We have entered the era of smart applications. Chatbots, recommendation services, knowledge discovery tools and analytics solutions are deployed across various industries to enhance digital customer interaction and increase operational efficiency. The demand for talented and experienced developers and technology professionals is constantly exceeding supply. However, applying and extending the usage of new machine learning algorithms and building an agile data infrastructure are only one side of the medal. Companies need to enable their subject matter experts to work with cognitive applications in order to create business value. Working with semantic technologies is a qualitatively driven way to enhance smart applications. In this talk you will learn how knowledge graphs make text processing transparent. The system intelligence can be extended and adapted by reshaping the knowledge graph. As the human brain evolves, so does a knowledge graph. See how subject matter experts start steering and training cognitive applications.

1. Nika Mizerski
Product Manager
Semantic Web Company
How to make
cognitive
applications
even smarter
1

2. 2Agenda
Semantic Technologies in a nutshell
How Semantic Technologies and other
technologies play together
Use Cases, Demos and an outlook in the future

3. Who we are
3
Semantic Web
Company
Product manager at
Nika
Mizerski
developer and
vendor of
2004
founded
6.1
current
Version
active at
based on
Vienna
located
part of Enterprise
Knowledge Graphs
manages
standard for
part of
enriches
>200serves customers
Taxonomies
Ontologies
standard for

4. Fundamental
Assumption
4
We do not search for
documents only,
but rather for things
and facts about them.
Machines shall help to
create links across
data silos to give
answers to questions.
Converging AI
Technologies

5. Content
Management
Lifecycle
5

6. Four-layered
Content
Architecture
6

7. Dynamic
Content
Publishing
7 Recommender Systems AnalyticsSemantic Search
Dynamic Content
Publishing
Automatic Content
Authoring
Your Use Case

8. The Fusion of Search, Recommendation and Analytics

9. The “delivery
team” of smart
applications
9

10. Building a
Knowledge
Graph with
PoolParty
10

11. The knowledge
model behind
the Wine /
Cheese
recommender
11

12. PoolParty
Semantic
Classifier
Text Classification
based on Machine
Learning and
Semantic
Knowledge Models
12
PoolParty Semantic Classifier combines machine learning algorithms
(SVM, Deep Learning, Naive Bayes, etc.) with Semantic Knowledge Graphs.

13. Queries, Validation, Axioms,
Transformations
(SHACL, SPARQL,
OWL)
Mappings &
Linkings
Entities, Labels &
Relations
Start simple,
grow over time
Linked Data as
pay-as-you-go
data integration
technology
13
Schema
(SKOS, RDFS)
PoolParty supports several modes of knowledge graph management
Human-made knowledge models (ontologies and taxonomies), automatic entity
linking, corpus learning, relational data and XML to graph transformations, ...

14. Fusion of
Search,
Knowledge
Discovery &
Analytics
14
Find more Success Stories at https://www.poolparty.biz/download-zone/

15. Linking Data
with Thesauri
15

16. A question at
the end
Will Artificial
Intelligence
make
Subject Matter
Experts
obsolete?
16 Imagine you want to
build an application
that helps to identify
patients and
treatments pairings.
Which will you prefer?
Applications solely based on machine learning, those ones which
are based on doctors' knowledge only, or a combination of both?

17. Knowledge
Graph
17