Latent Semantic Index: A Microservices Architecture

Julio Proaño; Andres Reinoso; Jonnathan Juma

doi:10.1007/978-3-030-46785-2_12

Latent Semantic Index: A Microservices Architecture

Julio Proaño, Andres Reinoso, Jonnathan Juma

Spatial Data Infrastructure Research Group Artificial Intelligence Geoportals and Applied Computing (IDE IA GEO CA)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

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.

Original language	English
Title of host publication	Smart Technologies, Systems and Applications - 1st International Conference, SmartTech-IC 2019, Proceedings
Editors	Fabián R. Narváez, Diego F. Vallejo, Paulina A. Morillo, Julio R. Proaño
Publisher	Springer
Pages	142-153
Number of pages	12
ISBN (Print)	9783030467845
DOIs	https://doi.org/10.1007/978-3-030-46785-2_12
State	Published - 1 Jan 2020
Event	1st International Conference on Smart Technologies, Systems and Applications, SmartTech-IC 2019 - Quito, Ecuador Duration: 2 Dec 2019 → 4 Dec 2019

Publication series

Name	Communications in Computer and Information Science
Volume	1154 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	1st International Conference on Smart Technologies, Systems and Applications, SmartTech-IC 2019
Country/Territory	Ecuador
City	Quito
Period	2/12/19 → 4/12/19

Bibliographical note

Publisher Copyright:
© Springer Nature Switzerland AG 2020.

Keywords

Distributed computing
Latent Semantic Index
Micro services

Access to Document

10.1007/978-3-030-46785-2_12

Cite this

Proaño, J., Reinoso, A., & Juma, J. (2020). Latent Semantic Index: A Microservices Architecture. In F. R. Narváez, D. F. Vallejo, P. A. Morillo, & J. R. Proaño (Eds.), Smart Technologies, Systems and Applications - 1st International Conference, SmartTech-IC 2019, Proceedings (pp. 142-153). (Communications in Computer and Information Science; Vol. 1154 CCIS). Springer. https://doi.org/10.1007/978-3-030-46785-2_12

Proaño, Julio ; Reinoso, Andres ; Juma, Jonnathan. / Latent Semantic Index : A Microservices Architecture. Smart Technologies, Systems and Applications - 1st International Conference, SmartTech-IC 2019, Proceedings. editor / Fabián R. Narváez ; Diego F. Vallejo ; Paulina A. Morillo ; Julio R. Proaño. Springer, 2020. pp. 142-153 (Communications in Computer and Information Science).

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keywords = "Distributed computing, Latent Semantic Index, Micro services",

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Proaño, J, Reinoso, A & Juma, J 2020, Latent Semantic Index: A Microservices Architecture. in FR Narváez, DF Vallejo, PA Morillo & JR Proaño (eds), Smart Technologies, Systems and Applications - 1st International Conference, SmartTech-IC 2019, Proceedings. Communications in Computer and Information Science, vol. 1154 CCIS, Springer, pp. 142-153, 1st International Conference on Smart Technologies, Systems and Applications, SmartTech-IC 2019, Quito, Ecuador, 2/12/19. https://doi.org/10.1007/978-3-030-46785-2_12

Latent Semantic Index: A Microservices Architecture. / Proaño, Julio; Reinoso, Andres; Juma, Jonnathan.
Smart Technologies, Systems and Applications - 1st International Conference, SmartTech-IC 2019, Proceedings. ed. / Fabián R. Narváez; Diego F. Vallejo; Paulina A. Morillo; Julio R. Proaño. Springer, 2020. p. 142-153 (Communications in Computer and Information Science; Vol. 1154 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T2 - 1st International Conference on Smart Technologies, Systems and Applications, SmartTech-IC 2019

AU - Proaño, Julio

AU - Reinoso, Andres

AU - Juma, Jonnathan

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2020.

PY - 2020/1/1

Y1 - 2020/1/1

N2 - 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.

AB - 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.

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BT - Smart Technologies, Systems and Applications - 1st International Conference, SmartTech-IC 2019, Proceedings

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A2 - Morillo, Paulina A.

A2 - Proaño, Julio R.

PB - Springer

Y2 - 2 December 2019 through 4 December 2019

ER -

Latent Semantic Index: A Microservices Architecture

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Keywords

Access to Document

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