ICT$371$ Artificial Intelligence

Tutorial $11$

Week $11$: Clustering Twitter data in rapid miner studio

Task: Use K$-$Means Clustering to Identify Twitter Topics in RapidMiner

Import the twitter dataset from the week $11$ section of the moodle page. After importing, do the following:

Now we have to clean the data and the first step is to convert the data into text and do some text processing. Add Nominal to Text operator into the process. Now use Replace operator to remove any URL in the tweets, you can also remove any @ data as well. We have to use a regular expression to remove the URL which is $($http$($s$)?)$:VV$($www$.)?$a$-$zA$-$Z$0-9$@:$\%.\_|+*$#$=](2,256\}\backslash .[$a$-$z$](2,61\backslash$bI$-$a$-$

ZA$-$Z$0-9$@$\%\_\backslash +.$~#$2$&$//=*$

Parameters

$$ Replace

stribute filer bype v

invert selection

$$ incude special attributes

replace what

Khttp$$s$23$Ww$?$a$-24\mathrm{.}20-3$@$\%\_1$~$8=12\mathrm{.}256113-212\mathrm{.}6100$