Download Knowledge Management and Collexis

Presentation by Yuri de Lugt
Presentation structure
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Definitions of knowledge management
•
Forms of knowledge
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Knowledge infrastructure
•
Collexis background
•
Collexis application examples
•
Demonstrations (optional)
Definitions Knowledge Management
Collexis definitions on KM
• Data
“Structured data”
(data, stored set of a meaningful combination of characters and symbols)
• Information
“Data with ADDED value for the receiver”
• Knowledge
“Combined information and experience in the minds of people”
“Knowing how to act to retrieve optimal added value”
• Competence
Combination of Knowledge, skills and behavior that leads to an
essential contribution to achieving the goals of the business
Collexis definitions on KM
• Knowledge management:
“Creating an enviornment in wich knowledge will retrieve
maximum added value”
“Actions and Rules based on a consistent strategy witch
enables an organisation and her employees to use the
available knowledge as a strategic production factor for
optimal performance.”
Forms of Knowledge
To perform ‘Knowledge Management’ one needs to
know what forms of Knowledge are there.
‘Forms’ of Knowledge
• Explicit Knowledge
– Stored, Transferable Knowledge.
– Handbooks, Information Systems, Procedures, etc.
– Information
• Tacit (implicit) Knowledge
– In peoples minds
– Improved by experience
– Not stored, hard to store
Knowledge transformation
To
Tacit
From
Tacit
Social
External
•Copy by seeing
•Report
•Imitate
•Visualize
•Master-student
•Modelling
Internal
Explicit
Explicit
•Learn by doing
Combine
•Merge
•Recombine &
systemize
Collexis definitions on KM
Thus:
•
Knowledge is not manageable
•
Only the circumstances in which Knowledge can be explored best are
manageable
•
Only explicit knowledge can be stored
•
Implicit knowledge can be made accessible
► Collexis facilitates the optimum circumstances to explore and
develop knowledge.
The Knowledge infrastructure
To find out where Collexis can be of use, we must
explore the Knowledge infrastructure
Knowledge infrastructure
Structure
IT
& processes
Knowledge flow
•Develop
•Share
•Use
•Evaluate
Culture
Management
3 Instrument Groups
© Human Connection 2000
Collexis & Knowledge management
• Collexis facilitates:
Retrieving information (portals, search and retrieval)
Merging information to support Knowledge processes
(dynamic categorization, heat maps, content graphs, etc.)
Access knowledge by identifying experts (expert finder)
Analyzing information to retrieve knowledge (semantic web)
Information mining (semantic web, heat maps, content graphs)
►How ?
Collexis Approach
Collexis Functions
Content Resources
Business Cases
Tools
Collexis Approach
Business Cases
Tools
XML
Web
Documents
Databases
content
Collexis Functions
Collexis Approach
Concept
Maps
Aggregation
Homonym
detection
Fingerprinting
Structured data
XML
Web
Documents
Databases
Business Cases
Tools
content
Associative
Concept Graphs
Collexis Approach
Gap analysis
Competitor
Analysis
Semantic
Networks
Homonym detection
Specialized
Search
Who is Who
Structured data
Dynamic Portals
Vocabulary search,
textual search
Associative
Concept Graphs
Concept
Maps
Aggregation
Fingerprinting
applications
information mining
information matching / searching
Web
Documents
Databases
content
XML
Collexis Approach
levels of information management
level 1:
Aggregation
Fingerprinting
Concept
Maps
Gap analysis
Semantic Networks
Competitor Analysis
Homonym detection Specialized Search
Structured data
Dynamic Portals
Who is Who
applications
level 2:
Associative
Concept Graphs
Vocabulary search,
textual search
information matching / searching
XML
Web
Documents
Databases
content
level 3:
information mining
Collexis Approach
levels of information management
level 2:
use of explicit links,
thesaurus hierarchy,
contextual information
use of normalization,
language independency,
synonyms, matching,
thesaurus / vocabulary
level 1:
Associative
Concept Graphs
Aggregation
Fingerprinting
Concept
Maps
Gap analysis
Semantic Networks
Competitor Analysis
Homonym detection Specialized Search
Structured data
Dynamic Portals
Who is Who
applications
use of cooccurrence,
concept clustering,
ontologies
Vocabulary search,
textual search
information matching / searching
XML
Web
Documents
Databases
content
level 3:
information mining
Collexis
Why it was created and how it works
One Million Hit Syndrome
• Billions of gigabytes of information is available
• Is this bad news or good news?
• How to manage?
– Human indexing is too expensive
– Automatic indexing is usually not advanced enough
– Keyword search provides too little or too much
Information Abundance
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Increasing amount of digital information in organizations
Stored in different forms and different formats
Spread over a variety of databases and archives
Internet adds staggering volumes of information
The Human Touch
• Store Explicit Knowledge in (relational) thesauri
• Use free texts and content relations
• Explore and use linguistic techniques
• Searching for documents or knowledge?
– Knowledge is embedded in people
– Collexis behaves like a (human) expert
– Collexis finds information, experts and
organizations
– Collexis supports knowledge exploration
The power of Fingerprints
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Collexis is based on the principle of Fingerprinting
Fingerprint: a profile of a piece of information
A Fingerprint contains a list of weighted concepts
Concepts are derived from a Thesaurus
Fingerprint characteristics: unique and small
100% Malaria
35% Agencies
30% Enthusiastic
28% Collaboration
27% Funding
27% Africa
25% Science
15% Dedications
15% Applaud
15% agenda
14% Inaccurate
14% advocacy
13% hope
13% research funding
13% Fund Raising
What is a thesaurus?
A thesaurus is a specialized vocabulary (“repository of knowledge”) of a
particular domain, such as medicine, energy or ICT. It contains selected
words, terms and concepts with their semantic relations in a hierarchical
structure and can also contain synonyms
Means
of transport
Simplified Thesaurus example
Aircraft
Airplane
Train
Motor Vehicle
Automobile
Car
Plane
Truck
Lorry
Collexis®, the concept
indexing

Concept
matching
Word-based
Searching
What? Why?
How? Who?
indexing

The magic of Fingerprinting
Emails
Word
Jobs
RFP’s
CV’s,
Skills
average
average
Articles
books
content fingerprints
organization
fingerprints
people
fingerprints
Multi concept & free text
Concept Fingerprints
Query text
or
document
+
Σ
MATCH
Free text Fingerprints
Result list
Collexis characteristics
• Accurate and sensitive
Collexis Fingerprints are highly sensitive and accurate, and can
be manipulated to optimize search results
– Precision: only relevant documents shown
– Recall: all relevant documents shown, even when narrowing the search
• Performance
even in millions of documents, search results should be provided
instantly
• Human approach
not only documents, but also experts and organizations can be
the result of a search
Collexis characteristics
• Open architecture
Easy integration by the use of an API
• Omnivore
Collexis processes structured and unstructured information; this
is possible in one action
• Adaptable
Collexis respects existing databases and does not require large
hardware investments
• Fast in any language & language independent
Collexis works across languages.
Some Collexis markets and applications
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Publishing (portals)
Scientific organizations (Referee finder)
Biotechnology (Genes and protein identification)
Pharmaceutical & Chemical (Research and development)
Library (Research)
Healthcare (Intranet)
Legislation & Jurisdiction (Legal Intelligence)
Universities (Research and Portals)
International Authorities (Information Mining)
Collexis Application Examples
Search and Retrieval
Indexing
Search results
Experts retrieved
Refine a search
Use the thesaurus
Use the thesaurus
Information sharing
Add2Collexis
Add2Collexis
• Find information and experts;
• Search assistance through so called “proposed concepts”
• Available for domains Life Sciences, ICT, food and agriculture
(other knowledge domains on request);
• Supported formats: MS-Word, RTF, .txt, HTML and .pdf;
• Fully web enabled;
• Application based on Microsoft® .Net technology.
Add2Collexis
Search using thesaurus intelligence
e-Vamp
• Automatically enriches existing web pages with hyperlinks;
• Use thesaurus for concept recognition ;
• Allows the user to apply a Collexis match for related documents,
experts or external database information;
• Outlinking to other search engines;
• Configured for different domains
Original document
e-Vamped document
Search using e-Vamp
ClipFinder
• small client application
• easy to use
• complete texts as query
input
• makes use of clipboard
• fast
Meta-Analysis
Knowledge maps
Networks for Meta-Analysis
Demonstrations (optional)
Thank you!
Choice ofChoice
word
measured
phrase
above
the reach
of and
word and
measured phrase
above
the reach
ordinary men.
of of
ordinary
men.
William Wordsworth
(William Wordsworth)