I gave this presentation at the Mendeley Advisor Appreciation 1 day workshop in Mendeley's London office on 21 September, 2012. This presentation introduces the concept of recommender systems, providing a number of use cases in which they have been deployed, before focussing on Mendeley Suggest. In the workshop, the slides served as a focus point for an open floor discussion on Mendeley Suggest as a product.

1. Mendeley Suggest:
What will you read
next?
Kris Jack, PhD
Chief Data Scientist

2. Being the best researcher you
can be!
➔
Good researchers are on top of their game
➔
Large amount of research produced
➔
Takes time to get at what you need

3. Query driven
How to query for
interesting research
for you?

4. Search Vs. Recommendation
➔
search is a pull strategy
vs.
➔
recommendation is a push strategy

5. Search Vs. Recommendation
search is like
following a path...

6. Search Vs. Recommendation
recommendation is
like being on a roller
coaster...
A different
sense of
control

7. What's a recommender?
“A recommendation
system (recommender) is
a subclass of information
filtering system that aims
to predict a user's interest
in items.”

8. Recommendation Systems in the Wild (people)

9. Recommendation Systems in the Wild (books)

10. Recommendation Systems in the Wild (music)

11. Recommendation Systems in the Wild (films)

12. Recommendation Systems in the Wild (jokes)

13. Recommendation Systems in the Wild (love)

15. Input:
User libraries
Output:
Suggested articles to read

16. Recommendation Systems in the Wild (research)

18. Mendeley Suggest:
What will you read
next?
➔
Mendeley's suggestions are based on what you read
➔
Help you deal with the problem of information overload
➔
Help you to discover new research
➔
Our system is improving as the community grows
➔
What do you want from Mendeley Suggest?

19. Over to you
How many papers do
you read a day?
What do you want from
Mendeley Suggest?
Have you tried it yet?
How well does it work
Do you feel like you're for you?
on top of your domain?
How would you
What would your perfect improve it?
Mendeley Suggest
experience be? Have you
discover it yet?