Thomas Grandell April 8 th, 2016 This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit

We help people learn new things by making it easy for them to find, or discover, relevant content in any data.

Etsimo Ltd Reinventing exploratory searching and content discovery Etsimo is a spinout from the University of Helsinki Cloud based visual content discovery platform Intent modelling + results visualization + human- computer interaction = iterative discovery process Technology result of 3 years of research with 2 patents Founded 2015, 6 employees, 3 of them internationally recognized scientists Backed by University of Helsinki Funds and TEKES* * The Finnish Funding Agency for Innovation.

Traditional searching i.e. query-response model or lookup searching Search intent is captured in the initial query only “Important”, i.e. high-ranked hits are at the top Long results list spanning several pages Users seldom go beyond the first few pages Advanced search features are complicated

Does it work? Lookup searching isn’t the answer for all use cases YES, if you know what you are looking for where to look for it how to formulate a query NO, if you want to learn/acquire new knowledge search for unusual findings, e.g. unknown unknowns

Why doesn’t it work? User needs to know the domain, the sources and the vocabulary Unfamiliarity with the domain – gap between current knowledge and desired knowledge Query formulation is challenging, too wide or too narrow User gets trapped within the initial query Too many results, no big picture The information bubble is hard to break According to Microsoft, up to half of all searches are exploratory

Case in point Finding unknown unknowns Suppose you’re an expert in domain X and you want to learn something new. For anything you know, you can build a query. But how do you query for something you don’t know about? Use your normal keywords and queries and go through several thousands of hits?

Live demo on Wikipedia Built to showcase the capabilities of our Visual Discovery Engine Two example scenarios for exploratory searching; 1.Refining an inexact query 2.Navigating the information space Demo information Complete English Wikipedia content, 5M articles, 35M docs Interface can look completely different from this one Hosted by Amazon Available at wikipedia.etsimo.com

The Etsimo technology Discovery beyond search A completely data driven visual discovery engine No special structure needed – works on just keywords in a full text index AI and ML used to create ad hoc connections (intent models) in the content Completely transparent, the user is directing the search Perfect for breaking silos and combining different data sets Surgical solution, won’t break current offering

Usability tests Outperforming text based search* Benchmarking visual discovery against text based search * Glowacka, D., Ruotsalo, T., et al.., Directing Exploratory Search: Reinforcement Learning from User Interactions with Keywords. In ACM IUI 2013 Proceedings of the 2013 ACM international conference on Intelligent User Interfaces, March 19-22, 2013 Santa Monica, CA USA, BEST PAPER AWARD. 109 % 57 % 3.8 x 2x2x Better user task performance finding novel information Better user task performance overall More interactions with the search results Pages viewed

Current work Completed implementations and work in progress Scientific publications Wikipedia University of Helsinki CRIS University of Helsinki Library Association of American University Presses & The National Academies Press OCLC Duodecim Oppiportti

Wrapping it up Visual discovery delivers excellent results Lookup searching is very effective when you know what you are searching for Exploratory searching doesn’t compete with lookup searching – the use case is different Using appropriate tools for exploratory searching gives superior results Better findability can be turned into more revenue ➟ more relevant content ➟ longer stays ➟ happier, returning customers ➟ higher conversions / more pages viewed

Thank You! Thomas Grandell