WSEAS Transactions on Computer Research


Print ISSN: 1991-8755
E-ISSN: 2415-1521

Volume 5, 2017

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of WSEAS Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.


Artificial Teaching Assistant - Scarlet

AUTHORS: Ilhan Karić, Zanin Vejzović, Denis Mušić, Emina Junuz, Mirza Smajić

Download as PDF

ABSTRACT: Scarlet an Artificial Teaching Assistant is a personal digital assistant that has been developed with main aim to assist students in their learning process by ensuring fast and efficiently search of documents and learning materials. Scarlet is able to give an adequate response to a specific question based on knowledge gathered by an unique algorithm which enables her to recognize context during file and web page content search. After finding the most appropriate answer Scarlet seeks for student feedback in order to improve future search. The metric proposed is based on the power law which occurs in natural language, that is the Zipfian distribution[1]. It is designed to work for any spoken language although it might work on some better than other depending on the nature of the language, the structure, grammar and semantics. The method uses this metric to derive context from data and then queries the data source looking for the best match. The whole implementation is rounded off by a learning module which gives the system a learning curve based on users (students) scoring how relevant the output is among other parameters. All the main algorithms and newly proposed metrics like the “contextual similarity” are presented in the same paper.

KEYWORDS: Artificial intelligence, machine learning, pattern recognition, natural language processing

REFERENCES:

[1] Konrad Rieck, Pavel Laskov, “Linear-Time Computation of Similarity Measures for Sequential Data”, Journal of Machine Learning Research 9 (2008) 23-48 pp. 1

[2] S T. Piantadosi, “Zipf’s word frequency law in natural language: A critical review and future directions”, Psychonomic Bulletin & Review, vol. 21, 2014,pp.1112-1130 to perform linearithmic due to the nature of the function.

[3] Ljubomir Lazic, Nikos Mastorakis, 'Cost effective software test metrics', WSEAS Transactions on Computers, pp. 599-619, Vol.7, Issue 6, 2008

[4] Klimis Ntalianis, Nikos Mastorakis, 'Social Media Video Content Diversity Visualization', International Journal of Signal Processing, pp. 169- 176, Volume 1, 2016,

WSEAS Transactions on Computer Research, ISSN / E-ISSN: 1991-8755 / 2415-1521, Volume 5, 2017, Art. #17, pp. 137-146


Copyright © 2017 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0

Bulletin Board

Currently:

The editorial board is accepting papers.


WSEAS Main Site