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 Despite the overall success of these conferences, the main drawback is that these working notes are not peer-reviewed.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.
By Frank Hopfgartner on February 10, 2017
By Tony Russell-Rose on February 10, 2017
Unless you’ve been on another planet for the last year or so, you‘ll almost certainly have noticed that chatbots (and conversational agents in general) became quite popular during the course of 2016. It seems that every day a new start up or bot framework was launched, no doubt fuelled at least in part by a growth in the application of data science to language data, combined with a growing awareness in machine learning and AI techniques more generally. So it’s not surprising that we now see on a daily basis all manner of commentary on various aspects of chatbots, from marketing to design, development, commercialisation, etc.
But one topic that doesn’t seem to have received quite as much attention is that of evaluation. It seems that in our collective haste to join the chatbot party, we risk overlooking a key question: how do we know when the efforts we have invested in design and development have actually succeeded? What kind of metrics should be applied, and what constitutes success for a chatbot anyway?
By Jose Alberto Equivel on February 10, 2017
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:
By Tony Russell-Rose on February 10, 2017
This year’s ECIR conference will include an Industry Day, following very successful events at ECIR in recent years. The Industry Day will be held on Thursday 13th April 2017, immediately after the regular conference program.
The Industry Day’s objectives are three-fold. The first objective is to present the state of the art in search and search-related areas, delivered as keynote talks by influential technical leaders from the search industry. The second objective of the Industry Day is the presentation of interesting, novel and innovative ideas related to information retrieval. Finally, a highly-interactive panel session will conclude the day, topic to be announced.
Speakers confirmed so far include:
By Stephane Goldstein on February 2, 2017
What do information retrieval (IR) and information literacy (IL) have in common? At a fundamental level, they are both concerned with enabling users to locate and retrieve information, and thereby to meet their information needs; and the deployment of IL is partly dependent on IR systems. To a large extent, there is therefore a common purpose, but both concepts approach this from rather different perspectives. Given current and growing concerns about ‘post-truth’ and the tension between information and misinformation, it is perhaps timely to reflect on how approaches to IR and IL can feed off each other.
By Andy Macfarlane on January 31, 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/
By Udo Kruschwitz on November 8, 2016
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!
So far so good, but Continue reading “Editorial”
By Helen Clegg on November 8, 2016
By Gabriella Kazai on November 7, 2016
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.
By Tony Russell-Rose on October 29, 2016
And finally… here’s the third installment of my trilogy of posts on the information retrieval challenges of recruitment professionals. The background to this (in case you missed the previous two) is that a few months ago I published a post describing our InnovateUK-funded research project investigating professional search strategies in the workplace. As you may recall, we surveyed a number of professions, and the one we analyzed first was (cue drum roll)… recruitment professionals.
It’s a profession that information retrieval researchers haven’t traditionally given much thought to (myself included), but it turns out that they routinely create and execute some of the most complex search queries of any profession, and deal with challenges that most IR researchers would recognize as wholly within their compass, e.g. query expansion, optimization, and results evaluation.