It is a supervised classification problem.
For example, a very simple case:
say, overall we collect 4 pages from the data set: { web_page 1 web_page
2 web_page 3 web_page 4 }
then users may have input vectors like:
user1 [1 1 0 0]
user2 [1 1 0 0]
user3 [0 0 1 1]
user4 [0 0 1 1]
user5 [0 0 1 1]
... ....
then whatever classification algorithm mahout has should return
classification results as
group 1 { user1, user2}
group 2 { user3, user4, user5 }
On Fri, Nov 9, 2012 at 10:29 AM, Sean Owen <[email protected]> wrote:
> First: what question are you trying to answer from this data? You are
> trying to classify users into what, for what purpose?
>
>
> On Fri, Nov 9, 2012 at 4:20 PM, qiaoresearcher <[email protected]
> >wrote:
>
> > Hi All,
> >
> > Assume the data is stored in a gzip file which includes many text files.
> > Within each text file, each line represents an activity of a user, for
> > example, a click on a web page.
> > the text file will look like:
> >
> >
> ----------------------------------------------------------------------------------
> > user 1 time11 visiting_web_page11
> > user 2 time21 visiting_web_page21
> > user 1 time12 visiting_web_page12
> > user 1 time13 visiting_web_page13
> > user 2 time22 visiting_web_page22
> > user 3 time31 visiting_web_page31
> > user 1 time14 visiting_web_page14
> > ... .... ..........
> >
> > I am thinking to first construct a web page set like
> > { visiting_web_page11, visiting_web_page12, visiting_web_page31, .......
> }
> >
> > then for each user, we form a vector [ 1 0 0 1 0 0 ..... ] where
> > '1' means the user visited that page and 0 means he did not
> > then use mahout to classify the users based on the vectors
> >
> > does mahout has example like this? if not, what kind of java code we need
> > to write to process this task?
> >
> > thanks for any suggestions in advance !
> >
>
