strategic decision making with exploratory search toby mostyn cto polecat
TRANSCRIPT
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Strategic decision making with exploratory search Toby Mostyn
CTO Polecat
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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
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What is the point of Polecat?
Intelligent searching
on
public conversations
Unlocking the Potential of Social Media!
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Architecture
Searchplatform
News
Blogs
Social media
MeaningMine
Importer
Indexing
InformationExtraction
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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
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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
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Beyond traditional search
Irish Government: setting the agenda for the Irish Economic Forum
Query + results = failure to meet information need
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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
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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!
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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
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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
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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
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Results: Finding “insights” in the noise
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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
![Page 15: Strategic decision making with exploratory search Toby Mostyn CTO Polecat](https://reader035.vdocuments.us/reader035/viewer/2022062404/5519d1df550346443e8b4ac1/html5/thumbnails/15.jpg)
Solving both problems: an exploratory paradigm
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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
![Page 17: Strategic decision making with exploratory search Toby Mostyn CTO Polecat](https://reader035.vdocuments.us/reader035/viewer/2022062404/5519d1df550346443e8b4ac1/html5/thumbnails/17.jpg)
Darwinian algorithms
Polecat Ecosystem
Business
Academia
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Darwinian algorithms Public search application: summarisation engine
Plug-in architecture for 3rd party algorithms/ visualisations
Crowd source judgements
Published evaluation tables (weekly/monthly)
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Darwinian algorithms
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Ranked insight by query type
Ranked insight combinations
Ranked visualisation by insight type
Individual scores for each contributor
Darwinian algorithms
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