Browsing by Author "Metin S.K."

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Citation - WoS: 8
Citation - Scopus: 24
An Android based home automation system
(IEEE Computer Society, 2013) Gurek A.; Gur C.; Gurakin C.; Akdeniz M.; Metin S.K.; Korkmaz I.
In recent years, the number of network enabled digital devices at homes has been increasing fast. With the rapid expansion of the Internet, the owners have been requesting remote control and monitoring of these in-home appliances. This leads to networking these appliances to form a kind of home automation system. In this paper, an Android based home automation system that allows multiple users to control the appliances by an Android application or through a web site is presented. The system has three hardware components: a local device to transfer signals to home appliances, a web server to store customer records and support services to the other components, and a mobile smart device running Android application. Distributed cloud platforms and services of Google are used to support messaging between the components. The prototype implementation of the proposed system is evaluated based on the criteria considered after the requirement analysis for an adequate home automation system. © 2013 IEEE.
Citation - Scopus: 1
Combining Machine Translation and Text Similarity Metrics To Identify Paraphrases in Turkish
(Institute of Electrical and Electronics Engineers Inc., 2018) Soleymanzadeh K.; Karaoğlan B.; Metin S.K.; Kişla T.
Paraphrase identification (PI) is to recognize whether given two sentences are restatements of each other or not. In our study we propose an approach that exploits machine translation and text similarity metrics as features for PI. Machine learning algorithms like Support Vector Machine (SVM) with three different kernels, C4.5 Decision tree and Multinomial Naïve Bayes (NB) are trained with these features. We evaluated our system on Parder, Turkish paraphrase corpus. The experimental results show that the proposed approach offers state-of-the-art results. © 2018 IEEE.
Contribution of Syntactic and Semantic Attributes in Paraphrase Identification
(Institute of Electrical and Electronics Engineers Inc., 2018) Karaoglan B.; Kisla T.; Metin S.K.
Automatic paraphrase identification is a natural language understanding problem where a decision is to be made whether the given sentence pairs bare similar meanings to a certain extent. Syntactic and semantic features are used to classify the sentences as paraphrase or non-paraphrase. Word overlapping, word ordering are some of the syntactic features widely used in the literature, where, similarity of words in meaning and named entity (NE) overlap are among the semantic features. Turkish, unfortunately doesn't have a useful tool like WordNet to draw the semantic relations between words as it is done for English. Here we exploit tense and polarity differences as semantic features and assess the improvement on the classification brought by these semantic features. We performed the experiments with several different combinations of features on the Turkish paraphrase corpus that is built by the researchers and report the results. © 2018 IEEE.
Text Similarity Analysis Using Ir Lists
(2013) Metin S.K.; Karaoglan B.; Kisla T.
Natural language processing can be seen as a signal processing problem when the characters, syllabi, words, punctuations in a text are considered as signals. In this article, we present a novel approach that detects text similarity in Turkish, based on the similarities of the lists of retrieved documents when the texts are given as queries to web search engines. The similarities between the URLs contained in the items of the returned lists are measured using statistical methods like euclidean, city-block, chebychev, cosine, correlation, spearman and hamming distances. For experimenting, a corpus of 150 news is developed by gathering news in 50 different topics from 3 Turkish newspapers published during a certain time slot. News on the same topic published in different newspapers are considered as similar texts. Statistical methods are applied on the formed newsXterms matrix; and for each news similar news are ranked from the most similar to least similar. If at least one of the top two is the same with the ones marked manully as similar, it is counted as success. Experimental results show that cosines and correlation distances give the best performance with 84% precision. © 2013 IEEE.