TELKOMNIKA Telecommunication Computing Electronics and Control
Big data cloud-based recommendation system using NLP techniques with machine and deep learning

TELKOMNIKA Telecommunication Computing Electronics and Control
Big data cloud-based recommendation system using NLP techniques with machine and deep learning

Artificial intelligence
Big data
Keras
Natural language processing
Recommendation system

Recommendation systems (RS) are crucial for social networking sites.
Without it, finding precise products is harder. However, existing systems
lack adequate efficiency, especially with big data. This paper presents a
prototype cloud-based recommendation system for processing big data. The
proposed work is implemented by utilizing the matrix factorization method
with three approaches. In the first approach, singular value decomposition
(SVD) is used, which is an old and traditional recommendation technique.
The second recommendation approach is fine-tuned using the alternating
least squares (ALS) algorithm with Apache Spark. Finally, the deep neural
network (DNN) algorithm is utilized with TensorFlow. This study solves the
challenge of handling large-scale datasets in the collaborative filtering (CF)
technique after tuning the algorithms by adjusting the parameters in the
second approach, which uses machine learning, as well as in the third
approach, which uses deep learning. Furthermore, the results of these two
approaches outperformed conventional techniques and achieved an
acceptable computational time. The dataset size is about 1.5 GB and it is
collected from the Goodreads website API. Moreover, the Hadoop
distributed file system (HDFS) is used as cloud storage instead of the
computer’s local disk for handling larger dataset sizes in the future.

Hoger K. Omar, Mondher Frikha, Alaa Khalil Jumaa

http://telkomnika.uad.ac.id

May 01, 2023

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