1. Strategic decision making with exploratory search Toby Mostyn CTO Polecat

2. Failing to meet the information need Results: Finding insights in the noise Queries: Handling complex topics Solving both problems: an exploratory paradigm What is the point of Polecat? Darwinian algorithms Agenda

3. What is the point of Polecat ? Intelligent searching on public conversations Unlocking the Potential of Social Media !

4. Architecture Search platform News Blogs Social media MeaningMine Importer Indexing Information Extraction

5. Failing to meet the information need Results: Finding insights in the noise Queries: Handling complex topics Solving both problems: an exploratory paradigm What is the point of Polecat? Darwinian algorithms

6. Failing to meet the information need What are the issues that people care about most? Forming Policy Give me an up to the minute / long-term info on an issue Issue Management What/who is my product associated with? Brand Management I need to know,quickly,all about x Briefing Overview

7. Beyond traditional search Irish Government: setting the agenda for the Irish Economic Forum Query + results = failure to meet information need

8. Failing to meet the information need Results: Finding insights in the noise Queries: Handling complex topics Solving both problems: an exploratory paradigm What is the point of Polecat? Darwinian algorithms

9. Queries : handling complex topics Information need: What is the discussion around innovation in the UK economy? Simple keyword = failure User unable to assess and select keywords User unable to formulate complex boolean query All (relevant) documents are important!

10. Queries : handling complex topics Query by document Feed in 1 to n documents Pseudo relevance feedback Query extraction -> query expansion Exploratory interface Results become query prompts Users build iterative queries

11. Failing to meet the information need Results: Finding insights in the noise Queries: Handling complex topics Solving both problems: an exploratory paradigm What is the point of Polecat? Darwinian algorithms

12. Results : Finding insights in the noise Solution: Insights: extracted information/statistics that describe the data Information Retrieval Statistics Topic models Sentiment analysis Entity extraction Show me the data! Goal: provide the user with an exploratory overview of the results

13. Results : Finding insights in the noise

14. Failing to meet the information need Results: Finding insights in the noise Queries: Handling complex topics Solving both problems: an exploratory paradigm What is the point of Polecat? Darwinian algorithms

15. Solving both problems : an exploratory paradigm

16. Failing to meet the information need Results: Finding insights in the noise Queries: Handling complex topics Solving both problems: an exploratory paradigm What is the point of Polecat? Darwinian algorithms

17. Polecat Ecosystem Polecat Ecosystem Business Academia

18. Darwinian algorithms Public search application: summarisation engine Plug-in architecture for 3 rd party algorithms/ visualisations Crowd source judgements Published evaluation tables (weekly/monthly)

19. Darwinian algorithms

20. Ranked insight by query type Ranked insight combinations Ranked visualisation by insight type Individual scores for each contributor Ranked insight by query type Ranked insight combinations Ranked visualisation by insight type Individual scores for each contributor Darwinian algorithms