Latent Semantic Index: A Microservices Architecture

Julio Proaño, Andres Reinoso, Jonnathan Juma

Producción científica: Capítulo del libro/informe/acta de congresoContribución de conferenciarevisión exhaustiva


Nowadays, searching for a topic on the Internet can be a frustrating experience because of all the excessive information. Thus, a strategy for automatically classifying the results can improve user experience and work efficiency. Latent Semantic Indexing (LSI) algorithm is used to classify documents by meaning due to its effectiveness. However, there is a problem with the implementation of this algorithm. LSI is computationally intensive because the cost is directly related to the number of documents. In particular, the Singular Value Decomposition (SVD) that is mainly used in LSI is unscalable in terms of both memory and computation time. One possible solution is to use more powerful computational resources, such as multiple computing nodes. In this paper, a novel distributed architecture for the LSI algorithm is proposed. It is based on the use of microservices in a Google Cloud environment. We evaluated the performances of the proposed Cloud-based LSI, and comparison is made with standalone LSI. The results show the benefits of using distributed systems based on runtime, concurrency, and processing.

Idioma originalInglés
Título de la publicación alojadaSmart Technologies, Systems and Applications - 1st International Conference, SmartTech-IC 2019, Proceedings
EditoresFabián R. Narváez, Diego F. Vallejo, Paulina A. Morillo, Julio R. Proaño
Número de páginas12
ISBN (versión impresa)9783030467845
EstadoPublicada - 1 ene. 2020
Evento1st International Conference on Smart Technologies, Systems and Applications, SmartTech-IC 2019 - Quito, Ecuador
Duración: 2 dic. 20194 dic. 2019

Serie de la publicación

NombreCommunications in Computer and Information Science
Volumen1154 CCIS
ISSN (versión impresa)1865-0929
ISSN (versión digital)1865-0937


Conferencia1st International Conference on Smart Technologies, Systems and Applications, SmartTech-IC 2019

Nota bibliográfica

Publisher Copyright:
© Springer Nature Switzerland AG 2020.

Copyright 2020 Elsevier B.V., All rights reserved.


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