Science for SEO: research

Showing posts with label research. Show all posts

November 21, 2008

Issues with collaborative voting

Collaborative voting is used a lot these days in news systems, where people submit articles and others vote on whether they are interesting or not. The articles with the most votes are ranked highest if you like, making it to the much coveted front page.

There are some issues with these systems which cause degradation in user feedback, here are a few:

Not all votes carry the same weight - if an expert votes on an article and a layman does, the expert vote is the most noteworthy. There are problems with establishing who are the authorities on which topics.

Social voting: consistently voting for people you know and your friends. These are not always votes based on the quality of the article.

Sometimes though, users find that they appreciate articles from a certain author and track them, voting often on their submissions, but in this case, it is a genuine vote. It's hard to tell these apart.

Some votes are generated without much thought.

Some votes are given for fun or for profit.

There is a lot of research going on to resolve these issues, take a look at these to start with:

Complexity and Social Networks Blog of the Institute for Quantitative Social Science and the Program on Networked Governance, Harvard University

"A Few Bad Votes Too Many? Towards Robust Ranking in Social Media" (Jiang Bian, Yandong Liu, Eugene Agichtein, Hongyuan Zha)

"Dynamics of Collaborative Document Rating Systems" (Kristina Lerman)

October 24, 2008

bgC3

Despite the weekly "aw...Bill" bit in the TGIF posts, I like Bill. I think he's a cool guy who despite saying some silly things (I have too, but I'm not rich and famous so not a lot of people care), has been visionary. Lets not forget the work of "The Bill and Melissa Gates foundation" either.

Ok, his company, Microsoft, has ripped me off several times with rubbish OS, and expensive and unnecessary Office products (use OpenOffice), but I have to say that without Microsoft I may not have found so much of the free and amazing software I use now!

Anyway, that aside, he's creating a new company called bgC3 (Bill Gates Catalyst and 3 is his 3rd project). It's supposed to be a think tank. He is still Microsoft's chairman and is still involved there but has actually "left". This is him branching out and doing his own thing again. It's obviously all computer science and technology oriented research that he has in mind. The idea is that he'll bring together clever people to work on cutting-edge ideas.

This is what labs around the world do, get clever people to work on innovative and cutting-edge ideas and technology. The problem in academia is funding. This is something that bgC3 won't be struggling with I suspect.

Check out Tech Flash more a lot more information.

October 21, 2008

Internet progress fast - CS slow

I wrote a rather long post at High Rankings and decided that it deserved a place on the blog. A very good point was made by Randy about how fast the Internet moves. There are new developments almost daily, new systems, new ways of doing things emerge, and we all keep up with the new trends and algorithms. Computer science research that is 4 years old (or even older!) isn't as current, it is true.

This is because it takes ages for a lot of methods to be evaluated properly so that they can safely be used in public systems like search engines or social networks for example. Some systems aren't designed to use some methods, and only when they have gone through many iterations, they suddenly see the need to incorporate a certain method or even a few.

Stemming for example is quite old, it goes back to 1966 when the Lovins stemmer was made. Google I believe (but not totally sure of the exact date) implemented stemming to queries in 2003. That's 37 years! I think they were already using it in the internal system though, it's a pretty standard method in IR after all. I wrote a stemmer in 2005 and it only started being used in 2007, not a lot of people saw any use for a stemmer that stemmed to exact words, but now it's pretty standard too. That took 2 years.

PageRank came about in 1995 and was implemented when Google was publicly released in 1998, that's 3 years.

I work in conversational systems and it has taken a while for the science community and also the industry to see why they could be useful. Now there's a lot of research in this area, and the first chatbot was invented in 1966 (ELIZA). It's not until recently that companies have started using chatbots on their websites (Ikea for example) and suddenly the potential for such systems in IR is being realised. Long wait! We don't even have all the technology needed yet to make something really good.

I think it's really important for the SEO community to keep track of papers released by IR researchers and also NLP/AI researchers when the work is related to search engines particularly. It's useful to learn about the methods being developed and then it gives some insight into how they might be implemented (although this could take some time!). You can use Citeseer to find them, or DBLP, and checking the references too can be useful. Those are where my massive reading list comes from!

Of course some methods do get implemented quite quickly and I think that this happens when they are specifically built for a system in build progress. The big search engines have people working solely on this and also companies like IBM for example. What I mean is that you shouldn't discount methods that have been published a few years ago. A lot of social media stuff was published quite some years ago too.

Happy reading :)