Build better searches using data visualization

Summer’s finally here, and with it comes another milestone for 2dSearch: alternative visualisations. The default ‘Nested’ view has its strengths, but it isn’t to everyones liking. So we’ve added two completely new ways to view, understand and optimise your searches:

• Tree View, which uses the metaphor of the family tree, with a root node at the top and successive generations of children below
• Inline View, which maps hierarchical structure onto physical structure with groups aligned a common midline, allowing a traditional left-to-right ‘Boolean string’ reading

And of course you still have the Nested View, which maps hierarchical structure onto a series of nested containers. And all of this for free! There’s lots more details in our Medium post, but for the best experience just try them out for yourself.

Think outside the search box: https://www.2dsearch.com/

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New views, new insights: data visualisation to optimise search and discovery

Have you ever had that moment when you’ve seen something out of the corner of your eye, then turned to look but it’s gone? We’re left feeling cheated, as if some magic took place that was never intended for our eyes. But the reality is often more prosaic: cells in the human retina are arranged such that movement and contrast are better perceived around the peripherae, while the central region is better suited to colour and detail. It’s a simple explanation, but one that reminds us that in order to better understand, we sometimes need to see in different ways.

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How to create Boolean searches using drag and drop

Just published the following video on Youtube, which complements last week’s piece on the topic of How to debug and optimise Boolean strings. As always, comment & feedback welcome.

Struggling with complex Boolean searches? Editing Boolean strings is inefficient & error prone.

With 2dSearch you can visualize your search in 2D, then drag & drop blocks to optimise and refine. Use automated query suggestions to refine your search. Works with Bing, Google, Google Scholar, PubMed, TRIP, Epistemonikos and more. When you’re done, you can save & share your own collection of search templates and best practices.

Think outside the search box: https://www.2dsearch.com/

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How to debug and optimise Boolean strings

Just published the following video on Youtube, Twitter et al. Sharing here for completeness!

Not seeing the results you expected? Debugging complex searches can be a frustrating experience. Don’t waste time editing Boolean strings: find and fix errors the visual way. Visualise your search in 2D, switch parts on & off, enable and disable terms…experiment and optimise, then save and share.

Think outside the search box: https://www.2dsearch.com/

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Searching in the Tower of Babel

You may have noticed on this blog that I’ve been busy with a number of things just recently, but I’m pleased to report that we’ve been continuing to add useful features to 2dSearch, and one of them in particular deserves a shout out here.

As you may know, many professions need to perform searches that are comprehensive, accurate and repeatable, using strategies that search across multiple databases with platform-specific syntax and operators. For example, a recruiter looking to fill a particular data science role may want to search LinkedIn, Stackoverflow, Github, and other social forums to find suitable candidates. Likewise, a clinician or information professional performing a systematic literature review may need to search numerous databases such as PubMed, Embase, Web of Science, PyscINFO, and more. In each case, their search query has to be manually ‘translated’ to the syntax and user interface of each database. All of this is tedious, error-prone, and inefficient.

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Rethinking ‘Advanced Search’: A New Approach to Complex Query Formulation

I am delighted to announce publication of our latest open-access scholarly paper ‘Rethinking ‘Advanced Search’: A New Approach to Complex Query Formulation‘, which has just been published in the proceedings of the 41st European Conference on Information Retrieval (ECIR) in Cologne. This work is a collaboration with Jon Chamberlain and Udo Kruschwitz of Essex University, and accompanies our demo at the event.

The paper focuses on the application of query visualisation to structured searching and in particular the challenges associated with the recruitment profession, and hopefully complements some of the more opinion or design-oriented posts on this site. I’ve appended the abstract below. For free access to a copy, visit the ECIR website.

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Introduction to Natural Language Processing (slideshow)

Earlier this week I gave a talk called “Introduction to NLP” as part of a class I am currently teaching at the University of Notre Dame. This is an update of a talk I originally gave in 2010, whilst working for Endeca. I had intended to make a wholesale update to all the slides, but noticed that one of them was worth keeping verbatim: a snapshot of the state of the art back then (see slide 38). Less than a decade has passed since then (that’s a short time to me 🙂 but there are some interesting and noticeable changes. For example, there is no word2vec, GloVe or fastText, or any of the neurally-inspired distributed representations and frameworks that are now so popular (let alone BERT, ELMo & the latest wave). Also no mention of sentiment analysis: maybe that was an oversight on my part, but I rather think that what we perceive as a commodity technology now was just not sufficiently mainstream back then.

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