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Predicting the next request of a user as she visits Web pages has gained importance as Web-based activity increases. Markov models and their variations, or models based on sequence mining have been found well suited for this problem. However, higher order Markov models are extremely complicated due to their large number of states whereas lower order Markov(More)
In web recommender systems, clustering is done offline to extract usage patterns and a successful recommendation highly depends on the quality of this clustering solution. In these types of applications, data to be clustered is in the form of user sessions which are sequences of web pages visited by the user. Sequence clustering is one of the important(More)
OBJECTIVE We aimed to determine Axis I psychiatric disorders in women with hyperemesis gravidarum (HG) and to follow up the course of psychiatric disorder and its association with nausea and vomiting (NV) during pregnancy. METHODS The study sample was composed of 47 patients with HG. Psychiatric interviews were conducted using the Structured Clinical(More)
Content-based classification of audio data is an important problem for various applications such as overall analysis of audiovisual streams, boundary detection of video story segment, extraction of speech segments from video, and content-based video retrieval. Though the classification of audio into single type such as music, speech, environmental sound and(More)
World Wide Web is the biggest source of information. Though the World Wide Web contains a tremendous amount of data, most of the data is irrelevant and inaccurate from users " point of view. Consequently it has become increasingly necessary for users to utilize automated tools such as recommender systems in order to discover, extract, filter, and evaluate(More)