Mining QA Pairs from IRC Logs Using Simple Heuristics and a Chat Disentagler

Mon, 22 Apr 2013 03:56:46 -0400

Tags: IRC, QA


If you haven't heard of TikiWiki, it is a Wiki/CMS that follows the "Wiki way" also for development process: the development happens in SourceForge SVN and everybody is invited to commit code to the project. Even though that sounds brutal, it actually produces a very different development dynamic and a feature-rich product.

A number key people in the Tiki world live around Montreal and I have met some of them and been intrigued by the project for a while. It turns out their annual meeting ("TikiFest") was in Montreal/Ottawa this year so I got to attend for a few days and work on an interesting project: Mining Question/Answer pairs from #tikiwiki history. While the topic of mining QA-pairs has received a lot of attention in NLP and related areas, this is a real attempt at making this type of technology available to regular users. (You can see a demo on my local server.)

The process involves (see the page on for plenty of details):

  • Downloading the logs
  • Normalizing the IRC logs across different IRC logging clients
  • Identifying users that are likely to have asked questions
  • Identify the threads where said users participated
  • Assembling the final corpus
  • Indexing

To avoid having to annotate training data for the question identification, I'm using the approximation of finding IRC nicks that have only said 2 to 10 things in the whole logging history. The expectation is that the said users appear on #tikiwiki, ask a question receive an answer and left.

For the extraction step, I'm using a publically available implementation of Disentangling chat (2010) by Elsner and Charniak.

If this approach works, I can think of packaging it for use on other QA-oriented IRC channels (like #debian). If this interests you, leave me a comment or contact me.


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