Sebastian Gabler Consultant, Semantic Web Company Dr Ian Piper UK Director PoolParty Semantic Suite Information Energy 2017 May 18th 2017 From Strings to Things - and from Lists to Taxonomies 1
Welcome message from author
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
Sebastian GablerConsultant, Semantic Web
Company
Dr Ian PiperUK Director
PoolParty Semantic Suite
Information Energy 2017May 18th 2017
From Strings to Things - and from Lists to Taxonomies
1
Introduction
2Semantic Web
Company
Consultant
Sebastian Gabler
developer and vendor
2004
founded
5.7
current Version
follows
based on
Vienna
located
part ofTaxonomies Knowledge
Graphs
managed with
standard forpart of
is a
>200serves customers
follows
knows
Dr Ian M Piper
AGENDAPART 1 (Sebastian Gabler)● Implicit and explicit semantics● Knowledge Acquisition Models● PoolParty Taxonomy management
PART 2 (Ian Piper)● Using the Enterprise Knowledge Graph● Integrating Knowledge Graphs into Content Management
Systems(Remark: the last 3 points are not covered in this slide deck as they were performed as live demonstrations.)
3
Four-layered Content Architecture
4
USING THE SEMANTIC LAYER ALONG THE CONTENT LIFE CYCLE
5
Types of Knowledge models
Implicit and explicit Semantics
6
Content is King?
▸ Natural languages
▸ Ambiguity versus Universality▸ Context information and background knowledge needed
7
Susan observes Mike on a tower with a telescope.
Context is King!
▸ Natural languages
▸ Ambiguity versus Universality▸ Context information and background knowledge needed
8- Susan and Mike are persons.- Yesterday, Michael bought a Celestron.- If one buys something, (s)he owns it and
can use it.- Mike and Michael are the same person.- A Celestron is a type of telescope
Susan observes Mike on a tower with a telescope.
Natural knowledge acquisition
9 Bla bla bla bla. Bla bla bla bla
The stove is on. The stove is hot!
Ontological model → reasoningTaxonomical model → is-a abstractions
Bla stove bla bla. Bla bla bla hot
Switched on devices are dangerous devices.
Switched on devices are dangerous, only if the operating temperature is above 100 degrees and the automatic shutdown mechanism is broken.
The stove is on. The stove is hot!
Statistical model/co-occurrences → is related
The stove is on. The stove is hot!
Bla bla bla bla Bla bla bla bla.
Semiotic Triangle
The level of efficiency of an Interpretant depends mainly on its ability to correctly link a symbol with the object it stands for.
10
TelescopeSymbol
Object
Interpretant
Semiotic Triangle
The level of efficiency of an Interpretant depends mainly on its ability to correctly link a symbol with the object it stands for.
11
TelescopeSymbol
Object
Interpretant
http://dbpedia.org/resource/Telescope
List of Strings
12
Taxonomies
13
skos:Concept
Anthony van
Hoboken
skos:prefLabel
skos:Concept
skos:related
Joseph Haydn
skos:prefLabel
Papa Haydnskos:altLabel
skos:Concept
Michael Haydn
skos:prefLabel
skos:related skos:ConceptScheme
skos:inScheme
skos:inScheme
Person
skos:prefLabel
skos:Concept
Symphony No. 23
skos:prefLabel
skos:Concept
skos:broader
Hoboken Catalogue
skos:prefLabelskos:related
http://localhost/Music/1823
rdf:about
SKOS business value
• A simple, well-defined, easy to understand format for taxonomies
• An extensible model for flexible taxonomy building
• A fundamental building block for semantic content classification
14
Cost trade-off
15
Thesauruses provide an "interpretive layer of semantics" between what we are looking for and the information stored in databases, file systems, the web or any other place where we try to store and retrieve information. (ANSI/NISO, 2005, S.11)
SKOS
Progressive Knowledge Aggregation
16Bain Capital is a venture capital company based in Boston, MA.Since inception it has invested in hundreds of companies including AMC Entertainment, Brookstone, and Burger King. The company was co-founded by Mitt Romney.
Taxonomy & Ontology Server
Entity Extractor & Text Mining
Data Integration & Data Linking
UnstructuredData
Semi-structured
Data
StructuredData
UnifiedViews
PoolParty GraphSearch
identify newcandidate terms
controlled vocabulary: High-precision extraction base
entity extractor informs all incoming data streams about its Semantics, linking them
Meet the PoolParty Team at some major events in 2017
17 June 12-14, LondonMarkLogic World 2017 EMEA> More information
Sep 11-14, Amsterdam13th Int. Conference on Semantic Systems> More information
Nov 6-9, Washington D.C.KM World and Taxonomy Bootcamp> More information
Oct 17-18, LondonTaxonomy Bootcamp> More information
Oct 21-25, Vienna16th Int. Semantic Web Conference> More information
CONNECT
Dr Ian PiperUK PoolParty DirectorTellura Information Services Ltd.▸ [email protected]▸ https://www.linkedin.com/in/ianpiper ▸ https://twitter.com/tellura_tweets ▸ http://tellura.co.uk/
18
© Semantic Web Company - http://www.semantic-web.at/ and http://www.poolparty.biz/
Get in touch
Sebastian GablerConsultant, Semantic Web Company
▸ [email protected]▸ https://at.linkedin.com/in/SebastianGabler▸ https://poolparty.biz
19
© Semantic Web Company - http://www.semantic-web.at/ and http://www.poolparty.biz/
Related Documents
