The document discusses using artificial intelligence and big data in knowledge management. It covers extracting knowledge from data through information architecture and data curation. It then discusses utilizing AI to deliver knowledge through chatbots using natural language processing, predicting trending knowledge areas, and personalizing knowledge delivery. The goal is to provide knowledge management that is dynamic, accurate, and personalized through leveraging AI technologies.

1. SIKM
May 18, 2021
Artificial Intelligence & Big Data
In
Knowledge Management
Copyright © 2019 A.J. Rhem & Associates, Inc. 1

2. Agenda
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About Anthony Rhem
& AJ Rhem &
Associates, Inc.
Introduction: KM, AI,
and Big Data
Extracting Knowledge
Organizing & Optimizing
Your Data
Utilizing AI in the
Delivery of Knowledge

3. About
Anthony J. Rhem
Anthony J. Rhem, PhD.: serves as the CEO/Principal
Consultant of A.J. Rhem & Associates, Inc., a
privately held Knowledge Management, Artificial
Intelligence, and System Integration Consulting,
Training and Research firm located in Chicago,
Illinois.
Anthony has over thirty (30) years of experience in
information technology with a focus in Knowledge
Management and Artificial Intelligence. A published
author, educator, and researcher; Anthony has
presented the application and theory of Software
Engineering Methodologies, Knowledge
Management, Artificial Intelligence, Information
Architecture, and Big Data at universities and
conferences in the US, Europe, Asia and Australia.
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4. Introduction
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5. KM, AI, and
Big Data
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THE EMERGING CHALLENGE FOR ORGANIZATIONS IS TO DERIVE MEANINGFUL INSIGHTS FROM
AVAILABLE DATA AND RE-APPLY IT INTELLIGENTLY. KNOWLEDGE MANAGEMENT PLAYS A
CRUCIAL ROLE IN EFFICIENTLY MANAGING THIS DATA AND DELIVERING IT TO THE END USERS TO
AID IN THE DECISION-MAKING PROCESS.
KNOWLEDGE MANAGEMENT (KM) AND BIG DATA WITHIN ORGANIZATIONS, THE ADVANCEMENT
OF SEARCH TECHNOLOGIES IS MAKING AN IMPACT. THE “FINDABILITY” OF INFORMATION AND
KNOWLEDGE WITHIN LARGE AMOUNTS OF UNSTRUCTURED DATA CONTRIBUTE TO THE ABILITY
TO DISSEMINATE AND REUSE THE KNOWLEDGE OF THE ENTERPRISE.
AI THROUGH PREDICTIVE ANALYTICS AND KNOWLEDGE FLOW OPTIMIZATION WILL PROVIDE A
DYNAMIC, ACCURATE AND PERSONAL DELIVERY OF KNOWLEDGE. AI WILL ENABLE ANALYZING
AND SYNTHESIZING DATA TO DERIVE MEANINGFUL KNOWLEDGE.
Copyright © 2021 A.J. Rhem & Associates, Inc.

6. KM, AI, and Big Data
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BIG DATA IS UNIQUELY POSITIONED TO TAKE ADVANTAGE OF
AI ANALYTICS, KM PROCESSES AND PROCEDURES.
THESE PROCESSES AND PROCEDURES ENABLE KM TO PROVIDE
A RICH STRUCTURE TO ENABLE DECISIONS TO BE MADE ON A
MULTITUDE AND VARIETY OF DATA.
THE TOTAL PICTURE IS WHAT SHOULD DRIVE DECISIONS”. KM
ENABLES ORGANIZATIONS TO TAKE THE TOTAL PICTURE BIG
DATA PROVIDES.
LEVERAGING AI TOOLS THAT PROVIDE PROCESSING SPEED TO
BREAK UP THE DATA INTO SUBSETS FOR ANALYSIS WILL
EMPOWER ORGANIZATIONS TO MAKE DECISIONS ON THE
VAST AMOUNT AND VARIETY OF DATA AND INFORMATION
BEING PROVIDED.
Copyright © 2021 A.J. Rhem & Associates, Inc.

7. Extracting Knowledge:
Organizing & Optimizing
Your Data
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8. Extracting Knowledge from Data starts
with: Information Architecture
Information Architecture: Information architecture (IA)
focuses on organizing, structuring, and labeling content
in an effective and sustainable way. The goal is to help
users find information and complete tasks. To do this,
you need to understand how the pieces fit together to
create the larger picture, how items relate to each other
within the system – Usability.gov
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9. Information Architecture
Classifications
& Hierarchies
Labels &
Indexing
Navigation Search
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INFORMATION ARCHITECTURE CONNECTS PEOPLE TO YOUR DATA
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10. Three Major Parts of Information
Architecture
Users
• Users: Information
needs, audience
types, expertise, tasks
• [How to Use the
Information]
Content
• Content: Document
types Objects,
structure, attributes,
Meta-information
• [How to describe the
information]
Context
• Context: Business
models & goals,
corporate culture,
resources
• [Where information is
used]
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11. IA Optimizes Knowledge Flow
• An understanding of how
knowledge flows throughout
your organization is
essential for delivering KM
• Using IA: Connecting
explicit knowledge to the
tacit knowledge holders
creates a holistic view of
knowledge.
• Tacit knowledge holders
• workers who are experienced
with executing certain tasks,
developing a solution, working
in a specific industry, practice
area or company while
leveraging the stored
knowledge.
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Connect
Collect
Store
Use/Reuse
Learn
Create
New
Store New
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12. IA: Data Curation for Big Data Analytics
• IA effects Big Data Analytics through Content (Data)
Curation
• Content (Information & Knowledge) Curation is an essential
step to enabling Big Data Analytics to be effective
• Curate the content adding the necessary metadata
(descriptive, structural, administrative) and categorization
elements aligning it to the domain taxonomy (apply
Information Architecture).
• Content curation provides the methodological and
technological data management support to address data
quality issues maximizing the usability of the data.
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13. Content Curation Process
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14. Utilizing AI to Deliver
Knowledge
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15. AI in KM Knowledge Delivery
• AI plays an important part to KM by elevating how the
delivery of knowledge occurs to the people who need it. AI is
used to scale the volume and effectiveness of knowledge
distribution.
AI KM
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16. AI Powered Delivery of Knowledge
To provide KM, the delivery of knowledge must be
• Dynamic
• Dynamic knowledge is constantly updated adhering to your
organization’s content (information and knowledge) lifecycle
management processes. This also includes the experts who can provide
insights about the knowledge. The Dynamic component of knowledge
reflects your organization’s brand, tone and evolves over time.
• Accurate
• The Accurate component of knowledge is identified as the authoritative
source and authoritative voice for that subject matter. This knowledge is
accepted by your organization as the “source of truth”.
• Personal.
• The Personalized component of knowledge answers the questions that
the users of your knowledge are seeking. Personalized knowledge is
tailored to what the individual need to make a decision and presented in
a way that is tailored to the device and applications the users are
leveraging to access answers to their questions. Personalized knowledge
is facilitated by how knowledge flows throughout your organization.
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17. AI Powered KM: Chatbots w/ Natural
Language Processing (NLP)
Personalize knowledge –
through specialized
knowledge assistants
(bots) working together
with users, knowledge can
be made available in a
personalized way
depending on the needs of
the consumer.
Chat Bots will provide
value for all knowledge
workers in the various
business areas along
critical decision-making
points with personalization
of the delivery of
knowledge.
Copyright © 2020 A.J. Rhem & Associates, Inc. 17

18. Copyright © 2020 A.J. Rhem & Associates, Inc.
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Predict trending
knowledge areas/topics
that your knowledge
workers needs
Identify which targeted
knowledge will resonate
with your knowledge
workers based on real-
time engagement and
content consumption
Personalize knowledge
based on individual
preferences
Improve content
decisions by leveraging
machine learning around
what content will be best
suited to address the
situation
AI will make search and
its search products more
relevant, precise and
efficient.
AI through intents will be
able to better know what
content your knowledge
workers need. Intents will
provide a better
understanding of what a
person is looking for by
better understanding the
intended use of the
content.
Chatbots w/ Natural Language Processing
(NLP): will provide cognitive capabilities to
understand, interpret and manipulate human
language that will enable the bots to anticipate
the needs, attitudes and aspirations of users to
aid in decision making and improve outcomes,
all geared to achieve substantial business
value.
AI will power
the delivery of
Knowledge by
providing the
ability to :

19. AI in KM Predicting Trending Knowledge
• Predict trending knowledge areas/topics that your
knowledge workers needs
• Leverages supervised learning algorithms that will
learn over time.
• Supervised learning allows the algorithm to make inferences
from labeled data.
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20. Discussion
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21. Anthony J. Rhem, PhD.
CEO/Principal Consultant
205 North Michigan Ave., Suite 810
Chicago, Illinois 60601
Phone: 312-396-4024
email: tonyr@ajrhem.com
Website: www.ajrhem.com
Blog: http://knowledgemanagementdepot.com/
Latest Book:
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