학술논문

Comparison of two Algorithms for Routing Questions and Answers, Applied to Group of Students Software Engineering
Document Type
Conference
Source
2018 IEEE Latin American Conference on Computational Intelligence (LA-CCI) Computational Intelligence (LA-CCI), 2018 IEEE Latin American Conference on. :1-6 Nov, 2018
Subject
Computing and Processing
Engineering Profession
General Topics for Engineers
Robotics and Control Systems
Routing
Training
Biological neural networks
Neurons
Self-organizing feature maps
Clustering algorithms
Community question answering
routing questions
neural network
self organized maps
Language
Abstract
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.