On Friday I was privileged to present a paper called ‘Towards Explainability in Professional Search‘ at the 3rd International Workshop on ExplainAble Recommendation and Search (EARS 2020), part of SIGIR 2020. This paper was co-presented with my colleague Andy MacFarlane of City University, and represents our collective thoughts and recommendations on how to develop more transparent, reproducible and explainable systems in professional search. Understandably, given our respective geographic locations the presentation was made remotely, and we are thankful for the local attendees who stayed around until 22:00 (local time) for our talk. The slides are available below. We view these recommendations as a conversation starter rather than the last word, so comments & feedback are particularly welcome. The paper itself is available for download from the EARS website.

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In our previous video we learnt how to use visual approaches to create the correct structure for our search strategy. In this video, we’ll look at techniques to create the right content.

A key task in developing effective search strategies is choosing the right keywords. But how do we create these terms in the first place? One way is simply to brainstorm them, i.e. think up related terms for each facet. Or you might use your search results as a source of inspiration. But is there a more efficient way to generate related terms?

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Last week I was privileged to present at the Singapore Chapter of ISKO on the topic of “Putting search theory to work on large datasets“. Understandably, given our respective geographic locations this presentation was made remotely, but I’m pleased to say we had a good attendance and a very informative discussion. Big thanks go to Patrick Lambe, Maish Nichani and Mark Garlinghouse for making this happen. The slides are available below, and the video should follow shortly. As always, comments & feedback welcome 🙂

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In this video, we’ll look at how data visualization techniques can help us optimize and re-use search strategies.

The benefits offered by visualization become more apparent as the complexity of your search increases. For example, here is a relatively complex search string used by a recruiter to find social profiles for project managers in the Republic of Ireland. As you can see, it is quite hard to visualize how this search is structured, and even harder to debug or improve.

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In our previous video we learnt how to build a search strategy and then save it and create a shareable link to it. In this video, we learn how to use visual approaches to make our searches smarter and more efficient.

Let’s return to the previous example where our research question concerned the role of physical activity in preventing obesity in older people. One of the immediate benefits of the 2D approach is that it you can see hit counts for each search block, displayed in the top right hand corner. You can use these to better understand which parts of your search to focus on when optimising your query.

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In this short video we’re going to learn how to save, share and collaborate on structured searches.

Let’s return to the example we saw earlier, where our research question was to investigate promoting physical activity to prevent obesity in older people.

Choosing the correct terms can take some thought and effort but to save time in this video we have already entered our preferred terms on the canvas. To create the Boolean logic we saw earlier, we simply drag-and-drop terms to create groups:

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IRSG logoJust in case you missed it, here are details of the latest issue of Informer, which came out on this week. As usual, lots of good stuff, with a mix of conference reviews, feature articles, news and updates in the world of IR. For further details see the Informer website. Or if you fancy becoming a contributor, get in touch!

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It’s been a little while in the making, but I am delighted this week to announce a new release of 2Dsearch. This contains a variety of bug fixes and improvement, notably support for:

  • Lens.org (a patent search facility and knowledge resource containing over 200m records)
  • Yandex (5th largest search engine worldwide)

We’re particularly excited about the support for Lens.org, as it opens up all sorts of possibilities to find meta-analysis, systematic reviews, review articles of topics you are interested in regardless of your discipline.

Moreover, you can now use 2Dsearch to search visually across 8 different databases, and use automated translations for many more.  We’ve also made various improvements to the quality of the query parsing and the help/guidance provided on the messages tab, and added an in-app link to our tutorial videos. In addition, search strategies are now saved with an annotations field for your own notes and shared by name (rather than anonymously).

We’ve lots more planned for the next release, so if you’d like to help shape this and/or have comments of your own then do let us know. We’d be delighted to hear from you!

Weave Journal of Library User Experience

I’m pleased to report that our paper ‘Designing the Structured Search Experience: Rethinking the Query-Builder Paradigm‘ has finally come out in Weave: Journal of Library User Experience. It’s been a long time in the making, partly as Weave comes out only twice a year, but mostly as we wanted to include some key changes and updates from our latest work. What makes this paper different is that for the first time we’ve had the scope and mandate to explore the UX issues in some depth. Whereas in previous papers we’ve rather glossed over these things as ‘simply good design’ or ‘what UX practitioners are meant to just get on and do’, in this paper we took the opportunity to demonstrate how solving a challenge like this involves a level of nuance and complexity that may not be immediately apparent to the untrained eye, and moreover, that what you see in the deployed app is actually the culmination of significant design exploration and thinking – much of which ends up on the ‘cutting room floor’. Even just the algorithm for painting the iteratively nested containers (in alternating white/blue) was non-trivial, as you need to avoid edges where boxes meet at different level of nesting, i.e. resulting in a white on white or blue on blue boundary. Ironically tho, that bit of detail, interesting tho it is, didn’t make the final cut: you’ll have to wait for a subsequent blog post for that 🙂

Anyway, feedback so far has been very informative. Keep it coming in! New release coming soon, so happy to accommodate thoughts & suggestions. Abstract appended below.

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