fishing in an ocean of information
TRANSCRIPT
Fishing In an Ocean of Information
www.tupaisystems.co.il
Fishing In an Ocean of InformationFishing In an Ocean of Information
An Intelligent fishing net has to catch a handful of interesting communications out of millions.
What is needed :- A dynamic search model (new rules, new inferences, new facts
are added all the time).- A model that is self adjustable - accumulating knowledge as it
tracks specific communications.- Personalised search models – building on history and chain of
communications- Linkable with other models – X knows Y who knows Z.- Self learning – Make a guess – see results – adjust accordingly.
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Fishing In an Ocean of InformationFishing In an Ocean of Information
Combining different forms of knowledge - Explicit – facts, rules- Implicit – statistical relations- Not being hooked on the obvious - the enemy is not
necessarily a fool, so stereotyped search behavior will fail
Combining different source of knowledge- Text Mining (conversations, e-mails, reports )- Data Mining – Locations, Events, History Records- Detective knowledge – Hints, Intuition, Experience- Propositional and Temporal Logic – following along a
plausible causal chain- Self Learning from past activations of the model
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Fishing In an Ocean of InformationFishing In an Ocean of Information
Tracking Communications Over Time.
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• 1.5.2000 – X is talking to Y about “the shipment”
• 10.6.2000 - Y notifies “arrival of goods”, raise the issue of payments.
•1.7.2000 – Y promises “payment” will be made soon
Search model has to track significance across multiple communications (phone, chat, e-mails, bills of lading…)Model makes new connections, adjust probabilities, searches for more information according to current and previous activations.
Assembling Pieces of the PuzzleAssembling Pieces of the Puzzle
Assemble Pieces of KnowledgeInto an Active Knowledge ObjectWhich Itself Can be Assembled...
Tom’s Model
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John is coming tomorrow
John’s Model
Fred’s Model
Fishing In an Ocean of InformationFishing In an Ocean of Information
Ability to connect many models dynamically
The conversation interacts (possibly) with 2 models - when John is mentioned, his model (if available) is brought in or created.
Real Time Risk Analysis
Real events spawn hypothetical events which spawn...The logical and time interaction of these event chains determines the risk of a catastrophic event
Fishing In an Ocean of InformationFishing In an Ocean of Information
Creating individual “Case” processors and keeping them up to date on the threat environment by transmitting knowledge in the form of undirected network
Monitoring Transmissions
The case models are adapting to their cases, while continuing to receive
general information
Fishing In an Ocean of InformationFishing In an Ocean of Information
The problem is dynamic in many dimensions - protagonists, communication channels, locations, types of threat....
So is the network structure used to continuously track and solve it......