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From Philippe de Rochambeau <phi...@free.fr>
Subject Re: Log analysis with GraphX
Date Sat, 10 Feb 2018 15:28:20 GMT
Hi Jörn,
thank you for replying.
By « path analysis », I mean « the user’s navigation from page to page on the website
» and by « clicking trends »  I mean «  which buttons does he/she click and in what order
». In other words, I’d like to measure, make sense out of, and perhaps, predict user behavior.

Philippe


> Le 10 févr. 2018 à 16:03, Jörn Franke <jornfranke@gmail.com> a écrit :
> 
> What do you mean by path analysis and clicking trends?
> 
> If you want to use typical graph algorithm such as longest path, shortest path (to detect
issues with your navigation page) or page rank then probably yes. Similarly if you do a/b
testing to compare if you sell more with different navigation or product proposals. 
> 
> Really depends your analysis. Only if it looks like a graph does not mean you need to
do graph analysis . 
> Then another critical element is how to visualize the results of your graph analysis
(does not have to be a graph to visualize, but it could be also a table with if/then rules
, eg if product placed at top right then 50% more people buy it). 
> 
> However if you want to do some other  analysis such as random forests or Markov chains
then graphx alone will not help you much.
> 
>> On 10. Feb 2018, at 15:49, Philippe de Rochambeau <phiroc@free.fr> wrote:
>> 
>> Hello,
>> 
>> Let’s say a website log is structured as follows:
>> 
>> <date and time>;<web item trigram>;<web page trigram>;<user
id>
>> 
>> eg.
>> 
>> 2018-01-02 12:00:00;OKK;PAG1;1234555
>> 2018-01-02 12:01:01;NEX;PAG1;1234555
>> 2018-01-02 12:00:02;OKK;PAG1;5556667
>> 2018-01-02 12:01:03;NEX;PAG1;5556667
>> 
>> where OKK stands for the OK Button on Page 1, NEX, the Next Button on Page 2, …
>> 
>> Is GraphX the appropriate tool to analyse the website users’ paths and clicking
trends, 
>> 
>> Many thanks.
>> 
>> Philippe
>> 
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