experimental results demonstrate that SVM dominates the K-NN and FBNN in improving the MC-CF predictive accuracy evaluated by most broadly popular measurement metrics, F1 and mean absolute error. In addition, the experimental results also demonstrate that the combination of Neuro-Fuzzy and dimensionality reduction techniques remarkably improves the recommendation quality and predictive accuracy of MC-CF in relation to the previous recommendation techniques based on multi-criteria ratings. | |
| 540 | |a Springer-Verlag Berlin Heidelberg, 2014 | ||
| 690 | 7 | |a Adaptive Neuro-Fuzzy inference systems |2 nationallicence | |
| 690 | 7 | |a Higher order singular value decomposition |2 nationallicence | |
| 690 | 7 | |a Multi-criteria collaborative filtering |2 nationallicence | |
| 690 | 7 | |a Predictive accuracy |2 nationallicence | |
| 690 | 7 | |a Classification |2 nationallicence | |
| 700 | 1 | |a Nilashi |D Mehrbakhsh |u Faculty of Computing, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia |4 aut | |
| 700 | 1 | |a Ibrahim |D Othman |u Faculty of Computing, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia |4 aut | |
| 700 | 1 | |a Ithnin |D Norafida |u Faculty of Computing, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia |4 aut | |
| 700 | 1 | |a Zakaria |D Rozana |u Construction Research Alliance, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia |4 aut | |
| 773 | 0 | |t Soft Computing |d Springer Berlin Heidelberg |g 19/11(2015-11-01), 3173-3207 |x 1432-7643 |q 19:11<3173 |1 2015 |2 19 |o 500 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s00500-014-1475-6 |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s00500-014-1475-6 |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Nilashi |D Mehrbakhsh |u Faculty of Computing, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Ibrahim |D Othman |u Faculty of Computing, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Ithnin |D Norafida |u Faculty of Computing, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Zakaria |D Rozana |u Construction Research Alliance, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Soft Computing |d Springer Berlin Heidelberg |g 19/11(2015-11-01), 3173-3207 |x 1432-7643 |q 19:11<3173 |1 2015 |2 19 |o 500 | ||