URL Classy: Guessing a class for a URL only from its text
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#URL Classy

Guessing a class for a URL only from its text. See a live demo.


URL Classy is a library that assigns a top-level dmoz category based on the URL text. It is an implementation of URL-based classifier in JavaScript.

See http://wiki.duboue.net/index.php/URL_Classifier

Work in progress, not nicely packaged yet. Do not look at this code as an example of how to pack things.

To use it, download content.rdf.u8.gz from dmoz.org and extract a training file as follows:

$ zcat content.rdf.u8.gz | perl -ne 'if(m/<ExternalPage/){($u)=m/about=\"(.*)\"\>/}elsif(m/\<topic/){($t)=m/\<topic\>Top\/(.*)\<\/topic\>/}elsif(m/\<\/ExternalPage/){print "$t\t$u\n" if($t and $u);$t="";$u=""}'|sort|uniq | gzip - > full_cat_urls.tsv.gz
zcat full_cat_urls.tsv.gz | perl -ne '@a=split(/\t/,$_);@b=split(/\//,@a[0]);push@b,'Top'; print $b[0]."\t".$b[1]."\t".$a[1]' > two_cats_urls.tsv

(or download a snapshot from http://aprendizajengrande.net/two_cats_urls.tsv.gz)

then train the classifier with

$node train/stay_classy.js two_cats_urls.tsv

full training using two level classes is currently running into out of memory problems (maybe related to https://code.google.com/p/v8/issues/detail?id=847 ?).

The current demo (in example/) is trained in top level class and 10%. Unseen performance is 54% accuracy but that includes lots of repeated URLs. Actual performance seems to be at 30% at most.

(The current training code uses only 1% of the data, change lines 77 and 81 to increase the percentage of the file to use.)

See example.