This presentation, by Joe Hilger of Enterprise Knowledge, was originally presented at the annual Fed KM Conference on May 14, 2019. In it, Joe offers enterprise search best practices and discusses enterprise knowledge graphs and ontologies.
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search is old and out of date.”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.
4. BUILDING A CONNECTED SEARCH
Action-Oriented
EK’s user centered process
for creating search interfaces
that help users get their job
done and not just find
information. Commonly seen
on Google.
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
6. SEARCH IS ABOUT PEOPLE FIRST
§ Your audience: personas and user journeys (reveals goals, needs,
opportunities).
§ Recognize that users may think about and look for information in
different ways.
§ Your goal is to help people get their job done.
@jhilgerbc, @ekconsulting
8. PRACTICAL KNOWLEDGE MANAGEMENT
EK’s Knowledge
Wheel
Practical Knowledge
Management uses
information sharing to
support action.
Action-oriented Search
follows these same
principles.
FIND
CAPTURE
CREATE
CONNECT
MANAGEENHANCE
ACT
@jhilgerbc, @ekconsulting
9. ACTION-ORIENTED SEARCH
Think Differently
1. Search is a detour from what I
want to do.
2. Everything I have is a
knowledge asset.
3. Each asset has a different
purpose.
4. Help me do my job!! I HAVE A JOB TO DO…
@jhilgerbc, @ekconsulting
10. ACTION-ORIENTED SEARCH
1. Identify what users want to
do.
2. Display information that
allows people to make a
decision.
3. Give users the ability to
take immediate action
from the search results.
@jhilgerbc, @ekconsulting
13. FACETED SEARCH
“Faceted navigation is arguably
the most significant search
innovation of the past decade.”
Search Patterns by Peter Moreville and Jeffery
Callender (O’Reilly, 2010)
@jhilgerbc, @ekconsulting
14. SIMPLIFY METADATA MANAGEMENT
Metadata “Card”
Title
Author
Doc Type
Product
Department
Free Text Entry
Policies
Procedures
Reports
Project Plans
User Documentation
…
IT
Finance
Marketing
Operations
Accounting
…
1. Minimize manual entry.
2. Prefill values based on
submitter, Location,
content, or Source.
3. Automate tagging using
tools.
• Auto-Categorization
• Text mining
• Auto-Tagging
@jhilgerbc, @ekconsulting
16. MACHINE LEARNING
§ Used to automate the tagging or
classification of content.
§ Two approaches: rules based or
statistical.
§ Rules frequently rely on NLP
technologies to understand parts of
speech.
§ Analyze user behavior to adjust
content relevance (personalized
relevancy).
§ Track user behavior to
disambiguate terms.
§ Often called cognitive search
Enhance Content Improve Search
@jhilgerbc, @ekconsulting
18. KNOWLEDGE GRAPHS
Another word for graphs are “networks”
Nodes
Edges
• 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
Google’s knowledge graph is a
popular use case
“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
@jhilgerbc, @ekconsulting
19. 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
20. 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.
21. HOW DO I GET STARTED
Educate the organization on how search can and should work.
Investigate the products and tools that you have access to that
can help improve search.
Inventory your content to understand what you have and how to
organize it.
Start small and then grow.