Shape retrieval - a tricky task

Welcome and Happy New Year! “We had a great 2016. 2017 will prove to be even better” as an anonymous letter writer assures me … although he/she/it also assures me that the European Union is doomed and that I should respect the democratic will of the British people. What better way to start the year than with a few friendly words?
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A Case for Satellite Events in Evaluation Campaigns

Local conferences, such as TREC in North America, CLEF in Europe, and NTCIR in Asia, play a leading role in promoting information retrieval research by supporting novel campaigns and releasing datasets to share the latest research challenges. To gain access to these datasets, participants are requested to communicate their work in the form of working notes. Despite the overall success of these conferences, the main drawback is that these working notes are not peer-reviewed. This may pose problems, especially for researchers who cannot easily afford or justify travel expenses to attend such conferences. To overcome the problem of distance, we organised an experimental satellite session that allowed participants of the Asia-based evaluation campaign NTCIR to present their work either in Europe or in Asia. Given participants’ feedback, we see this as an attractive method to foster research and innovation beyond continental borders.

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Search Solutions 2016 – Matching the IR talent supply and demand in the industry

Great thing about Search Solutions: the Audience

This past November 30th 2016, the British Computer Society hosted the Search Solutions forum at its London Offices.

It was divided into 5 sessions with the following themes: 1. Understanding users and context, 2. Moving towards question-answering, 3. Beyond web search, 4. New modes of search, and 5. Panel session. Particularly interesting, was the panel session, in which attendees and participants alike had a discussion on the possible reasons talent in Information Retrieval (IR) was so hard to find and not matching the industry’s demand. This article will attempt to summarize each of the 4 sessions preceding the panel; using issues and solutions that arose during the panel as a framework to structure the summary. First, I will attempt to summarise and list the panel’s main talking points. Afterwards I will map the talks given at the forum to these points, and will conclude with a personal take on these issues.
The panel session’s discussion was taken over by the unmet IR talent demand in the industry, observed (by some if not all of the attendees). This problem was also described as a lack of interest in IR areas by working technology professionals and students. After describing the problem this way, the discussion yielded the following possible causes:

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Events Winter 2017

One Day Events

Search Solutions 2017. The annual practioner focused event for the IRSG held at the BCS offices in Covent Garden, together with a tutorial day on 28 November 2017, with the main event on 29th November 2017.


CHIIR 2017: ACM SIGIR Conference on Human Information Interaction & Retrieval. A conference focusing on the interaction aspect of search. 7-11 March 2017. Oslo, Norway. http://sigir.org/chiir2017/

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Welcome to the Autumn 2016 edition of Informer! It’s been a busy few months and as you can see we waited until the election period was over before going live so that we can now officially confirm (hot off the press) that Stefan Rüger is the new chair of the IRSG. Stefan brings in many years of experience on the committee and I would say let’s give him a round of applause!

Breakfast means Breakfast (Scottish proverb)

So far so good, but Continue reading “Editorial”

Deep Learning In the News – Digest

It seems you can’t go very far these days without hearing something about Deep Learning. Here is a quick digest of some of the recent Deep Learning news and blog posts and a couple of pointers to potentially useful resources.

This compilation was made possible thanks to Lumi News AI. Articles in this digest appeared on my own personalised feed at some point in the past. I picked articles either based on recency, popularity or relevance to the context of this digest. This is not intended as a comprehensive review of deep learning.

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