strategic decision making with exploratory search toby mostyn cto polecat
TRANSCRIPT
Strategic decision making with exploratory search Toby Mostyn
CTO Polecat
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
What is the point of Polecat?
Intelligent searching
on
public conversations
Unlocking the Potential of Social Media!
Architecture
Searchplatform
News
Blogs
Social media
MeaningMine
Importer
Indexing
InformationExtraction
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
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
Beyond traditional search
Irish Government: setting the agenda for the Irish Economic Forum
Query + results = failure to meet information need
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
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!
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
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
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
Results: Finding “insights” in the noise
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
Solving both problems: an exploratory paradigm
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
Darwinian algorithms
Polecat Ecosystem
Business
Academia
Darwinian algorithms Public search application: summarisation engine
Plug-in architecture for 3rd party algorithms/ visualisations
Crowd source judgements
Published evaluation tables (weekly/monthly)
Darwinian algorithms
Ranked insight by query type
Ranked insight combinations
Ranked visualisation by insight type
Individual scores for each contributor
Darwinian algorithms
