1637269200
How to Solve The Area Of The Largest Rectangle in The Graph
Hey guys, In this video, We're going to solve another very famous Interview Problem called - The largest rectangular area in a Histogram
What is GEEK
Buddha Community
1656899776
Graph-scroll: Simple Scrolling Events for D3 Graphs
graph-scroll.js
Simple scrolling events for d3 graphs. Based on stack
Demo/Documentation
graph-scroll takes a selection of explanatory text sections and dispatches active events as different sections are scrolled into to view. These active events can be used to update a chart's state.
d3.graphScroll()
.sections(d3.selectAll('#sections > div'))
.on('active', function(i){ console.log(i + 'th section active') })
The top most element scrolled fully into view is classed graph-scroll-active. This makes it easy to highlight the active section with css:
#sections > div{
opacity: .3
}
#sections div.graph-scroll-active{
opacity: 1;
}
To support headers and intro images/text, we use a container element containing the explanatory text and graph.
<h1>Page Title</div>
<div id='container'>
<div id='graph'></div>
<div id='sections'>
<div>Section 0</div>
<div>Section 1</div>
<div>Section 2</div>
</div>
</div>
<h1>Footer</h1>
If these elements are passed to graphScroll as selections with container and graph, every element in the graph selection will be classed graph-scroll-graph if the top of the container is out of view.
d3.graphScroll()
.graph(d3.selectAll('#graph'))
.container(d3.select('#container'))
.sections(d3.selectAll('#sections > div'))
.on('active', function(i){ console.log(i + 'th section active') })
When the graph starts to scroll out of view, position: sticky keeps the graph element stuck to the top of the page while the text scrolls by.
#container{
position: relative;
}
#sections{
width: 340px;
}
#graph{
margin-left: 40px;
width: 500px;
position: sticky;
top: 0px;
float: right;
}
On mobile centering the graph and sections while adding a some padding for the first slide is a good option:
@media (max-width: 925px) {
#graph{
width: 100%;
margin-left: 0px;
float: none;
}
#sections{
position: relative;
margin: 0px auto;
padding-top: 400px;
}
}
Adjust the amount of pixels before a new section is triggered is also helpful on mobile (Defaults to 200 pixels):
graphScroll.offset(300)
To update or replace a graphScroll instance, pass a string to eventId to remove the old event listeners:
graphScroll.eventId('uniqueId1')Author: 1wheel
Source Code: https://github.com/1wheel/graph-scroll
License: MIT license
1621327800
Graphs and Knowledge Connexions. The Year of the Graph Newsletter, Autumn 2020
As 2020 is coming to an end, let’s see it off in style. Our journey in the world of Graph Analytics, Graph Databases, Knowledge Graphs and Graph AI culminate.
The representation of the relationships among data, information, knowledge and --ultimately-- wisdom, known as the data pyramid, has long been part of the language of information science. Digital transformation has made this relevant beyond the confines of information science. COVID-19 has brought years’ worth of digital transformation in just a few short months.
In this new knowledge-based digital world, encoding and making use of business and operational knowledge is the key to making progress and staying competitive. So how do we go from data to information, and from information to knowledge? This is the key question Knowledge Connexions aims to address.
Graphs in all shapes and forms are a key part of this.
Knowledge Connexions is a visionary event featuring a rich array of technological building blocks to support the transition to a knowledge-based economy: Connecting data, people and ideas, building a global knowledge ecosystem.
The Year of the Graph will be there, in the workshop “From databases to platforms: the evolution of Graph databases”. George Anadiotis, Alan Morrison, Steve Sarsfield, Juan Sequeda and Steven Xi bring many years of expertise in the domain, and will analyze Graph Databases from all possible angles.
This is the first step in the relaunch of the Year of the Graph Database Report. Year of the Graph Newsletter subscribers just got a 25% discount code. To be always in the know, subscribe to the newsletter, and follow the newly launched Year of the Graph account on Twitter! In addition to getting the famous YotG news stream every day, you will also get a 25% discount code.
#database #machine learning #artificial intelligence #data science #graph databases #graph algorithms #graph analytics #emerging technologies #knowledge graphs #semantic technologies
1595932020
Graph Therapy: The Year of the Graph Newsletter, June/May 2020
Parts of the world are still in lockdown, while others are returning to some semblance of normalcy. Either way, while the last few months have given some things pause, they have boosted others. It seems like developments in the world of Graphs are among those that have been boosted.
An abundance of educational material on all things graph has been prepared and delivered online, and is now freely accessible, with more on the way.
Graph databases have been making progress and announcements, repositioning themselves by a combination of releasing new features, securing additional funds, and entering strategic partnerships.
A key graph database technology, RDF*, which enables compatibility between RDF and property graph databases, is gaining momentum and tool support.
And more cutting edge research combining graph AI and knowledge graphs is seeing the light, too. Buckle up and enjoy some graph therapy.
Stanford’s series of online seminars featured some of the world’s leading experts on all things graph. If you missed it, or if you’d like to have an overview of what was said, you can find summaries for each lecture in this series of posts by Bob Kasenchak and Ahren Lehnert. Videos from the lectures are available here.
Stanford Knowledge Graph Course Not-Quite-Live-Blog
Stanford University’s computer science department is offering a free class on Knowledge Graphs available to the public. Stanford is also making recordings of the class available via the class website.
Another opportunity to get up to speed with educational material: The entire program of the course “Information Service Engineering” at KIT - Karlsruhe Institute of Technology, is delivered online and made freely available on YouTube. It includes topics such as ontology design, knowledge graph programming, basic graph theory, and more.
Information Service Engineering at KIT
Knowledge representation as a prerequisite for knowledge graphs. Learn about knowledge representation, ontologies, RDF(S), OWL, SPARQL, etc.
Ontology may sound like a formal term, while knowledge graph is a more approachable one. But the 2 are related, and so is ontology and AI. Without a consistent, thoughtful approach to developing, applying, evolving an ontology, AI systems lack underpinning that would allow them to be smart enough to make an impact.
The ontology is an investment that will continue to pay off, argue Seth Earley and Josh Bernoff in Harvard Business Review, making the case for how businesses may benefit from a knowldge-centric approach
Is Your Data Infrastructure Ready for AI?
Even after multiple generations of investments and billions of dollars of digital transformations, organizations struggle to use data to improve customer service, reduce costs, and speed the core processes that provide competitive advantage. AI was supposed to help with that.
Besides AI, knowledge graphs have a part to play in the Cloud, too. State is good, and lack of support for Stateful Cloud-native applications is a roadblock for many enterprise use-cases, writes Dave Duggal.
Graph knowledge bases are an old idea now being revisited to model complex, distributed domains. Combining high-level abstraction with Cloud-native design principles offers efficient “Context-as-a-Service” for hydrating stateless services. Graph knowledge-based systems can enable composition of Cloud-native services into event-driven dataflow processes.
Kubernetes also touches upon Organizational Knowledge, and that may be modeled as a Knowledge Graph.
Graph Knowledge Base for Stateful Cloud-Native Applications
Extending graph knowledge bases to model distributed systems creates a new kind of information system, one intentionally designed for today’s IT challenges.
The Enterprise Knowledge Graph Foundation was recently established to define best practices and mature the marketplace for EKG adoption, with a launch webinar on June the 23rd.
The Foundation defines its mission as including adopting semantic standards, developing best practices for accelerated EKG deployment, curating a repository of reusable models and resources, building a mechanism for engagement and shared knowledge, and advancing the business cases for EKG adoption.
Enterprise Knowledge Graph Maturity Model
The Enterprise Knowledge Graph Maturity Model (EKG/MM) is the industry-standard definition of the capabilities required for an enterprise knowledge graph. It establishes standard criteria for measuring progress and sets out the practical questions that all involved stakeholders ask to ensure trust, confidence and usage flexibility of data. Each capability area provides a business summary denoting its importance, a definition of the added value from semantic standards and scoring criteria based on five levels of defined maturity.
Enterprise Knowledge Graphs is what the Semantic Web Company (SWC) and Ontotext have been about for a long time, too. Two of the vendors in this space that have been around for the longer time just announced a strategic partnership: Ontotext, a graph database and platform provider, meets SWC, a management and added value layer that sits on top.
SWC and Ontotext CEOs emphasize how their portfolios are complementary, while the press release states that the companies have implemented a seamless integration of the PoolParty Semantic Suite™ v.8 with the GraphDB™ and Ontotext Platform, which offers benefits for many use cases.
#database #artificial intelligence #graph databases #rdf #graph analytics #knowledge graph #graph technology
1595924640
Graph Therapy: The Year of the Graph Newsletter, June/May 2020
Parts of the world are still in lockdown, while others are returning to some semblance of normalcy. Either way, while the last few months have given some things pause, they have boosted others. It seems like developments in the world of Graphs are among those that have been boosted.
An abundance of educational material on all things graph has been prepared and delivered online, and is now freely accessible, with more on the way.
Graph databases have been making progress and announcements, repositioning themselves by a combination of releasing new features, securing additional funds, and entering strategic partnerships.
A key graph database technology, RDF*, which enables compatibility between RDF and property graph databases, is gaining momentum and tool support.
And more cutting edge research combining graph AI and knowledge graphs is seeing the light, too. Buckle up and enjoy some graph therapy.
Stanford’s series of online seminars featured some of the world’s leading experts on all things graph. If you missed it, or if you’d like to have an overview of what was said, you can find summaries for each lecture in this series of posts by Bob Kasenchak and Ahren Lehnert. Videos from the lectures are available here.
Stanford Knowledge Graph Course Not-Quite-Live-Blog
Stanford University’s computer science department is offering a free class on Knowledge Graphs available to the public. Stanford is also making recordings of the class available via the class website.
Another opportunity to get up to speed with educational material: The entire program of the course “Information Service Engineering” at KIT - Karlsruhe Institute of Technology, is delivered online and made freely available on YouTube. It includes topics such as ontology design, knowledge graph programming, basic graph theory, and more.
Information Service Engineering at KIT
Knowledge representation as a prerequisite for knowledge graphs. Learn about knowledge representation, ontologies, RDF(S), OWL, SPARQL, etc.
Ontology may sound like a formal term, while knowledge graph is a more approachable one. But the 2 are related, and so is ontology and AI. Without a consistent, thoughtful approach to developing, applying, evolving an ontology, AI systems lack underpinning that would allow them to be smart enough to make an impact.
The ontology is an investment that will continue to pay off, argue Seth Earley and Josh Bernoff in Harvard Business Review, making the case for how businesses may benefit from a knowldge-centric approach
Is Your Data Infrastructure Ready for AI?
Even after multiple generations of investments and billions of dollars of digital transformations, organizations struggle to use data to improve customer service, reduce costs, and speed the core processes that provide competitive advantage. AI was supposed to help with that.
Besides AI, knowledge graphs have a part to play in the Cloud, too. State is good, and lack of support for Stateful Cloud-native applications is a roadblock for many enterprise use-cases, writes Dave Duggal.
Graph knowledge bases are an old idea now being revisited to model complex, distributed domains. Combining high-level abstraction with Cloud-native design principles offers efficient “Context-as-a-Service” for hydrating stateless services. Graph knowledge-based systems can enable composition of Cloud-native services into event-driven dataflow processes.
Kubernetes also touches upon Organizational Knowledge, and that may be modeled as a Knowledge Graph.
Graph Knowledge Base for Stateful Cloud-Native Applications
Extending graph knowledge bases to model distributed systems creates a new kind of information system, one intentionally designed for today’s IT challenges.
The Enterprise Knowledge Graph Foundation was recently established to define best practices and mature the marketplace for EKG adoption, with a launch webinar on June the 23rd.
The Foundation defines its mission as including adopting semantic standards, developing best practices for accelerated EKG deployment, curating a repository of reusable models and resources, building a mechanism for engagement and shared knowledge, and advancing the business cases for EKG adoption.
Enterprise Knowledge Graph Maturity Model
The Enterprise Knowledge Graph Maturity Model (EKG/MM) is the industry-standard definition of the capabilities required for an enterprise knowledge graph. It establishes standard criteria for measuring progress and sets out the practical questions that all involved stakeholders ask to ensure trust, confidence and usage flexibility of data. Each capability area provides a business summary denoting its importance, a definition of the added value from semantic standards and scoring criteria based on five levels of defined maturity.
Enterprise Knowledge Graphs is what the Semantic Web Company (SWC) and Ontotext have been about for a long time, too. Two of the vendors in this space that have been around for the longer time just announced a strategic partnership: Ontotext, a graph database and platform provider, meets SWC, a management and added value layer that sits on top.
SWC and Ontotext CEOs emphasize how their portfolios are complementary, while the press release states that the companies have implemented a seamless integration of the PoolParty Semantic Suite™ v.8 with the GraphDB™ and Ontotext Platform, which offers benefits for many use cases.
#database #artificial intelligence #graph databases #rdf #graph analytics #knowledge graph #graph technology
1624264440
Weighted Graph Queries in InfiniteGraph
In this article, learn the concept of a weighted graph and queries in the InfiniteGraph database and show how InfiniteGraph offers several unique advantages.
1. Introduction
Graph databases have moved to the forefront of trendy technologies. There are a lot of mature companies with graph database technologies and a lot of new players seem to be arriving on the scene almost daily, and for good reason; graphs are a more natural way to represent many kinds of data. They excel at modeling and managing the connections between data elements and this opens up new possibilities for what we can accomplish with our data.
In this blog, we will introduce the concept of a weighted graph and weighted graph queries in the InfiniteGraph database, and show how InfiniteGraph offers several unique advantages for performing weighted graph queries.
#tutorial #big data #graph database #graph database analytics #infinite graph #weighted graphs