Stack overflow knockoff for machine learning, NLP, AI, ...
metaoptimize.com
metaoptimize.com
Question: What little-known non-convex optimization trick has been used in most Berkeley NLP papers since 2006?
Answer: http://metaoptimize.com/qa/questions/14/what-are-the-state-o...
I am the person that built this site. I wasn't planning on announcing the site yet, until I disseminated it more widely in academic circles, because I wanted to establish a core highly technical user-base, but I guess this is fine. The quality of the users coming from HN has been great.
What people are saying about MetaOptimize Q+A:
Ryan McDonald (Google): "A tool like this will help disseminate and archive the tricks and best practices that are common in NLP/ML, but are rarely written about at length in papers."
Aria Haghighi (Berkeley): "Both NLP and ML have a lot of folk wisdom about what works and what doesn't. A site like this is crucial for facilitating the sharing and validation of this collective knowledge."
Bob Carpenter (Alias-I): "Par for the course, it’s a mix of wildly general (non-convex optimization) and reasonably specific (testing a random number generator) questions." (http://lingpipe-blog.com/2010/06/29/training-examples-a-stac...)
I'm targetting machine learning, natural language processing, vision, AI, statistics, data mining, neuroscience, etc. and other data-driven fields. As we've learned from StackOverflow, having a broad topic means that information cross-polinates between groups that don't normally communicate. This problem is particularly acute in academia.
It's a site for scientists to share knowledge and techniques, to document our ideas in an informal online setting, and to discuss details that don't always make it into publications.
Also, I've gotten a handful of job offers through answering questions on Quora. So hopefully this will connect people with gigs they like.
Why should you sign up and post a question or answer?
* Communicate with experts
* Crosspolinate information with experts in adjacent fields
* Answer a question once publicly, instead of potentially many times over email
* Share knowledge to create additional impact beyond conference or journal publication
* Find new collaborators
* Get job offers and gigs
The site is powered by OSQA. (http://osqa.net) I think it's unfair to the core developers to call it a StackOverflow knockoff, given that StackOverflow is---like most software---itself derivative.
I'm trying to disseminate this site to my peers and professors, to see if it will help people around.
- The functionality of Q/A seems to be exactly the same - The visual design is almost indistinguishable from that of StackOverflow - The classification of questions (votes/answers/views with tags) is identical - The badges that users can earn is a blatant copy from SO - "First time here? Check out the FAQ!". Hmmm, where have I seen that before...? - etc.
There may be some examples where the derivative vs. knock-off classification is debatable, but here, for me, the answer is clear.
Please note that I'm not making a judgement on whether this is better or worse than SO, and I'm not making a judgement on the skills of the developers. Building something that clearly builds on someone else's work without any attribution that I could see, leaves a bad taste in my mouth.
Unless of course I don't know the whole story and SO ripped of someone else. I'm awaiting enlightenment...
The software wasn't designed to work out of a subdir, so we're still ironing issues out on that front.
[edit: This happens for reasons that neither I nor the core devs understand: http://jira.osqa.net/browse/OSQA-204 ]
I fully support the decision to make this site especially if its not around yet.
Maybe this site will bring together all the ML people and do a better job.
Visually, the site is not that great. The logo is unreadable at first attempt
OSQA is supported by DZone, and the pace of development has been rapid. The core developers have stated on many occasions that they are moving in independent direction from StackExchange.
In particular, because the site is open-source, I can experiment with adding NLP to it. I can improve the Related Questions, I can automatically infer tags, and I can implement techniques for helping you organize and navigate information.
The selection process for new sites is community-driven:
http://area51.stackexchange.com/
. . . but it looks like a stats site is close to being a reality:
http://area51.stackexchange.com/proposals/33/statistical-ana...
As Chris Manning (Stanford NLP professor) says, Area 51 hasn't gotten any buy-in from the academic community. I have focused on getting academia to be the immediate core of the community, so that the quality of Q+A is high. I am able to do this because of my academic connections.
They are fragmenting the Q+A sites into four: http://area51.stackexchange.com/proposals/33/statistical-ana... http://area51.stackexchange.com/proposals/6607/artificial-in... http://area51.stackexchange.com/proposals/2761/natural-langu... http://area51.stackexchange.com/proposals/7607/machine-learn...
The last thing we need is NLP and ML people communicating less. That's why my site encompasses all of these proposals, as well as adjacent fields. As we've learned from StackOverflow, having one site for a broad topic leads to cross-polination of ideas between groups who don't normally communicate.
Most importantly, OSQA (which powers my site) is an open platform, built on Django+Python. That comes with all the benefits of open software. In particular, because the site is open-source, I can experiment with adding NLP to it. I can improve the Related Questions, I can automatically infer tags, and I can implement techniques for helping you organize and navigate information.
"automatically infer tag": tokenize / shingle q&a, ORDER token+bigrams BY TF-IDF(token + bigrams)
In both cases a global IDF estimate can be held in memory using a Counting Bloom Filter (or a traditional solr index).
Edit: Easy to fix. Replace http://metaoptimize.com/qa/qa/account/validate/ by http://metaoptimize.com/qa/account/validate/
I am getting complaints that validation email links don't work (they have the subdir twice, as you mentioned), even though welcome email links work just fine.
This is weird because they both use the exact same link in the template:
forum/skins/default/templates/auth/welcome_email.html: <a style="{{ a_style }}}" href="{% fullurl auth_validate_email user=recipient.id,code=validation_code %}">{% trans "Validate my email address" %}</a>
forum/skins/default/templates/auth/mail_validation.html: <a style="{{ a_style }}}" href="{% fullurl auth_validate_email user=recipient.id,code=validation_code %}">{% trans "Validate my email address" %}</a>