Web mining: implementando técnicas de data mining en un servidor web
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As mentioned before, algorithms for mining frequent patterns in data stream can also be distinguished depending on whether they consider the frequency of the patterns from the
We propose that which Baeza-Yates (2009) calls content mining and in this case particular deals with textual data. The mining process was done through an ad hoc [06] Crawler,
In this sense the grouping of students with similar learning behavior could significantly help in the e-learning personalization, by the fact that the teacher can
Linked data, enterprise data, data models, big data streams, neural networks, data infrastructures, deep learning, data mining, web of data, signal processing, smart cities,
And finally, using these results on evolving data streams mining and closed frequent tree mining, we present high performance algorithms for mining closed unlabeled rooted
The variable activity contains the activity name, complete indicates how much the student has completed the activity, variable grade stores the activity mark of the student, action
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Among the most widely- used prediction techniques are the Naive Bayes classifier (NB), as a modern statistical technique, and the Artificial Neural Networks (ANN) and Decision