2016 2nd International Conference on Science and Technology-Computer (ICST) 2016
DOI: 10.1109/icstc.2016.7877370
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Implementation of multi-criteria collaborative filtering on cluster using Apache Spark

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Cited by 10 publications
(3 citation statements)
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“…Sistem yang tidak terskalakan (unscalable) memengaruhi kualitas layanan dan biaya pemeliharaan (Wijayanto, 2016). Sistem perlu diuji dengan baik untuk mengatasi penambahan beban agar tidak mengganggu kinerja bisnis.…”
Section: Pendahuluanunclassified
“…Sistem yang tidak terskalakan (unscalable) memengaruhi kualitas layanan dan biaya pemeliharaan (Wijayanto, 2016). Sistem perlu diuji dengan baik untuk mengatasi penambahan beban agar tidak mengganggu kinerja bisnis.…”
Section: Pendahuluanunclassified
“…Panigrahi et al used Alternating Least Square (ALS) on Spark and -means to avoid the data sparsity and scalability of collaborative filtering algorithms [43]. Wijayanto and Winarko implemented multicriteria collaborative filtering using Spark framework [44]. The experiments' results showed that efficiency of algorithms improved with the number of nodes in Spark clusters.…”
Section: Big Data Analytics For Recommendationmentioning
confidence: 99%
“…Experiments show that the accuracy of the recommended results has improved compared with the original algorithm. In [7], the multi-standard collaborative filtering algorithm extended horizontally and ran by adding the computing nodes. The experimental results show that the algorithm has not been improved obviously with the increase of nodes.…”
Section: Introductionmentioning
confidence: 99%