Browsing by Author "Kurt, Mehmet"

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ALGORITHMIC APPROACH TO BITONIC ALGEBRAS AND THEIR GRAPHS
(Bayram Sahin, 2024) Şule Ayar Özbal; Refet Polat; Saadet Eskiizmirliler; Mehmet Kurt; Kurt, Mehmet; Polat, Refet; Ozbal, Sule Ayar; Eskiizmirliler, Saadet
Under the aim of this paper we establish the terms of graphs related with bitonic-algebras which is a bitonic-graph where the vertices are the elements of bitonic algebra and where the edges are the companian of two vertices that is two elements from bitonic algebra. We designate the upper sets of elements in a bitonic algebra and studied properties of these sets. We state algorithms to check whether the given set is a bitonic algebra or a commutative bitonic algebra or not. Additionally we mention the codes of these algorithms. Moreover we associate the algorithms of graphs of a bitonic algebra and state properties of these graphs obtained. © 2024 Elsevier B.V. All rights reserved.
Citation - WoS: 3
Citation - Scopus: 3
Analyzing Learning Concepts in Intelligent Tutoring Systems
(ZARKA PRIVATE UNIV, 2016) Korhan Gunel; Refet Polat; Mehmet Kurt; Kurt, Mehmet; Polat, Refet; Gunel, Korhan
The information that is increasing and changing rapidly at the present day and the usage of computers in educational and instructional processes has become inevitable. With the rapid progress in technology research gives more importance to integrate intelligent issues with educational support systems such as distance learning and learning management systems. Such studies are considered as applications of the artificial intelligence on educational processes. Regarding this viewpoint some supervised learning models which is able to recognize the learning concepts from a given educational content presented to a tutoring system has been designed in this study. For this aim firstly three different corpora constructed from educational contents related to the subject titles such as calculus abstract algebra and computer science have been composed. For each candidate learning concepts the feature vectors have been generated using a relation factor in addition to tf-idf values. The relation factor is defined as the ratio of the total number of the most frequent substrings in the corpus that appear with a candidate concept in the same sentence within an educational content to most frequent substring in the corpus. The achievement of this system is measured according to the F-measure.
Citation - Scopus: 3
Dealing with learning concepts via support vector machines
(Springer Verlag service@springer.de, 2014) Korhan Günel; Rifat Aşliyan; Mehmet Kurt; Refet Polat; Turgut Ozis; Özis, Turgut; Kurt, Mehmet; Aşliyan, Rifat; Polat, Refet; Günel, Korhan
Extracting learning concepts is one of the major problems of artificial intelligence on education. Essentially the determination of learning concepts within an educational content has some differences as compared with keyword or technical term extraction process. However the problem can still taught as a classification problem notwithstanding. In this paper we examine how to handle the extraction of learning concepts using support vector machines as a supervised learning algorithm and we evaluate the performance of the proposed approach using f-measure. © Springer-Verlag Berlin Heidelberg 2014. © 2016 Elsevier B.V. All rights reserved.