Create Great Parser - Extract Relevant Text From HTML/Blogs

Question

I\'m trying to create a generalized HTML parser that works well on Blog Posts. I want to point my parser at the specific entrie\'s URL and get back clean text of the post it

Answer 1

There are projects out there that specifically look at filtering out the 'noise' of a given page. Typically the way this is done is by giving the algorithm a few examples of a given type of page, and it can look at what parts don't change between them. That being said, you'd have to give the algorithm a few example pages/posts of every blog you wanted to parse. This usually works well when you have a small defined set of sites you'll be crawling (news sites, for instance). The algorithm is basically detecting the template they use in HTML and picking out the interesting part. There's no magic here, it's tough and imperfect.

A great example of this alogrithm can be found in the EveryBlock.com source code which was just open-sourced. Go to everyblock.com/code and download the "ebdata" package and look at the "templatemaker" module.

And I don't mean to state the obvious, but have you considered just using RSS from the blogs in question? Usually the fields have the entire blog post, title, and other meta info along with them. Using RSS is going to be far simpler than the previous solution I mentioned.

Answer 2

Boy, do I have the perfect solution for you.

Arc90's readability algorithm does exactly this. Given HTML content, it picks out the content of the main blog post text, ignoring headers, footers, navigation, etc.

Here are implementations in:

• JavaScript
• Perl
• PHP
• Python
• Ruby
• C#

I'll be releasing a Perl port to CPAN in a couple of days. Done.

Hope this helps!