Yahoo (who i work for) was well represented with more than 26 papers/posters. We had a booth in which we demo'ed YQL using its console on how one can get real time tweets from twitter translated using google translate api into many languages (including hindi). Yahoo's clues was also demo'ed. These demos were well received by those who stopped by. YQL wow'ed them with the power it can provide for developing mashup applications.
About the conference itself most of the sessions i attended had lots of papers related to twitter and social-media. It seemed as if the entire research community is doing free research for twitter (and none from twitter was there in the conference afaik). It is the power of open data from twitter and how the web community is enamored by them.
The best poster was about predicting popular messages in twitter. The best paper proposed a new model for product search based on maximizing the value of money for the user.
Dr.Abdul Kalam did the first key note on web for societal transformation. He suggested the www research community to help break all barriers especially the language and make the web accessible by each and every one.
Tim Benners Lee invetor of www did the second key note on designing the web for open society. He touched upon openness/net-neutrality, balancing between accountability and anonymity (in expressing opinions), democracy and transparency using web.
Christos Papadimitriou did the final key note on Games, Algorithm and Internet. He discussed the nash equilibrium (non zero sum multi player game). The cost of anarchy (as opposed to optimal path) is 4/3 (30% more), but the cost is unbounded if agents start acting on their own interests/optimizing.
Incentivizing high quality UGC is one of the papers from yahoo! research. This paper proposes a game theoretic model to balance between quantity and quality to encourage users to contribute content at optimal quality (by a simple rating model by viewers).
Buy it Now or take a chance analyzes the problem with second price auction (SPA) in scenarios like high targeted content. When you have much more precise targeting the number of advertisers interested in it reduces and it can become very attractive to a single advertiser. In this case the SPA is a losing proposition to content owner, auctioner. This paper proposes a buy-it-now price (or take a chance in bidding) to the advertiser which will be better than pure SPA.
Spatio Temporal Analysis:
Unified Analysis of Streaming News is a joint work of yahoo! research with CMU. This paper unifies the clustering, categorization and analysis (all three) of news articles to identify key entities, topics in the stories and reveal the temporal structure of stories as they evolve. The approach used is Rigorous Chinese Restaurant Process for story clustering and Latent Dirichlet Allocation (LDA) for topic extraction and Sequential Monte Carlo for inference.
We know who you followed last summer (in twitter) uses bounded methods to estimate when one user followed another. This is very good for estimating the followers of celebrity. The idea is to use the twitter follower graph which returns results in time sorted (latest follower first) and the user account creation time. One can find bounds of time for each user (his follow time has to be greater than his account creation time, but lesser than next person who follows) and with set of users one can find reasonable approximation.
Like Like Alike is a joint effort from yahoo. This paper proposes using both users interests and their friends to target the interests and friendship recommendation (than in isolation).