The document discusses enhancing search experiences by implementing connected knowledge graphs and semantic technologies to improve information retrieval. It emphasizes the importance of actionable and context-rich search results that cater to user needs rather than traditional keyword-based searches. The discussion also highlights the growing significance of integrating structured and unstructured data to enable more effective natural language search and aggregation of information.

1. CREATING CONNECTED SEARCH EXPERIENCES
November 7, 2019

2. JOE HILGER
• Principal Consultant and co-founder at Enterprise
Knowledge.
• 20 years of KM and technology consulting
experience.
• 13 years experience implementing enterprise
search solutions.
• Worked on close to 100 different search projects
for companies around the world.
@jhilgerbc, @ekconsulting

3. “Why can’t our search be more like
Google?”
“I can’t find anything on our
company search.”
“Our search would be great if
people would just tag their
content.”
“Everything I find on our company
search is old and out of date.”
“I don’t trust our company search.”
“Lets just use Google search so
that we never have to worry about
search again.”
SEARCH COMPLAINTS
Comments I have
heard more than once
during our search
workshops.
@jhilgerbc, @ekconsulting

4. BUILDING A CONNECTED SEARCH
Knowledge Graphs
A semantic technology used
to aggregate information and
map content relationships.
Typically used to power
Natural Language Search and
Artificial Intelligence.
Faceting
Navigation based on
taxonomies and metadata that
allows users to filter search
results to find information
more quickly.
Machine Learning
Newer technologies that
improve the way content is
tagged and search results are
presented.
“The best search experiences connect people to information,
information to people, and people to people.”
@jhilgerbc, @ekconsulting
Action-Oriented
Rich search results that help
users get their job done and
not just find information.
Commonly seen on Google.
Roger F. Hilger
Sr. Manufacturing Project Engineer
Roger F. Hilger

5. ACTION ORIENTED SEARCH
Action-Oriented
Rich search results that help
users get their job done and
not just find information.
@jhilgerbc, @ekconsulting
Search is about things not strings
Search is a detour from what your searchers
are trying to do
Do not force your searchers down false paths
Key considerations:
Roger F. Hilger
Sr. Manufacturing Project Engineer
Roger F. Hilger

6. GOOGLE: MOVIES
I would like to see a
movie and I am trying
to find the one I want
to see
I want to…
• Get tickets on-line
• See movie times and
locations for the next 4 days
• View previews of the movie
to see if I will like it.
• See critics reviews
• Find out what other people
thought of it.
@jhilgerbc, @ekconsulting

7. EK CUSTOMER: EXPERT SEARCH
I need to speak with
an expert in neurology
to help answer a
question.
I want to…
• Understand a person’s
expertise
• Contact them
• Understand where they are
• Learn who they work for or
which department they work
for
@jhilgerbc, @ekconsulting

8. EK CUSTOMER: CONFERENCE ROOMS
I want to book a
conference room for
my upcoming
meeting.
I want to…
• Find which conference rooms
are open
• Understand which room best
meets my purposes
• Find a room that is close to
me
@jhilgerbc, @ekconsulting

9. KNOWLEDGE GRAPHS
Knowledge Graphs
A semantic technology used
to aggregate information and
map content relationships.
Typically used to power
Natural Language Search and
Artificial Intelligence.
@jhilgerbc, @ekconsulting
• A knowledge graph: a network of the
things we want to describe and how
they are related
• We construct a semantic model since
we want to capture and generate
meaning with the model
“The application of graph processing and graph DBMSs will
grow at 100 percent annually through 2022 to continuously
accelerate data preparation and enable more complex and
adaptive data science.”
– Gartner’s Top 10 Data and Analytics
Technology Trends for 2019

10. WHAT IS A KNOWLEDGE GRAPH
Content Sources
Subject Predicate Object
Project A hasTitle Title A
Person B isPMOn Project A
Document C isAbout Topic D
Document C isAbout Topic F
Person B IsExpertIn Topic D
… … …
Business Ontology
Graph Database
Enterprise
Knowledge Graph
Business Taxonomy
Person B
Project A
Document C
Person F
Topic D
Topic E
@jhilgerbc, @ekconsulting

11. BENEFITS OF A KNOWLEDGE GRAPH
Understanding Context
Relationships between
information allows gives us a
better understanding of how
things fit together so that search
can be more precise.
Structured and
Unstructured Information
Graphs allow for the integration of
structured and unstructured
information so that users can
search for data and content at the
same time.
Natural Language Search
Graphs store information the way
people speak. Integrating a
graph into your search makes
natural language search easier to
implement.
Aggregation
Graphs allow for aggregation of
information from multiple
disparate solutions so that search
results can display information
that exists in multiple locations
and formats.
@jhilgerbc, @ekconsulting

12. EK CUSTOMER: PEOPLE
@jhilgerbc, @ekconsulting

13. EK CUSTOMER: TOPICS/PROJECTS
@jhilgerbc, @ekconsulting

14. GOOGLE’S KNOWLEDGE GRAPH
@jhilgerbc, @ekconsulting

15. WE’LL BE ANSWERING QUESTIONS NOW
Q A&
THANKS FOR LISTENING
Q & A SESSION