Semi-automated intelligent systems

Srihari Akash Chinam; N. V. Subba Reddy; K. V. Prema

doi:10.1109/ICACCI.2017.8125825

Semi-automated intelligent systems

Srihari Akash Chinam, N. V. Subba Reddy, K. V. Prema

Department of Computer Science and Engineering, Manipal Institute of Technology, Manipal

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

Abstract

An intelligent system uses machine learning algorithms to provide outputs to every input provided. The introduction of emotions in intelligent systems is required to create systems that are more similar to human beings and thus more reliable. In this paper, the idea of introducing the emotion 'uncertainty' in Intelligent Systems is proposed. A Semi-Automated Intelligent System is introduced in this paper, which combines a Naïve Bayesian Classifier, a Random Forest Classifier and a Multi Layer Perceptron using a Multi Model Strategy to introduce uncertainty. When used individually the classifiers had errors in the range of 6-7% but when combined as the Semi-Automated Intelligent System, the false predictions were kept under 0.2%. The paper also discusses several preprocessing techniques that were applied on the text documents to ensure effective analysis of data.

Original language	English
Title of host publication	2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	110-115
Number of pages	6
Volume	2017-January
ISBN (Electronic)	9781509063673
DOIs	https://doi.org/10.1109/ICACCI.2017.8125825
Publication status	Published - 30-11-2017
Event	2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017 - Manipal, Mangalore, India Duration: 13-09-2017 → 16-09-2017

Conference

Conference	2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017
Country/Territory	India
City	Manipal, Mangalore
Period	13-09-17 → 16-09-17

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Computer Science Applications
Information Systems

Access to Document

10.1109/ICACCI.2017.8125825

Cite this

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title = "Semi-automated intelligent systems",

abstract = "An intelligent system uses machine learning algorithms to provide outputs to every input provided. The introduction of emotions in intelligent systems is required to create systems that are more similar to human beings and thus more reliable. In this paper, the idea of introducing the emotion 'uncertainty' in Intelligent Systems is proposed. A Semi-Automated Intelligent System is introduced in this paper, which combines a Na{\"i}ve Bayesian Classifier, a Random Forest Classifier and a Multi Layer Perceptron using a Multi Model Strategy to introduce uncertainty. When used individually the classifiers had errors in the range of 6-7% but when combined as the Semi-Automated Intelligent System, the false predictions were kept under 0.2%. The paper also discusses several preprocessing techniques that were applied on the text documents to ensure effective analysis of data.",

author = "Chinam, {Srihari Akash} and {Subba Reddy}, {N. V.} and Prema, {K. V.}",

year = "2017",

month = nov,

day = "30",

doi = "10.1109/ICACCI.2017.8125825",

language = "English",

volume = "2017-January",

pages = "110--115",

booktitle = "2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017 ; Conference date: 13-09-2017 Through 16-09-2017",

}

Chinam, SA, Subba Reddy, NV & Prema, KV 2017, Semi-automated intelligent systems. in 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017. vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 110-115, 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017, Manipal, Mangalore, India, 13-09-17. https://doi.org/10.1109/ICACCI.2017.8125825

Semi-automated intelligent systems. / Chinam, Srihari Akash; Subba Reddy, N. V.; Prema, K. V.
2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017. Vol. 2017-January Institute of Electrical and Electronics Engineers Inc., 2017. p. 110-115.

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

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T1 - Semi-automated intelligent systems

AU - Chinam, Srihari Akash

AU - Subba Reddy, N. V.

AU - Prema, K. V.

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N2 - An intelligent system uses machine learning algorithms to provide outputs to every input provided. The introduction of emotions in intelligent systems is required to create systems that are more similar to human beings and thus more reliable. In this paper, the idea of introducing the emotion 'uncertainty' in Intelligent Systems is proposed. A Semi-Automated Intelligent System is introduced in this paper, which combines a Naïve Bayesian Classifier, a Random Forest Classifier and a Multi Layer Perceptron using a Multi Model Strategy to introduce uncertainty. When used individually the classifiers had errors in the range of 6-7% but when combined as the Semi-Automated Intelligent System, the false predictions were kept under 0.2%. The paper also discusses several preprocessing techniques that were applied on the text documents to ensure effective analysis of data.

AB - An intelligent system uses machine learning algorithms to provide outputs to every input provided. The introduction of emotions in intelligent systems is required to create systems that are more similar to human beings and thus more reliable. In this paper, the idea of introducing the emotion 'uncertainty' in Intelligent Systems is proposed. A Semi-Automated Intelligent System is introduced in this paper, which combines a Naïve Bayesian Classifier, a Random Forest Classifier and a Multi Layer Perceptron using a Multi Model Strategy to introduce uncertainty. When used individually the classifiers had errors in the range of 6-7% but when combined as the Semi-Automated Intelligent System, the false predictions were kept under 0.2%. The paper also discusses several preprocessing techniques that were applied on the text documents to ensure effective analysis of data.

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BT - 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017

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ER -

Semi-automated intelligent systems

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All Science Journal Classification (ASJC) codes

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