The document discusses semantic web technology, which aims to make information on the web better understood by machines by giving data well-defined meaning. It outlines the evolution of web technologies from the initial web to the semantic web. Key aspects of semantic web technology include ontologies to define common vocabularies, semantic annotations to associate meaning with data, and reasoning capabilities to enable complex queries and analyses. Languages, tools, and applications are needed to implement these semantic web standards and make the web of linked data usable.
The Semantic Web is an evolving development of the World Wide Web in which the word semantic stands for the meaning of. The semantic of something is the meaning of something. The Semantic Web or Web 2.0 or Web3.0 is a “Web of data” that enables machines to understand the semantics or meaning. Of information on the World Wide Web. It extends the network of hyperlinked human-readable web pages by inserting machine-readable metadata about pages and how they are related to each other. Enabling automated agents to access the Web more intelligently and perform tasks on behalf of users. The term was coined by Tim Beemers-Lee, the inventor of the World Wide Web and director of the World Wide Web Consortium. Which oversees the development of the proposal Semantic Web standards? He defines the Semantic Web as “a web of data that can be processed directly and
indirectly by machines.”
The Semantic Web is an evolving development of the World Wide Web in which the word semantic stands for the meaning of. The semantic of something is the meaning of something. The Semantic Web or Web 2.0 or Web3.0 is a “Web of data” that enables machines to understand the semantics or meaning. Of information on the World Wide Web. It extends the network of hyperlinked human-readable web pages by inserting machine-readable metadata about pages and how they are related to each other. Enabling automated agents to access the Web more intelligently and perform tasks on behalf of users. The term was coined by Tim Beemers-Lee, the inventor of the World Wide Web and director of the World Wide Web Consortium. Which oversees the development of the proposal Semantic Web standards? He defines the Semantic Web as “a web of data that can be processed directly and
indirectly by machines.”
This is a lecture note #1 for my class of Graduate School of Yonsei University, Korea.
It describes overview of the Semantic Web, its recommendations, and case studies.
NLP is the branch of computer science focused on developing systems that allow computers to communicate with people using everyday language. Also called Computational Linguistics – Also concerns how computational methods can aid the understanding of human language
Machine Learning. What is machine learning. Normal computer vs ML. Types of Machine Learning. Some ML Object detection methods. Faster CNN, RCNN, YOLO, SSD. Real Life ML Applications. Best Programming Languages for ML. Difference Between Machine Learning And Artificial Intelligence. Advantages of Machine Learning. Disadvantages of Machine Learning
This presentation walks through essential points for developing and working with REST APIs or web services to communicate through various platforms. This also explains HTTP methods.
ith the spread of online banking, increasing competition has elevated the need for providing excellent customer service in the Banking and Insurance sector. Digital also offers insurers new ways to cut costs and an opportunity to bring real additional value to the customer experience.
Semantic web technologies and applications provide the
emantic web technologies and applications for InsTemesgenHabtamu
ith the spread of online banking, increasing competition has elevated the need for providing excellent customer service in the Banking and Insurance sector. Digital also offers insurers new ways to cut costs and an opportunity to bring real additional value to the customer experience.
Semantic web technologies and applications provide the emantic web technologies and applications for Insemantic web technologies and applications for Ins
This is a lecture note #1 for my class of Graduate School of Yonsei University, Korea.
It describes overview of the Semantic Web, its recommendations, and case studies.
NLP is the branch of computer science focused on developing systems that allow computers to communicate with people using everyday language. Also called Computational Linguistics – Also concerns how computational methods can aid the understanding of human language
Machine Learning. What is machine learning. Normal computer vs ML. Types of Machine Learning. Some ML Object detection methods. Faster CNN, RCNN, YOLO, SSD. Real Life ML Applications. Best Programming Languages for ML. Difference Between Machine Learning And Artificial Intelligence. Advantages of Machine Learning. Disadvantages of Machine Learning
This presentation walks through essential points for developing and working with REST APIs or web services to communicate through various platforms. This also explains HTTP methods.
ith the spread of online banking, increasing competition has elevated the need for providing excellent customer service in the Banking and Insurance sector. Digital also offers insurers new ways to cut costs and an opportunity to bring real additional value to the customer experience.
Semantic web technologies and applications provide the
emantic web technologies and applications for InsTemesgenHabtamu
ith the spread of online banking, increasing competition has elevated the need for providing excellent customer service in the Banking and Insurance sector. Digital also offers insurers new ways to cut costs and an opportunity to bring real additional value to the customer experience.
Semantic web technologies and applications provide the emantic web technologies and applications for Insemantic web technologies and applications for Ins
Semantic Web: Technolgies and Applications for Real-WorldAmit Sheth
Amit Sheth and Susie Stephens, "Semantic Web: Technolgies and Applications for Real-World," Tutorial at 2007 World Wide Web Conference, Banff, Canada.
Tutorial discusses technologies and deployed real-world applications through 2007.
Tutorial description at: http://www2007.org/tutorial-T11.php
“The Semantic Web is a vision: the idea of having data on the Web defined and linked in a way that it can be used by machines not just for display purposes, but for automation, integration and reuse of data across various applications”
X api chinese cop monthly meeting feb.2016Jessie Chuang
Topics
XAPI Vocabulary spec. From ADL
Linked Data / Semantic web. / Web 3.0
Linked Data in education and content recommender
Semantic search and Google Knowledge Graph
APIs eat software (connect with partners and services)
How should we exploit data and build intelligence layer?
Case Study (Hong Ding Educational Technology)
Monetize your data and add value (intelligence)
The Semantic Web is a vision of information that is understandable by computers. Although there is great exploitable potential, we are still in "Generation Zero'' of the Semantic Web, since there are few real-world compelling applications. The heterogeneity, the volume of data and the lack of standards are problems that could be addressed through some nature inspired methods. The paper presents the most important aspects of the Semantic Web, as well as its biggest issues; it then describes some methods inspired from nature - genetic algorithms, artificial neural networks, swarm intelligence, and the way these techniques can be used to deal with Semantic Web problems.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
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Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
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During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
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Charlie Greenberg, Host
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
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2. What is Semantic Web?
• The current Web activities are
mostly focus on Machine-to-
Human;
• Machine-to-Machine activities
are not particularly well
• supported by software tools.
“The Semantic Web is an extension of the current web in which
information is given well-defined meaning, better enabling
computers and people to
work in co-operation.“ [Berners-Lee, 2001]
3. Evolution of Web Technology
Web (since 1992)
• HTTP
• HTML/CSS/JavaScript
Semantic Web
•Reasoning
•Logic, Rules
•Trust
Social Web (since 2003)
• Folksonomies/Tagging
• Reputation, sharing
• Groups, relationships
Data Web (since 2006)
• URI de-reference
• CBD
• RDF serializations
4. From Web of Document to Web of Linked Data
Many Web sites
containing unstructured,
textual content
Few large Web sites
are specialized on
specific content types
Many Web sites containing
& semantically syndicating
arbitrarily structured
content
Pictures
Video
Encyclopedic
articles
+ +
Web 1.0 Web 2.0 Web 3.0
5. Semantic Web Stack
• Machine Processable,
Global Web Standards:
• Assigning Unambiguous
Names (URI)
• Expressing data, including
metadata (RDF, RDFS)
• Modelling Ontologies
(OWL)
• Query and Retrieve
(SPARQL)
6. Key Functions of Semantic Web Technology
• Ontology Modeling
Agreement with a common vocabulary, conceptual models and
domain Knowledge;
Schema + Knowledge base
Agreement is what enables interoperability
Formal description - Machine processability is what leads to
automation
• Semantic Annotation
Metadata Extraction: Associating meaning with data, or labeling
data so it is more meaningful to the system and people.
Can be manual, semi-automatic (automatic with human verification),
automatic
• Reasoning Computation
semantics enabled search, integration, answering complex queries,
connections and analyses (paths, sub graphs), pattern finding,
mining, hypothesis validation, discovery, visualization
7. 7
Semantic Technology Market Forecasting
Semantic solution, services & software markets will
grow rapidly, topping $60B by 2020
8. Semantic Web: Annotations
Semantic
Annotations
Ontologies Logical Support
Languages Tools Applications /
Services
Web content
UsersCreatorsWWW
and
Beyond
Semantic
Web
Semantic Web
content
Users
Semantic
Web and
Beyond
Creators
applications
agents
Semantic annotations are
specific sort of metadata,
which provides information
about particular domain
objects, values of their
properties and relationships, in
a machine-processable, formal
and standardized way.
9. Semantic Web: Ontologies
Semantic
Annotations
Ontologies Logical Support
Languages Tools Applications /
Services
Web content
UsersCreatorsWWW
and
Beyond
Semantic
Web
Semantic Web
content
Users
Semantic
Web and
Beyond
Creators
applications
agents
Ontologies make metadata
interoperable and ready for
efficient sharing and reuse. It
provides shared and common
understanding of a domain, that
can be used both by people and
machines. Ontologies are used as
a form of agreement-based
knowledge representation about
the world or some part of it and
generally describe: domain
individuals, classes, attributes,
relations and events.
10. Semantic Web: Rules
Semantic
Annotations
Ontologies Logical Support
Languages Tools Applications /
Services
Web content
UsersCreatorsWWW
and
Beyond
Semantic
Web
Semantic Web
content
Users
Semantic
Web and
Beyond
Creators
applications
agents
Logical support in form of rules is needed to infer
implicit content, metadata and ontologies from
the explicit ones. Rules are considered to be a
major issue in the further development of the
semantic web. On one hand, they can be used in
ontology languages, in conjunction with or as an
alternative to description logics. And on the other
hand, they will act as a means to draw
inferences, to configure systems, to express
constraints, to specify policies, to react to
events/changes, to transform data, to specify
behavior of agents, etc.
11. Semantic Web: Languages
Semantic
Annotations
Ontologies Logical Support
Languages Tools Applications /
Services
Web content
UsersCreatorsWWW
and
Beyond
Semantic
Web
Semantic Web
content
Users
Semantic
Web and
Beyond
Creators
applications
agents
Languages are needed for machine-processable
formal descriptions of: metadata (annotations) like e.g.
RDF; ontologies like e.g. OWL.; rules like e.g.
RuleML. The challenge is to provide a framework for
specifying the syntax (e.g. XML) and semantics of all
of these languages in a uniform and coherent way.
The strategy is to translate the various languages into
a common 'base' language (e.g. CL or Lbase)
providing them with a single coherent model theory.
12. Semantic Web: Tools
Semantic
Annotations
Ontologies Logical Support
Languages Tools Applications /
Services
Web content
UsersCreatorsWWW
and
Beyond
Semantic
Web
Semantic Web
content
Users
Semantic
Web and
Beyond
Creators
applications
agents
User-friendly tools are needed for
metadata manual creation (annotating
content) or automated generation, for
ontology engineering and validation, for
knowledge acquisition (rules), for
languages parsing and processing, etc.
13. Semantic Web: Applications and Services
Semantic
Annotations
Ontologies Logical Support
Languages Tools Applications /
Services
Web content
UsersCreatorsWWW
and
Beyond
Semantic
Web
Semantic Web
content
Users
Semantic
Web and
Beyond
Creators
applications
agents
Utilization of Semantic Web
metadata, ontologies, rules,
languages and tools enables to
provide scalable Web applications
and Web services for consumers and
enterprises" making the web 'smarter'
for people and machines.
14. The Idea of Web Linked Data
• Think of the semantic web as building on the ideas behind Linked Data;
• Linked Data is nor a specification, but a set of best practices for providing
a data infrastructure that makes it easier to share data across the web;
• Use semantic web technologies such as RDFS, OWL, and SPARQL to build
applications around that data;
Four Principles of Linked Data:
1. Use URIs as names for things;
2. Use HTTP URIs so that people can look up those names;
3. When looking up a URI, provide useful information with the standards
such as RDF, RFFS, OWL, SPARQL;
4. Include links to other URIs to discover more information;
15. Foundation for Future Enterprise Systems
• Semantic technology as a software technology allows the
meaning of information to be known and processed at
execution time. For a semantic technology there must be a
knowledge model of some part of the world that is used by
one or more applications at execution time.
Semantic Technologies represent meanings separately from
data, content, or program code, using the open standards
for the semantic web such as RDF and OWL W3C standards.
16. 16
Drivers for the Semantic Web Technology
• Business models develop rapidly these days, so
infrastructure that supports change is needed;
• Organizations are increasingly forming and disbanding
collaborations;
• Data is growing so quickly that it is no longer possible for
individuals to identify patterns in their heads;
• Increasing recognition of the benefits of collective
intelligence;
It is, essentially, the Web of Data.
“Semantic Web Technologies” is a collection of standard
technologies to realize a Web of Data
17. Semantics Web Technology in Nut Shell
• “Semantics” provides a universal framework to describe and
link different data so that it can be better understood and
searched holistically, allowing both people and computers to
see and discover relationships in the data;