Semantic Web used to be perceived as an academic discipline for a long time. The purpose of this presentation is to demonstrate the industrial potential that this technology has now as well as showcase use cases in Web Search, Recommender Systems, and Semantic Marketing
2. The Big Vision
Sir Tim Berners-Lee
The web of human-readable document is being
merged with a web of machine understandable data.
The potential of the mixture of humans and
machines working together and communication
through the web could be immense.
• The Web as a huge decentralised database
(knowledge base)
• Machine-accessible data
Web of Data as an upgrade of The Web of
Documents
3. A Web for Machines
Web of DataWeb of Documents
Data can be interconnected with typed links,
similarly as Web pages are connected with
hyperlinks
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10. The time passed by
t
NowThe Academic Age of the Semantic
Web
Ontol
ogies
Description
LogicRules
RDF
OWL
2001
Linked
Data
Social
Semantic
Web
Sema
ntic
Open
Data
Sema
ntic
Marku
p
Knowl
edge
Graph
s
11. SW Now: Semantic Open Data
Linked
Open Data
Publishers: Governments,
Name things using URIs
Provide data over HTTP
Publish data using open structured data
standards
Link to data published by others
12. SW Now: Semantic Open Data
DBPedia
Semantic version of Wikipedia with rich data
about over 3.5M concepts of human
knowledge.
Open Source.
The core of the Web of data.
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13. SW Now: Knowledge Graphs
Big players have their own
Knowledge GraphsGoogle Knowledge Graph
powers factual responses to
Web searches.
Wolfram Alpha, that powers
some of Siri searches, relies
on own curated data sources.
Facebook Open Graph combines concepts of
human knowledge and social data
14. SW Now: Semantic Markup
Provide metadata about things that
you want people to like. Facebook
integrates it in their Open Graph.
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Facebo
ok Like
HTML 5
microda
ta
Provide metadata about your Web
pages and Google will index them
better.
18. Semantic Recommender Systems
Seevl uses data graphs to calculate artist
similarity and recommend music. It helps
users discover unknown artists that they
may like, and does it better then standard
collaborative-filtering systems.
Whitney Houston
Mariah Carey
When You Believe
Vocals
Aretha Franklin
Finding interesting paths in the graph
instead of statistical co-occurrence
19. Answer: , because Mary is buying
vegetables for her vegetarian lunch
Semantic Marketing
?
Answer: because Mary’s basket contains
same elements as Bob’s
Collaborative Filtering (data-mining)
Mary
Bob
Semantic Marketing
User shopping
baskets
Semantic Marketing helps
develop better
understanding of users
preferences and motivations
20. Sépage puts to use the years of research and experience
with using Semantic Graphs to produce Semantic Marketing
solutions for the future of the Web, making it more smart
and more adapted to growing users expectations.
21. Licence
Attribution - Partage dans
les Mêmes Conditions 3.0
France
Images
Internet – Yellow from the Noun Project
Document, The Noun project
Video, Dmitry Baranovskiy, The Noun Project
User, Lynn D. Christensen, The Noun Project
Lemon, Claudio Gomboli, The Noun Project
Carrot, Kate Vogel, Then Noun Project
Cucumber, Ashwini Sukhdeve, The Noun Project
Tomato, Okan Benn, The Noun Project
Pumpkin, Adam Mullin, The Noun Project
Thank
you
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