SpEnD portal: Linked data discovery using SPARQL endpoints

YUMUŞAK, Semih | ARAS, Rıza Emre | UYSAL, Elif | DOĞDU, Erdoğan | KODAZ, Halife | ÖZTOPRAK, Kasım

We present the project SpEnD, a complete SPARQL endpoint discovery and analysis portal. In a previous study, the SPARQL endpoint discovery and analysis steps of the SpEnD system were explained in detail. In the SpEnD portal, the SPARQL endpoints are extracted from the web by using web crawling techniques, monitored and analyzed by live querying the endpoints systematically. After many sustainability improvements in the SpEnD project, the SpEnD system is now online as a portal. SpEnD portal currently serves 1487 SPARQL endpoints, out of which 911 endpoints are uniquely found by SpEnD only when ...Daha fazlası

Konferans Bildirisi 2017 Institute of Electrical and Electronics Engineers Inc. 5 Görüntülenme

Erişime Açık

Comparison of machine learning algorithms on different datasets

UYSAL, Elif | ÖZTÜRK, Ali

Machine learning algorithms are methods used to classify data. Aim of this study is comparison of machine learning algorithms on different datasets. For this study, 9 different machine learning algorithms with 10 fold cross validation method in WEKA is classified on 3 different datasets. As a result of classification, machine learning algorithm which has high accuracy rate is different for 3 datasets. Multilayer Perceptron algorithm for Car Evaluation dataset, Random Forest algorithm for Image Segmentation dataset and Simple Logistic algorithm for User Knowledge Modeling dataset were obtained. ...Daha fazlası

Konferans Bildirisi 2018 Institute of Electrical and Electronics Engineers Inc. 6 Görüntülenme

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SpEnD portal: Linked data discovery using SPARQL endpoints

YUMUŞAK, Semih | ARAS, Rıza Emre | UYSAL, Elif | DOĞDU, Erdoğan | KODAZ, Halife | ÖZTOPRAK, Kasım

Comparison of machine learning algorithms on different datasets

UYSAL, Elif | ÖZTÜRK, Ali