#Semantic interoperability is the key enabler for #digitaltransformation. But how do we achieve it? By having content understandable & available in a machine processable form. #Ontologies will play a key role in providing infrastructure to support this

#NLP is now good enough that we can measure how well systems reads text in terms of extracted knowledge: Knowledge Base Population @diffbot released KnowledgeNet reproducible #dataset to measure this, w #opensource state-of-the-art baseline #research #AI

Literature review is complex, requires expert analysis of unstructured #data. #Automation of process presents opportunity for high throughput knowledge extraction & meta analysis. Gextext extracts #knowledgegraph of relationships from text #research #NLP

SHACL2SPARQL is a prototype Java implementation of the algorithm described in #iswc19 best #research paper award winner Validating SHACL constraints over a SPARQL endpoint (Corman, FLorenzano, Reutter & Savkovic). #opensource #github #softwaredevelopment

Analyzing US Lobbying Data in #Neo4J #graphdatabase

Personal Data Privacy Raises Difficult Questions. Tracking Personal Data Requires Deep Visibility, and #GraphDatabases Are a Good Foundation for #Data #Privacy #Compliance https://neo4j.com/blog/overcoming-ccpa-challenges-graph-technology-solves-personal-data-privacy-challenges/

VLog, a new rule based reasoner on #KnowledgeGraphs, with #opensource implementation on #Github #iswc_conf #research #sfotwareengineering h/t

The perfect dorm room assignment: Exploring the bipartite matching problem with #Neo4j #graphdatabase

Gartner Names PoolParty as Visionary in Metadata Management Magic Quadrant. Our modern approach combining machine learning and knowledge graphs makes the difference!

generation retrieval systems to improve retrieval performance. Knowledge graph abstracts things into entities and establishes relationships among entities, which are expressed in the form of triples. However, with the expansion of knowledge graph and the rapid increase of data volume, traditional place retrieval methods on knowledge graph have low performance. This paper designs a place retrieval method in order to improve the efficiency of place retrieval. Firstly, perform data preprocessing and problem model building in the offline stage. Meanwhile, build semantic distance index, spatial quadtree index, and spatial semantic hybrid index according to semantic and spatial information. At the same time, in the online retrieval stage, th

Learn about how AstraZeneca visualized patient journeys, answered important questions about prescriptions and diagnoses, and improved patient outcomes.

AtOoEEeib8ndhFNAFIw/citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.538.7139&rep=rep1&type=pdf , the original “Knowledge Graph” that Google acquired, has been the promise of pushing data control aspect from the database to the application layer including the possibility of people rolling their own situated personal ontologies in the expectation for being able to reconcile them through peer to peer interactions.Freebase exercised full control over the “Schema” and has demonstrated a million fold leverage of meta level knowledgeIn it’s day it had over 3000 million nodes and 3000 carefully defined and curated edge types.Years later Wiki

frames version.

pandemic) and have our LinkedIn feeds (trained by AI, ironically) locked into the data management world, these trends are

sourced Ampligraph, a suite of machine learning models that can uncover new knowledge from existing knowledge graphs. We’re also exploring how knowledge graphs can contribute to social good. Working with Lambert Hogenhout, Chief of Data Analytics for the United Nations, we organized a “Knowledge Graphs for Social Good” workshop. The effort focused on the UN’s 17 Sustainability Development Goals: concrete areas like poverty, hunger, and health where action is needed to impr

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Bill Slawski is an SEO legend.

Our interview with Teodora Petkova, sharing her views on weaving text into the semantic web and her recent book The Brave New Text.

down in that approach. Data analysis (and modeling)

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haystack discoveries that evade traditional analytic workflow.

I have seen several tools for converting spreadsheets to RDF over the years. They typically try to cover so many different cases that learning how to use them has taken more effort than just writing a short perl script that uses the split() command, so that’s what I usually ended up doing. (Several years ago I did come up with another way that was more of a cute trick with Turtle syntax.)

Gremlin Snippets are typically short and fun dissections of some aspect of the Gremlin language. For a full list of all steps in the Gremlin language see the Reference Documentation of Apache TinkerPop™. This snippet is based on Gremlin 3.4.7.Please consider bringing any discussion or questions about this snippet to the Gremlin Users Mailing List.

In this contributed article, editorial consultant Jelani Harper discusses how data modeling is the foundation of the data science discipline that’s [...]

In part 1 of this article series, I provided a quick primer on graph data structure, acknowledged that there are several graph based algorithms with the notabl…

commerce recommendations and financial risk management.

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