Comparison of two Algorithms for Routing Questions and Answers, Applied to Group of Students Software Engineering

Carlos E. Serquen-Llallire; Hugo D. Calderon-Vilca; Flor C. Cardenas-Marino

doi:10.1109/LA-CCI.2018.8625262

Comparison of two Algorithms for Routing Questions and Answers, Applied to Group of Students Software Engineering

Carlos E. Serquen-Llallire, Hugo D. Calderon-Vilca, Flor C. Cardenas-Marino

Research output: Contribution to conference › Paper

6 Scopus citations

Abstract

© 2018 IEEE. Community Question Answering (CQA) have become a popular web services where users respond and can ask questions. In this search we present the comparison of two algorithms to verify which of the two is better suited to the problem of routing questions. We began by taking the characteristics of the questions, then presented the Perceptron Back propagation learning and the Self Organizing Map (SOM) network to calculate the set of people most apt to answer the question, the adaptation of both algorithms was compared, concluding that the SOM network adapts better, being 14.81% more accurate than Perceptron in this type of problems.

Original language	American English
DOIs	https://doi.org/10.1109/LA-CCI.2018.8625262
State	Published - 23 Jan 2019
Event	2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018 - Duration: 23 Jan 2019 → …

Conference

Conference	2018 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2018
Period	23/01/19 → …

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10.1109/LA-CCI.2018.8625262

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N2 - © 2018 IEEE. Community Question Answering (CQA) have become a popular web services where users respond and can ask questions. In this search we present the comparison of two algorithms to verify which of the two is better suited to the problem of routing questions. We began by taking the characteristics of the questions, then presented the Perceptron Back propagation learning and the Self Organizing Map (SOM) network to calculate the set of people most apt to answer the question, the adaptation of both algorithms was compared, concluding that the SOM network adapts better, being 14.81% more accurate than Perceptron in this type of problems.

AB - © 2018 IEEE. Community Question Answering (CQA) have become a popular web services where users respond and can ask questions. In this search we present the comparison of two algorithms to verify which of the two is better suited to the problem of routing questions. We began by taking the characteristics of the questions, then presented the Perceptron Back propagation learning and the Self Organizing Map (SOM) network to calculate the set of people most apt to answer the question, the adaptation of both algorithms was compared, concluding that the SOM network adapts better, being 14.81% more accurate than Perceptron in this type of problems.

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Comparison of two Algorithms for Routing Questions and Answers, Applied to Group of Students Software Engineering

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