More Related Content Similar to 111 Blumauer - A Five-Star Rating System for Semantic Search (20) More from Andreas Blumauer (20) 111 Blumauer - A Five-Star Rating System for Semantic Search1. © Semantic Web Company - http://www.semantic-web.at/ and http://www.poolparty.biz/
A Five-Star
Rating System for
Semantic Search
Andreas Blumauer
CEO of Semantic Web Company
2. © Semantic Web Company - http://www.semantic-web.at/ and http://www.poolparty.biz/
Key questions in this talk
● Beyond precision and recall: What makes a ‘good’ search?
● Beyond document search: What other types of
‘semantic search’ exist?
● Beyond search: What other use case scenarios than ‘search’
benefit from linked data and knowledge graphs?
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Connotation of ‘semantic’
From: Wortschatz Leipzig - http://wortschatz.uni-leipzig.de/
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Some facts and figures
Vertical search & Enterprise search:
● Currently 201 ‘Semantic Search’ Startups (https://angel.co/semantic-search)
● Around US$ 900 million of venture capital
Web search:
● Wikipedia’s pageviews declined 21% the year after Google Knowledge Graph
was launched
● Google search volume for json-ld
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Diverse promises made by
‘Semantic Search’ vendors
Use
Weotta
and get
inspired.
Search is outdated. Google
steers you to right section of
the library, but doesn’t
answer your question or
compile that answer with
others to help you make a
decision.
Ambiance can
automatically match the
meaning of the page to
the products that are
most contextually
relevant in real time.
Benefit from
additional insights
through interactive
visualizations of
reports and search
results derived from
your data lake
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So, what is ‘Semantic Search’?
It’s all about improved user experience, no matter
how complex information procurement is:
I am a web shopper.
I want to have nice buying
experiences when using an
online shop.
I am a doctor. I need a 360-
degree view on my patient. I
don’t have the time to search
around.
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Semantic Search is about
precise contextualization (personalisation)
Semantic search engines are able to link entities in a
meaningful way. They extend graphs ‘on-the-fly’ by
reusing already existing knowledge graphs.
“Which skateboard fits to my
jacket and its manufacturer also
produces snowboards?”
“Which new medical studies
about allergy ABC talk also
about symptoms related to my
current patient?”
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A simple semantic search engine
“Which new medical studies
about allergy ABC talk also
about symptoms related to my
current patient?”
eyes allergy symptoms Go!
ocular allergy symptom
itchy eyes
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A simple semantic search engine
“Which new medical studies
about allergy ABC talk also
about symptoms related to my
current patient?”
eyes allergy symptoms Go!
ocular allergy symptom
itchy eyes
There are various
semantic technologies
to produce this additional
contextualization.
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‘Search’ by extending graphs ‘on-the-fly’
owns
fits
with
fits with“Which skateboard fits with my
jacket and its manufacturer also
produces snowboards?”
produces
produces
Snowboardis a
Skateboardis a
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‘Semantic Re-Engineering’
based on Text Mining
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Semantic Authoring
“Organizations should
focus on semantic
consistency and
performance in
upstream applications
and data stores
instead of information
consolidation in a
data lake.” Gartner
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The Semantic Web and Schema.org
What does it mean for Enterprises?
● 30% of all HTML pages contain structured data
(Source: https://commoncrawl.org/, 2014)
● 5 million web sites provide Schema.org data (Source: Google, 2014)
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Source:TFF2015,ChristianBizer,Uni
Mannheim
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Search, analytics and new insights
The IKEA principle
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More:http://www.confluentforms.com/2015/05/semantic-search-strategy.html
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Semantic Web and Linked Data
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+ + =
Structured and
Unstructured Data
Taxonomies Linked (Open) Data
Semantic Search &
Analytics
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● ‘Interpretation’ of information demand
by any means whatsoever
(see: ‘semantic re-engineering’)
● Single information source
● No explicit metadata, no standards
● Application: Query expansion, Search refiners
● Example: www.reegle.info/clean-energy-search
1-star Semantic Search
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● ‘Interpretation’ of information demand
based on a multi-lingual, controlled vocabulary
including multi-faceted hierarchies
● Single information source
● Explicit metadata layer
● Application: Faceted search
● Example: www.eip-water.eu/my-market-place/news
2-star Semantic Search
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● ‘Interpretation’ of information demand based on
multi-lingual, controlled vocabularies including
multi-faceted hierarchies
● Multiple information sources incl. user profiles
● Explicit and harmonised metadata layer, SKOS
● Typical application: Integrated search /
personalisation
● Example: www.healthdirect.gov.au
3-star Semantic Search
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● ‘Interpretation’ of information demand based on
multi-lingual, interlinked KOS
● Multiple information sources transformed and
stored in a Linked Data RDF Warehouse
● Explicit and harmonised metadata layer accessible
via SPARQL endpoint
● Typical application: Business Analytics
● Example: integrator.poolparty.biz/report_medicine
4-star Semantic Search
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● ‘Interpretation’ of information demand
based on multi-lingual, interlinked KOS
● Multiple information sources
transformed to RDF in real-time
● Explicit & harmonised metadata layer
accessible via federated SPARQL endpoint
5-star Semantic Search
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Bootstrapping a Virtual
Semantic Data Warehouse
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A Five-Star Rating System for
Semantic Search
Precise interpretation of information demand
Multilingual, multi-faceted search
Multiple sources
SPARQL-enabled
Federated
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The Rating System
from a UX perspective
Higher recall
Higher precision
Less browsing, personalisation
New insights
Real-time
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SPARQL is the new King of all
Data Scientist’s tools
Read more on LinkedIn Pulse
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Example: Disease Prevalence Analysis
The semantic approach for
tracking scientific
publications
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Connect
Andreas Blumauer, MScIT
CEO, Semantic Web Company
a.blumauer@semantic-web.at
http://at.linkedin.com/in/andreasblumauer
https://twitter.com/semwebcompany
https://ablvienna.wordpress.com/
Sorry, no Facebook!
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