Guven Fidan

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In this paper, we propose a novel framework called Smart-Miner for web usage mining problem which uses link information for producing accurate user sessions and frequent navigation patterns. Unlike the simple session concepts in the time and navigation based approaches, where sessions are sequences of web pages requested from the server or viewed in the(More)
In this paper, sentiment classification techniques are incorporated into the domain of political news from columns in different Turkish news sites. We compared four supervised machine learning algorithms of Naïve Bayes, Maximum Entropy, SVM and the character based N-Gram Language Model for sentiment classification of Turkish political columns. We also(More)
Web usage mining is a type of web mining, which exploits data mining techniques to discover valuable information from navigation behavior of World Wide Web users. The first phase of web usage mining is the data processing phase, which includes the session reconstruction operation from server logs. Session reconstruction success directly affects the quality(More)
The "Sentiment Analysis" task focuses on the recognition and classification of emotions (positive, negative, conflict, neutral) in reviews for the aspect. In this paper we propose the system for recognizing and analyzing the sentiments using SVM for the restaurant and laptop review dataset. We compare the performance of the system with well-known KNN(More)
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