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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)
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)
The growth of World Wide Web is incredible as it can be seen in present days. Users find it very difficult to extract useful and relevant information from the huge amount of information. The problems can be solved by Web Usage Mining which involves preprocessing, pattern discovery and pattern analysis. Preprocessing is an important process which converts(More)
Webusagemining is a type ofwebmining,which exploits datamining techniques to discover valuable information from navigation behavior ofWorldWideWeb users. Thefirst phase ofwebusagemining is thedataprocessingphase,which includes the session reconstruction operation from server logs. Session reconstruction success directly affects the quality of the frequent(More)
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