GraphNews

Beyond improving institutional memory, #knowledgegraphs open an organization's data to the growing sophistication of #artificialintelligence. https://t.co/e5WyplfL8i #semantictechnology #linkeddata #knowledgemanagement— Ontotext (@ontotext) September 30, 2020

Interesting paper on which parts of SPARQL query language are easier or more difficult to understand: https://t.co/TgWNXFrCfv— Learning SPARQL (@LearningSPARQL) September 29, 2020

⭕ Insightful Reading: "Semantic #KnowledgeGraphs Soar To The Fore Of #AI" v/@AITimeJournal #BigData #Analytics #DataScience #ML #IoT #IIoT #Python #RStats #TensorFlow #javascript #reactjs #CloudComputing #Linux #programming #coding #Industry40https://t.co/1GQw3IgRUa pic.twitter.com/aCnCY0NCJn— Bomoi Abdulmajid (@Bomoimajid) September 24, 2020

Everything you always wanted to know but never dared to ask about #knowledgeGraphs:On Oct. 27, 2020, our new free online course "Knowledge Graphs" with @lysander07 and @em_alam will start on the @openHPI platform. Register now at https://t.co/UA9XxTOO3O pic.twitter.com/V6YGkV5Pu4— Harald Sack (@lysander07) September 12, 2020

In this blog post, we explore how the performance of Memgraph as evolved across version from v0.15.2 to v1.1.0 and discuss how we were able to reduce memory usage by as much as 50% and improve throughput towards near-linear scalability.https://t.co/R8XTh520CK— Memgraph (@memgraphdb) October 1, 2020

Lots of very good material here. Covers a lot of ground including Amazon Neptune, performance tuning, data modeling, common use cases and also some @apachetinkerpop Gremlin and @w3c RDF tutorials. https://t.co/3gdcKcNHiT— Kelvin Lawrence (@gfxman) October 1, 2020

Ever had some weird dataset you wanted, like "a list of every US senator ever and their gender?" and thought "ugh, that's gonna be a pain to assemble?"Or "Wikipedia has info on X, but it's gonna be hard to get out?"Well, Have you heard of Wikidata?https://t.co/1L6pkFh43h pic.twitter.com/8KiZyKKlSX— Erin ✨💽 (@erincandescent) October 1, 2020

https://t.co/kSTvjW2oBv Such a thoughtful article on #knowledgegraphs! @TDataScience pic.twitter.com/BphubNoYwv— James Le (@le_james94) October 1, 2020

This is just super satisfying. A @GavinMGleason query to combine conflict data from @dbpedia and @SeshatDatabank I love:1. the explosion2. dragging empires around followed by their battles pic.twitter.com/4oxAT8ynAF— TerminusDB (@TerminusDB) October 1, 2020

This current issue of https://t.co/iSEn2yvLfR covers #datagovernance #dataestate #data's #gendergap #datacatalog #dataestate #knowledgegraphs #DMP ... more. New content from @RSeiner @MandySeiner @AJAlgmin Polikoff of @TopQuadrant Beechum and @HBKI71. https://t.co/EEuVW3g7SG pic.twitter.com/sIL7KvLiJp— TDAN (@TDAN_com) October 1, 2020

In case you missed it, the recording of last week's #Lotico session on JSON-LD is now available. https://t.co/Pzlyjh2S89. #jsonld cc/@neumarcx— Gregg Kellogg (@Gkellogg) October 1, 2020

We’re proud to announce that Stardog is joining the Enterprise Knowledge Graph Foundation as a founding vendor member. Read on if you want to learn who, what, and why.

While five new #AI solutions enter the Gartner Hype Cycle for AI, 2020 what trends are dominating this year’s #AI landscape? Read Gartner analyst Svetlana Sicular’s views here. #GartnerSYM #CIO #ML #Chatbot

Most of the world’s knowledge is encoded in natural language (e.g., news articles, books, emails, academic papers). It is estimated that 80 percent of business-relevant information originates in un…

Introduction to timbr and the Covid-19 SQL knowledge graph

Diving into the bowels of a global organization

An overview of how Strise tackle the Entity Linking problem.

Google introduces a personalized entity repository, similar to a user-specific knowedge graph to predict actions and suggestions for users of Google.

Interview with Giovanni Campagna, one of the Almond principal developers

Happy to announce that my @OReillyMedia book Semantic Modeling for Data is now published https://t.co/4yngwDPMrO and available in electronic and print format https://t.co/VsFc8zf2KY. Get a free sample chapter at https://t.co/DivwADNUGo #datascience #datamodeling #knowledgegraphs pic.twitter.com/9j58IF1lcZ— Panos Alexopoulos (@PAlexop) September 9, 2020

A cheat sheet for quickly analyzing and evaluating relationships in graph networks using Python, Networkx, and Gensim

Using neo4j’s power for scalable graph analytics in Python

Can We Divide It Into Supervised/Unsupervised Learning? It’s Not That Simple…

Wikidata and Wikipedia have been proven useful for reason-ing in natural language applications, like question answering or entitylinking. Yet, no existing work has studied the potential of...