Using Text Comprehension Model for Learning Concepts, Context, and Topic of...Kent State University
Concepts in web ontologies help machines to un-
derstand data through the meanings they hold. Furthermore,
learning contexts and topics of web documents also have helped
in better semantic-oriented structuring and retrieval of data on
the web. In this short paper we present a novel approach for
domain-independent open learning of domain concepts, context
and topic of any given web document. Our approach is based on a
computational version of the Construction-Integration (CI) model
of text comprehension. Our proposed system mimics the way
humans learn the meanings of textual units and identify domain
concepts, contexts and topics in the form of semantic networks.
We apply our system on a number of web documents with a
range of topics and domains. The resulting semantic networks
provide a quantitative and qualitative insights into the nature of
the given web documents.
Forms part of a training course in ontology given in Buffalo in 2009. For details and accompanying video see http://ontology.buffalo.edu/smith/IntroOntology_Course.html
Using Text Comprehension Model for Learning Concepts, Context, and Topic of...Kent State University
Concepts in web ontologies help machines to un-
derstand data through the meanings they hold. Furthermore,
learning contexts and topics of web documents also have helped
in better semantic-oriented structuring and retrieval of data on
the web. In this short paper we present a novel approach for
domain-independent open learning of domain concepts, context
and topic of any given web document. Our approach is based on a
computational version of the Construction-Integration (CI) model
of text comprehension. Our proposed system mimics the way
humans learn the meanings of textual units and identify domain
concepts, contexts and topics in the form of semantic networks.
We apply our system on a number of web documents with a
range of topics and domains. The resulting semantic networks
provide a quantitative and qualitative insights into the nature of
the given web documents.
Forms part of a training course in ontology given in Buffalo in 2009. For details and accompanying video see http://ontology.buffalo.edu/smith/IntroOntology_Course.html
Application of Ontology in Semantic Information Retrieval by Prof Shahrul Azm...Khirulnizam Abd Rahman
Application of Ontology in Semantic Information Retrieval
by Prof Shahrul Azman from FSTM, UKM
Presentation for MyREN Seminar 2014
Berjaya Hotel, Kuala Lumpur
27 November 2014
A lecture/conversation focusing on the first 12 years of Semantic Web - delivered on February 21, 2012.
See http://j.mp/SWIntro for more details. More detailed course material is at http://knoesis.org/courses/web3/
Data integration is a perennial challenge facing large-scale data scientists. Bio-ontologies are useful in this endeavour as sources of synonyms and also for rules-based fuzzy integration pipelines.
Semantic Web in Action: Ontology-driven information search, integration and a...Amit Sheth
Amit Sheth's Keynote talk given at: “Semantic Web in Action: Ontology-driven information search, integration and analysis,” Net Object Days 2003 and MATES03, Erfurt, Germany, September 23, 2003. http://knoesis.org
Note: slides 51-55 have audio.
The logic-based machine-understandable framework of the Semantic Web often challenges naive users when they try to query ontology-based knowledge bases. Existing research efforts have approached this problem by introducing Natural Language (NL) interfaces to ontologies. These NL interfaces have the ability to construct SPARQL queries based on NL user queries. However, most efforts were restricted to queries expressed in English, and they often benefited from the advancement of English NLP tools. However, little research has been done to support querying the Arabic content on the Semantic Web by using NL queries. This paper presents a domain-independent approach to translate Arabic NL queries to SPARQL by leveraging linguistic analysis. Based on a special consideration on Noun Phrases (NPs), our approach uses a language parser to extract NPs and the relations from Arabic parse trees and match them to the underlying ontology. It then utilizes knowledge in the ontology to group NPs into triple-based representations. A SPARQL query is finally generated by extracting targets and modifiers, and interpreting them into SPARQL. The interpretation of advanced semantic features including negation, conjunctive and disjunctive modifiers is also supported. The approach was evaluated by using two datasets consisting of OWL test data and queries, and the obtained results have confirmed its feasibility to translate Arabic NL queries to SPARQL.
study or concern about what kinds of things exist
what entities there are in the universe.
the ontology derives from the Greek onto (being) and logia (written or spoken). It is a branch of metaphysics , the study of first principles or the root of things.
Ontology languages are used in modelling the semantics of concepts within a particular domain and the relationships between those concepts. The Semantic Web standard provides a number of modelling languages that differ in their level of expressivity and are organized in a Semantic Web Stack in such a way that each language level builds on the expressivity of the other. There are several problems when one attempts to use independently developed ontologies. When existing ontologies are adapted for new purposes it requires that certain operations are performed on them. These operations are currently performed in a semi-automated manner. This paper seeks to model categorically the syntax and semantics of RDF ontology as a step towards the formalization of ontological operations using category theory.
Information residing in relational databases and delimited file systems are inadequate for reuse and sharing over the web. These file systems do not adhere to commonly set principles for maintaining data harmony. Due to these reasons, the resources have been suffering from lack of uniformity, heterogeneity as well as redundancy throughout the web. Ontologies have been widely used for solving such type of problems, as they help in extracting knowledge out of any information system. In this article, we focus on extracting concepts and their relations from a set of CSV files. These files are served as individual concepts and grouped into a particular domain, called the domain ontology. Furthermore, this domain ontology is used for capturing CSV data and represented in RDF format retaining links among files or concepts. Datatype and object properties are automatically detected from header fields. This reduces the task of user involvement in generating mapping files. The detail analysis has been performed on Baseball tabular data and the result shows a rich set of semantic information.
Translating Ontologies in Real-World SettingsMauro Dragoni
To enable knowledge access across languages, ontologies that are often represented only in English, need to be translated into different languages. The main challenge in translating ontologies is to find the right term with respect to the domain modeled by ontology itself. Machine translation services may help in this task; however, a crucial requirement is to have translations validated by experts before the ontologies are deployed. Real-world applications must implement a support system addressing this task for relieve experts work in validating all translations. In this paper, we present ESSOT, an Expert Supporting System for Ontology Translation. The peculiarity of this system is to exploit semantic information of the concept's context for improving the quality of label translations. The system has been tested both within the Organic.Lingua project by translating the modeled ontology in three languages and on other multilingual ontologies in order to evaluate the effectiveness of the system in other contexts. The results have been compared with the translations provided by the Microsoft Translator API and the improvements demonstrated the viability of the proposed approach.
semantic data integration the process of using a conceptual representation of the data and of their relationships to eliminate possible heterogeneities.
Concept hierarchy is the backbone of ontology, and the concept hierarchy acquisition has been a hot topic in the field of ontology learning. this paper proposes a hyponymy extraction method of domain ontology concept based on cascaded conditional random field(CCRFs) and hierarchy clustering. It takes free text as extracting object, adopts CCRFs identifying the domain concepts. First the low layer of CCRFs is used to identify simple domain concept, then the results are sent to the high layer, in which the nesting concepts are recognized. Next we adopt hierarchy clustering to identify the hyponymy relation between domain ontology concepts. The experimental results demonstrate the proposed method is efficient.
Federated data stores using semantic web technologySteve Ray
Semantic web, or linked data technology can help address interoperability problems in the internet, and particularly in support of the Internet of Things. This is an simple introduction to this technology.
UNIT III MINING COMMUNITIES
Aggregating and reasoning with social network data, Advanced Representations - Extracting
evolution of Web Community from a Series of Web Archive - Detecting Communities in Social
Networks - Evaluating Communities – Core Methods for Community Detection & Mining Applications of Community Mining Algorithms - Node Classification in Social Networks.
An updated "what is happening on the Semantic Web" presentation for 2010 - includes business use, government use, and some speculation on the current areas of excitement and development. A very accessible talk, not aimed solely at a technical audience.
Application of Ontology in Semantic Information Retrieval by Prof Shahrul Azm...Khirulnizam Abd Rahman
Application of Ontology in Semantic Information Retrieval
by Prof Shahrul Azman from FSTM, UKM
Presentation for MyREN Seminar 2014
Berjaya Hotel, Kuala Lumpur
27 November 2014
A lecture/conversation focusing on the first 12 years of Semantic Web - delivered on February 21, 2012.
See http://j.mp/SWIntro for more details. More detailed course material is at http://knoesis.org/courses/web3/
Data integration is a perennial challenge facing large-scale data scientists. Bio-ontologies are useful in this endeavour as sources of synonyms and also for rules-based fuzzy integration pipelines.
Semantic Web in Action: Ontology-driven information search, integration and a...Amit Sheth
Amit Sheth's Keynote talk given at: “Semantic Web in Action: Ontology-driven information search, integration and analysis,” Net Object Days 2003 and MATES03, Erfurt, Germany, September 23, 2003. http://knoesis.org
Note: slides 51-55 have audio.
The logic-based machine-understandable framework of the Semantic Web often challenges naive users when they try to query ontology-based knowledge bases. Existing research efforts have approached this problem by introducing Natural Language (NL) interfaces to ontologies. These NL interfaces have the ability to construct SPARQL queries based on NL user queries. However, most efforts were restricted to queries expressed in English, and they often benefited from the advancement of English NLP tools. However, little research has been done to support querying the Arabic content on the Semantic Web by using NL queries. This paper presents a domain-independent approach to translate Arabic NL queries to SPARQL by leveraging linguistic analysis. Based on a special consideration on Noun Phrases (NPs), our approach uses a language parser to extract NPs and the relations from Arabic parse trees and match them to the underlying ontology. It then utilizes knowledge in the ontology to group NPs into triple-based representations. A SPARQL query is finally generated by extracting targets and modifiers, and interpreting them into SPARQL. The interpretation of advanced semantic features including negation, conjunctive and disjunctive modifiers is also supported. The approach was evaluated by using two datasets consisting of OWL test data and queries, and the obtained results have confirmed its feasibility to translate Arabic NL queries to SPARQL.
study or concern about what kinds of things exist
what entities there are in the universe.
the ontology derives from the Greek onto (being) and logia (written or spoken). It is a branch of metaphysics , the study of first principles or the root of things.
Ontology languages are used in modelling the semantics of concepts within a particular domain and the relationships between those concepts. The Semantic Web standard provides a number of modelling languages that differ in their level of expressivity and are organized in a Semantic Web Stack in such a way that each language level builds on the expressivity of the other. There are several problems when one attempts to use independently developed ontologies. When existing ontologies are adapted for new purposes it requires that certain operations are performed on them. These operations are currently performed in a semi-automated manner. This paper seeks to model categorically the syntax and semantics of RDF ontology as a step towards the formalization of ontological operations using category theory.
Information residing in relational databases and delimited file systems are inadequate for reuse and sharing over the web. These file systems do not adhere to commonly set principles for maintaining data harmony. Due to these reasons, the resources have been suffering from lack of uniformity, heterogeneity as well as redundancy throughout the web. Ontologies have been widely used for solving such type of problems, as they help in extracting knowledge out of any information system. In this article, we focus on extracting concepts and their relations from a set of CSV files. These files are served as individual concepts and grouped into a particular domain, called the domain ontology. Furthermore, this domain ontology is used for capturing CSV data and represented in RDF format retaining links among files or concepts. Datatype and object properties are automatically detected from header fields. This reduces the task of user involvement in generating mapping files. The detail analysis has been performed on Baseball tabular data and the result shows a rich set of semantic information.
Translating Ontologies in Real-World SettingsMauro Dragoni
To enable knowledge access across languages, ontologies that are often represented only in English, need to be translated into different languages. The main challenge in translating ontologies is to find the right term with respect to the domain modeled by ontology itself. Machine translation services may help in this task; however, a crucial requirement is to have translations validated by experts before the ontologies are deployed. Real-world applications must implement a support system addressing this task for relieve experts work in validating all translations. In this paper, we present ESSOT, an Expert Supporting System for Ontology Translation. The peculiarity of this system is to exploit semantic information of the concept's context for improving the quality of label translations. The system has been tested both within the Organic.Lingua project by translating the modeled ontology in three languages and on other multilingual ontologies in order to evaluate the effectiveness of the system in other contexts. The results have been compared with the translations provided by the Microsoft Translator API and the improvements demonstrated the viability of the proposed approach.
semantic data integration the process of using a conceptual representation of the data and of their relationships to eliminate possible heterogeneities.
Concept hierarchy is the backbone of ontology, and the concept hierarchy acquisition has been a hot topic in the field of ontology learning. this paper proposes a hyponymy extraction method of domain ontology concept based on cascaded conditional random field(CCRFs) and hierarchy clustering. It takes free text as extracting object, adopts CCRFs identifying the domain concepts. First the low layer of CCRFs is used to identify simple domain concept, then the results are sent to the high layer, in which the nesting concepts are recognized. Next we adopt hierarchy clustering to identify the hyponymy relation between domain ontology concepts. The experimental results demonstrate the proposed method is efficient.
Federated data stores using semantic web technologySteve Ray
Semantic web, or linked data technology can help address interoperability problems in the internet, and particularly in support of the Internet of Things. This is an simple introduction to this technology.
UNIT III MINING COMMUNITIES
Aggregating and reasoning with social network data, Advanced Representations - Extracting
evolution of Web Community from a Series of Web Archive - Detecting Communities in Social
Networks - Evaluating Communities – Core Methods for Community Detection & Mining Applications of Community Mining Algorithms - Node Classification in Social Networks.
An updated "what is happening on the Semantic Web" presentation for 2010 - includes business use, government use, and some speculation on the current areas of excitement and development. A very accessible talk, not aimed solely at a technical audience.
Practical Semantic Web and Why You Should Care - DrupalCon DC 2009Boris Mann
Presented at Drupalcon DC 2009 - http://dc2009.drupalcon.org/session/practical-semantic-web-and-why-you-should-care
An overview of Semantic Web concepts and RDF. Exploration of RDFa. How open data fits. Examples of modules and functionality in Drupal today, and a plan for Drupal 7.
The Semantic Web (and what it can deliver for your business)Knud Möller
3-hour talk I gave on behalf of Social Bits and the Irish Internet Association (IIA). Contains an introduction to the general idea of the Semantic Web and Linked Data, its relevance and opportunities for businesses, and a look under the hood - how does it all work?
We present Fresnel Forms, a plugin we developed for Protégé, an editor for Semantic Web ontologies. The Fresnel Forms plugin processes the currently active ontology in a Protégé session to export a semantic wiki for that ontology. This export uses Semantic MediaWiki’s XML-based export format for import into an existing wiki. Fresnel Forms also provides a GUI editor to let the user fine-tune the generated interface before exporting it to a wiki.
Fresnel Forms exports use features from Semantic MediaWiki and Semantic Forms to provide an annotate-and-browse data system interface. Each wiki Fresnel Forms generates provides forms for entering data for classes and fields that conform to the original ontology. Templates provide displays of pages created with these forms. Finally, the wiki’s ExportRDF feature creates Semantic Web triples for the data entered that use URI’s from the original ontology. Fresnel Forms provides thus an efficient way to create a wiki for populating a given Semantic Web ontology.
Fresnel Forms can be downloaded and installed on Protégé from http://is.cs.ou.nl/OWF/index.php5/Fresnel_Forms
A presentation on mashing up Twitter Annotations with the Semantic Web. June 24, 2010 at the Semantic Technology Conference, San Francisco (SemTech 2010).
Very basic introductory talk about the Semantic Web, given to undergraduate and posgraduate students of Universidad del Valle (Cali, Colombia) in September 2010
The GoodRelations Ontology: Making Semantic Web-based E-Commerce a RealityMartin Hepp
A promising application domain for Semantic Web technology is the annotation of products and services offerings on the Web so that consumers and enterprises can search for suitable suppliers using products and services ontologies. While there has been substantial progress in developing ontologies for types of products and services, namely eClassOWL, this alone does not provide the representational means required for e-commerce on the Semantic Web. Particularly missing is an ontology that allows describing the relationships between (1) Web resources, (2) offerings made by means of those Web resources, (3) legal entities, (4) prices, (5) terms and conditions, and (6) the aforementioned ontologies for products and services. (1NDN)
In the talk, I will explain the need and potential of the GoodRelations ontology, introduce its key conceptual elements, highlight several lessons learned, and summarize design decisions with respect to to modeling approaches and the appropriate language fragment, which may be relevant for other ontology projects, too.
This talk introduces the concepts of web 3.0 technology and how they relate to related technologies such as Internet of Things (IoT), Grid Computing and the Semantic Web:
• A short history of web technologies:
o Web 1.0: Publishing static information with links for human consumption.
o Web 2.0: Publishing dynamic information created by users, for human consumption.
o Web 3.0: Publishing all kinds of information with links between data items, for machine consumption.
• Standardization of protocols for description of any type of data (RDF, N3, Turtle).
• Standardization of protocols for the consumption of data in “the grid” (SPARQL).
• Standardization of protocols for rules (RIF).
• Comparison with the evolution of technologies related to data bases.
• Comparison of IoT solutions based on web 2.0 and web 3.0 technologies.
• Distributed solutions vs centralized solutions..
• Security
• Extensions of Peer-to-peer protocols (XMPP).
• Advantages of solutions based on web 3.0 and standards (IETF, XSF).
Duration of talk: 1-2 hours with questions.
Although animals do not use language, they are capable of many of the same kinds of cognition as us; much of our experience is at a non-verbal level.
Semantics is the bridge between surface forms used in language and what we do and experience.
Language understanding depends on world knowledge (i.e. “the pig is in the pen” vs. “the ink is in the pen”)
We might not be ready for executives to specify policies themselves, but we can make the process from specification to behavior more automated, linked to precise vocabulary, and more traceable.
Advances such as SVBR and an English serialization for ISO Common Logic means that executives and line workers can understand why the system does certain things, or verify that policies and regulations are implemented
These slides were presented as part of a W3C tutorial at the CSHALS 2010 conference (http://www.iscb.org/cshals2010). The slides are adapted from a longer introduction to the Semantic Web available at http://www.slideshare.net/LeeFeigenbaum/semantic-web-landscape-2009 .
A PDF version of the slides is available at http://thefigtrees.net/lee/sw/cshals/cshals-w3c-semantic-web-tutorial.pdf .
Structured Dynamics provides 'ontology-driven applications'. Our product stack is geared to enable the semantic enterprise. The products are premised on preserving and leveraging existing information assets in an incremental, low-risk way. SD's products span from converters to authoring environments to Web services middleware and to eventual ontologies and user interfaces and applications.
Dare to build vertical design with relational data (Entity-Attribute-Value)Ivo Andreev
Entity-Attribute-Value model is often called “anti-pattern” by the criticism. And probably they would be right if one misses to read the “Handle with Care” label on it. Enthusiastic inexperienced developers would easily compromise the benefits of relational DB but the coin has yet another side. Hierarchical object with thousands of properties, unknown schema, flexibility and millions of records. As always – we have to sacrifice one thing in order to win another. Then all it comes to priorities and ability for decision making. At this lecture you will not get a step-by-step manual but instead get ideas for how to build one for you. A challenge, a proof of concept, hard work and successful project for millions – that is the story to share.
JSP 프로그래밍 #02 서블릿과 JSP 시작하기
2.1 톰캣 애플리케이션 만들기 (온라인 강의: https://youtu.be/04LIGWKCFjY)
2.2 간단한 서블릿 만들기 (온라인 강의: https://youtu.be/4ajw5EsxYE8)
2.3 간단한 JSP 만들기 (온라인 강의: https://youtu.be/6h-qH8pGdT8)
2.4 간단한 자바빈즈 만들기 (온라인 강의: https://youtu.be/TlgXkAWi1sc)
JSP 프로그래밍 #01 웹 프로그래밍
1.1 웹 (온라인 강의: https://youtu.be/qDZXXHhMr4A)
1.2 서블릿 (온라인 강의: https://youtu.be/a8hHeUhbz2k)
1.3 JSP(Java Server Page) (온라인 강의: https://youtu.be/Q4ezLP6KLwM)
1.4 프로그래밍을 위한 환경 설정 (온라인 강의: https://youtu.be/k2eR6gLULA8)
2018년 7월 5일에 있었던 한국인터넷거버넌스포럼(KrIGF)에서 발표한 "오픈 데이터와 인공지능" 발표자료입니다.
다음과 같은 내용을 담고 있습니다.
* 오픈데이터의 정의
* 오픈데이터의 중요성
* 인공지능
* 인공지능에서 데이터의 중요성
* 제한된 데이터 환경에서의 문제점
* 인공지능을 위한 오픈데이터의 중요성
* 더 나은 인공지능 시대를 위한 제언
2017년 4월에 진행된 도서관최신동향 과정에 있었던 발표자료입니다.
서지 분야에서의 Linked Data의 개념과 활용에 대한 내용을 담고 있습니다.
구체적으로는 아래와 같은 내용을 포함합니다.
- Linked Data란 무엇인가?
- 왜 도서관에서 Linked Data를 이야기하는가?
- Linked Data를 누가 쓰고 있나?
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
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...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
3. The Semantic Web The Semantic Web is not a separate Web but an extension of the current one, in which information is given well defined meaning, better enabling computers and people to work in cooperation. By Tim Berners-Lee The Semantic Web is a group of methods and technologies to allow machines to understand the meaning - or "semantics" - of information on the World Wide Web. From Wikipedia 3
4. Semantic Web Stack The Semantic Web Stack, also known as Semantic Web Cake or Semantic Web Layer Cake, illustrates the architecture of the Semantic Web. Semantic Web - XML2000 (2000) 4
5. Semantic Web Stack Representing Knowledge in the Semantic Web(2005) Rule Interchange Format (RIF) Highlight (2007) 5
11. Web Ontology Language The Web Ontology Language (OWL) is a family of knowledge representation languages for authoring ontologies. From Wikipedia An ontology is an explicit specification of a conceptualization. By Tom Gruber 11 OWL 2 OWL 1
18. Limited existential quantification Complex concept negation Role hierarchy (subproperties - rdfs:subPropertyOf) Nominals. (Enumerated classes of object value restrictions - owl:oneOf, owl:hasValue). Inverse properties Functional properties Cardinality restrictions (owl:Cardinality, owl:MaxCardinality) Use of datatype properties, data values or data types Limited complex role inclusion axioms; reflexivity and irreflexivity; role disjointness Qualified cardinality restrictions 15 OWL DL OWL Lite OWL 2