Trip Database Blog

Liberating the literature


February 2015

The light at the end of the tunnel…

…is, I hope, not the light of an oncoming train. I’ve nabbed that line from my favourite band – Half Man Half Biscuit (HMHB) who wrote The Light At The End Of The Tunnel (Is The Light Of An Oncoming Train) a good few years ago! My love for HMHB aside, I keep reflecting on how things seem to be going really well for Trip and I’m desperately hoping we’ve turned a corner.  So, why the optimism:

  • 2014 was pretty good.
  • We’re working on the new Freemium version of Trip.  What’s going to come out is going to be impressively good and some of the premium upgrades will be great.
  • We’re involved in the really interesting EU funded project which will be doing some really innovative things.  I’ll blog about that more when the final specifications are agreed, but we’ll be looking at making Trip more multi-lingual, we’re going to be improving the Trip Rapid Review system and loads of work around similarity which is useful for the next point.
  • Relatedness/similarity is looking very useful for what we want to do with regard developing our financial viability.  The measures we’re developing will allow us to do all sorts of interesting things, for instance we can highlight a new book that’s useful to a particular clinician, we can highlight a new trial that’s pertinent to an existing systematic review.  Many more uses on top of that, but I’ve got to keep some secrets.
  • I’m starting to realise the value in our clickstream data (helped by two separate teams and soon to be joined by a PhD student as part of the EU project).  You only have to look at most of this year’s blog posts to see I’m working hard on this.  This can help with the relatedness work but it can do other useful things, such as improving the search results and better predicting new articles that are of use to a Trip user.  If our mission is to ensure health professionals get the right evidence to support their care – using clickstream data will make it so much more effective.  The advantage of the clickstream data is that it’s Trip’s data to utilise, it’s our IP.  It’s at the heart of our future.  I actually think it’s this point that’s making me so happy/optimistic.
  • Lots of other nice bits and bobs e.g. I’ve just been invited to lecture in the USA in Autumn/Fall; I’m part of a large consortium bidding to be a support team for complex reviews; I’m presenting at the wonderful Evidence Live; I’m making headway in my new NHS job (I am lead for Knowledge Mobilisation for Public Health Wales); I’m waiting to hear about a large MRC grant (not optimistic but something to look forward to).

Long may this continue!

Another use for clickstream data

In the previous post (Clickstream data and results reordering) I highlighted how the clickstream data could be used to easily surface articles that are not picked up by usual keyword searches.  That post highlighted how it could be used to improve search results.  In my mind I was thinking this could help surface documents to improve a clinician trying to answer their clinical questions.

But what about in systematic reviews (or similar comprehensive searches)?  A couple of scenarios spring to mind:

  1. A user conducts a search and find, say 15, controlled trials.  We could create a system that highlights the most connected clinical trials that have not been selected already.  So, possibly an in-built safety check to ensure that no trials are missed.
  2. Related concepts.  You see some spectacularly complex search terms, no doubt human generated.  There may be other systems but we could surface related concepts.  A simple example was shown in the early post (Clickstream data and results reordering) where it highlighted that obesity is related to diet.  OK, we all know that – but the computer didn’t, it spontaneously highlighted it.  Doing this on a large scale using Trip’s ‘big data’ will generate more obscure relationships – potentially very useful in generating a comprehensive search strategy!

If there are any systematic reviewers/searchers I’d love to hear what you think!

Clickstream data and results reordering

Recently I’ve been discussing the potential for using our clickstream data (our earliest post on the subject being from October 2013).  After a post earlier this year Ok, I admit it, I’m stuck I have been contacted by two separate people who have both been very generous with their time and on Friday I met with one of them who talked me what they had found.

Before I share the results there are a few points to consider:

  • This really is early days and it needs some imagination to see how it would work on Trip.
  • The image below is one trial, simply to illustrate a point.  The results are not based on the full Trip index, just a very small sample.
  • The search is using a very simple text matching for title words only.  So, as you will see in the image below all the articles in the left-hand column have the search term – diet – in the title.

So, what’s going on?

The left hand side are the results in this mock-up search.  However, those on the right-hand side have been reordered using simple clickstream data.  Those articles that are surrounded by the light blue colour have been boosted (so appear higher) due to lots of people clicking on them.  Those results surrounded by orange are arguably more interesting – as they don’t include the search term in the title!

What this signifies is that users of Trip, while searching the actual Trip, have clicked on the orange articles in the same search session as one of the articles on the left-hand side.  So, it’s telling us that the orange articles are related to the normal results – and being inserted into the results – even though they were not matched in our search test by having the word diet in the title.

Trying to describe this in the blog is slightly difficult as I’m not sure if I’ve explained it particularly well.  I suppose there are two take homes:

  • Clickstream data, even using a small sample, can undercover some really useful articles that a standard keyword search might miss.
  • I am very excited by this, so have faith in that!

    Blog at

    Up ↑