new technologies supporting technical intelligence anthony trippe, 221 st acs national meeting
TRANSCRIPT
New Technologies New Technologies Supporting Technical Supporting Technical
IntelligenceIntelligence
Anthony Trippe, 221st ACS National Meeting
Introduction
What is Technical Intelligence– Definitions– How Does it Fit with the Company’s Business
Strategy• The Intelligence Cycle
• Actionable Intelligence
– What is it Not
Introduction (Cont.)
Gatekeeper Approach to TI– The Intelligence Cycle
Ad-Hoc Team Approach to TI– The Intelligence Cycle
Introduction (Cont.)
Computer Assisted TI– Data Mining– Text Mining
Available Methods– Concept Clustering– Self Organized Maps (SOMs)– Neural Networks– Decision Trees
What Is Technical Intelligence?
Definitions:– A tool to assist with long term strategic technical
planning– Work processes for helping technical decision makers
make smarter decisions faster– An analytical process that transforms disaggregated
technological information into relevant strategic knowledge about your competitor’s technical position, size of efforts and trends
What Is Technical Intelligence?
How Does it Fit with the Company’s Business Strategy– Provides foresight into strategic activities
• Entering new business areas
• Acquiring new technologies
• Evaluating competitor’s business moves
• Project guidance
• Developing partnerships
What Is Technical Intelligence?
Actionable Intelligence– Intelligence Cycle
• Define needs and prepare a plan
• Collect source materials
• Analyze the results
• Impact the business
– Information when analyzed becomes intelligence– Intelligence directed towards a business decision
becomes actionable– Must be used by the decision maker
What Is Technical Intelligence?
What is it Not?– For Patentability– For Validity– For Freedom to Practice– Not about information its about intelligence– It is about trends and forecasting not about
focused and specific information retrieval
Gatekeeper Networks and The Intelligence Cycle
Define Needs and Prepare a Plan– Gatekeepers tend to be an expert in a specific
area and typically only work in that area– TI is a part time job and involvement is often
reactive– Tend to approach each problem the same way
(hammer and nail approach) and while excited and interested in subject may not have time to stay current with new intelligence methods
Gatekeeper Networks and The Intelligence Cycle
Collect Source Materials– Limited conference attendance– Personal journal reading– Personal networking– Heavy reliance on the “grapevine”
Gatekeeper Networks and The Intelligence Cycle
Analyze the Results– Manual Mapping
• Involves reading each document one at a time
• Information is collected by using:
– Spreadsheets
– Word Processor tables
– Flow charts
– Butcher paper and sticky notes
• Difficult to see hidden trends in large data sets
• Does not scale well
Gatekeeper Networks and The Intelligence Cycle
Impact the Business– Delivers message using:
• Handmade charts and graphs• Memos• Attendance at internal meetings
– Knowledge is power– Potential silo creation– NIH– Potentially limited to specific projects
Ad-hoc Team Approach to TI
Define Needs and Prepare a Plan– Each project is done on a case by case basis using a
team approach involving subject matter experts– TI Facilitators can communicate in a technically
proficient manner and are trained in the field of TI with frequent updates
– TI people are often employed full-time in conducting TI
– Provides directed, actionable intelligence to the specific business need
– The Need Drives the Question
Ad-hoc Team Approach to TI
Collect Source Materials– Size doesn’t matter– Any available electronic source is fair game– Print resources can be scanned in– Internal and external data– Also use human intelligence– The Question Drives the Data
Ad-hoc Team Approach to TI
Analyze the Data– The Data Drives the Tool– Computer Generated Maps Can:
• Group similar documents together
• Build landscapes based on semantic concepts
• Discover trends and do statistical analysis
– Mining Activities• Data
• Text
– Does not replace reading the source materials
Ad-hoc Team Approach to TI
Impact the Business– Delivers message using:
• Specific, focused charts, graphs and presentations• Detailed visualizations• Buy-in from subject matter experts
– Focused on business need– Knowledge is shared– Collective effort of many experts– TI team is a corporate resource
Computer Assisted TI
Data Mining– Relies on fielded (structured) data and exact
string matches– Involves numerically based statistical analysis– Allows for temporal analysis– Clustering based on coding– Involves co-occurancy matrixes
• Examination of patent subject matter by Assignee
Computer Assisted TI
Text Mining– Relies on unstructured or semi-structured data– Term extraction takes place based on semantic
based AI algorithms– Documents containing similar concepts can be
organized together (Classification)– Documents containing overlapping concepts
can be placed together geographically (Clustering)
Text Mining
Term Extraction
Linguistic Pre-processing
Tokens
Part of Speech
Stemming
Term Generation
Candidate Generation
Combination of Candidates
Term Filtering
Linguistic Patterns & Association Metrics
Information Retrieval Metrics
TFIDF
Reader
Text Mining
Information Extraction
Term Extraction
Named Entity Recognition
Co-Reference
Domain Knowledge Taxonomies
Available Methods
Concept Clustering– A form of SOM– Uses:
• Term extraction
• TFIDF
• Bootstrapping and generation of vectors based on shared concepts
– Topographical representation
Available Methods
Self Organizing Maps (SOMs)– WEBSOM a method for automatically
organizing collections of text documents and for preparing visual maps of them to facilitate the mining and retrieval of information
– Details on SOM algorithm can be found at: http://www.cis.hut.fi/research/som-research/som.shtml
Available Methods
Neural Networks– Started as model of biological neural networks in the
brain– Start with a training set– Use a second known set to measure difference
between guess and known result– Computer makes adjustment, guesses again– Iterative process until within tolerance– Results visualized with standard methods (SOM, et…)
Available Methods
Decision Trees– Represents a set of rules– Training set identifies rules based on defined
results and corresponding trends– Can be used on new data to make business
decisions– Also called expert systems