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Python, log data mining for frequent templates

I need to develop a weblog data mining tool.

Having many sequences of URLs requested in a particular user session (extracted from web application logs), I need to figure out usage patterns and groups (clusters) of website users.

I'm new to Data Mining, and now a lot of Google savvy. Some useful information was found, that is, the query "Frequency of development of patterns in weblog data" seems to indicate almost exactly similar studies.

So my questions are:

  • Are there any python based tools that do what I need, or at least something like that?
  • Can the orange toolkit provide any help?
  • Can any help read the book Programming Collective Intelligence ?
  • What is Google, why read, what relatively simple algorithms are best used?

I am very limited in time (up to about a week), so any help would be extremely valuable. I need to point me in the right direction and advice on how to complete the task as soon as possible.

Thanks in advance!

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2 answers

1 & 2: Orange has a frequency mining module. It also supports clustering.

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Source: https://habr.com/ru/post/1747447/

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