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Tag Archives: search performace

European Conference on Information Retrieval (ECIR) 2011 in retrospect

Posted on April 27, 2011 by Svetoslav Marinov
1

The European Conference on Information Retrieval (ECIR) 2011 took place in Dublin last week, 18-21 April. In this blogpost I would try to highlight some of the papers and talks from the conference which caught my attention and back it up with what other attendees said about it.

First, I was intrigued by the session on evaluation for IR and especially the topic of Croudsourcing. In my opition, the paper A Methodology for Evaluating Aggregated Search Results, which also got the prize for best student paper, was among the most pedagogically presented ones. It deals with the task of incorporating search results from a number of different sources, called verticals, into Web search results. By using a small number of human judgements for a given query the authors present the way to evaluate any possible permutation of verticals in the result presentation. I think that this methodology should be adopted in the world of Enterprise search, since it is exactly there where we crawl, index and present information from a number of different sources – Web, databases, fileshares, etc. The prerequisites are really minimal and low cost but the return value, the user experience, seems quite high.

Amazon Mechanical Turk, or the Artificial Artificial Intelligence, which is the marketplace for Croudsourcing, provides a way for a ridiculously small sum of money to perform evaluation, relevance assessment or any task for which you would need humans to give you some judgements. Leaving aside ethical issues, two papers in the conference presented ways of how you can utilize this service for some IR tasks.

Evgeniy Gabrilovich from Yahoo! Research, who won the Karen Sparck Jones award for 2010, gave a very interesting keynote talk on Computational Advertising. Up to now, it has never struck me how hard advertising in Information Retrieval systems is actually. I liked one of his points on the future of Ads – by using product feeds, one can automatically create product description via Text Summarization and Natural Language Generation and index this, thus avoiding bid words.

Another interesting and very pedagogically presented paper was about the gensim package by Radim Řehůřek. I definitely think we can use it in some of our projects. In general, text categorization and IR for social network were the dominant tracks. In one of the social networks tracks, Oscar Täckström presented a neat way of discovering fine-grained sentiment where some coarse-grained supervision is available. It really hooked me on trying it for any of our customers where sentiment analysis is required.

Thorsten Joachims, the last of the keynote speakers, gave a very inspiring talk on The Value of User Feedback. He put forward the idea of designing retrieval systems for feedback. In stead of just looking at the clicklogs post factum one can think of a system which uses the clicks feedback to learn, thus creating a better ranker for a given query and a given user need. In a single session, we can use click feedback to disambiguate the query and deliver results on the run which are of immediate benefit to the users.

Unfortunately, I guess I could have missed other interesting presentations but with two parallel sessions and several workshops there was a limit to what I could devour. What surprised me though, was that there were very few papers by the industry. We do try to solve exactly the same problems and tackle the same issues as academia. We, at Findwise, have constantly flagged the huge benefit of good, relevant Metadata for the task of achieving better search performace, which was also touched upon in the paper “Topic Classification in Social Media using Metadata from Hyperlinked Objects”.

It was really great to visit Dublin and attent ECIR 2011. It was an inspiring conference and I do believe that at next ECIR we, from Findwise, can be on the podium, sharing our knowledge and hands-on experience on Enterprise search and IR.

Sláinte!

Posted in Enterprise Search, Findwise, Internet search, Relevancy, Research, Search, Technology, User Experience | Tagged Amazon, Artificial Artificial Intelligence, Document classification, Dublin, European Conference on Information Retrieval, Evgeniy Gabrilovich, hard advertising, Information retrieval, Information science, Metadata, Oscar Täckström, retrieval systems, Science, search performace, search results, social media, social network, Storage, Thorsten Joachims, Web search results, Yahoo | 1 Reply

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