GraphNews

GPU->Rapids->Cugraph->Scalable Graph Analytics

#SchemaOrg created FAQ Schema. #Google introduced filtering parameters that come w Search implementation. These act as commandments for Google’s algorithm which should be abided by for when markup is used in search results #SEO #semantics h/t @cyberandy

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Graph Theory and #DataScience: A topic intro with the Bridges of Königsberg. Graph Theory can be used to represent and analyze a wide variety of network information, has numerous modern applications within Data Science #data #tech #software #algorithms

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Building open domain conversational systems that allow users to have engaging conversations on topics of their choice is a challenging task. Alexa Prize was launched in 2016 to tackle the problem...

We explore the use of a knowledge graphs, that capture general or commonsense knowledge, to augment the information extracted from images by the state-of-the-art methods for image captioning. The...

Incorporating knowledge graph (KG) into recommender system is promising in improving the recommendation accuracy and explainability. However, existing methods largely assume that a KG is complete...

This paper presents the KG Usage framework, which allows the introduction of KG features to support Trust, Privacy and Transparency concerns regarding the use of its contents by applications. A...

To provide more accurate, diverse, and explainable recommendation, it is compulsory to go beyond modeling user-item interactions and take side information into account. Traditional methods like...

Background. Most tutorial ontologies focus on illustrating one aspect of ontology development, notably language features and automated reasoners, but ignore ontology development factors, such as...

.@opencitations & its datasets, tools, services, activities: #DataModel; @sparontologies (Semantic Publishing & Referencing) #ontologies; open software for searching, browsing and providing REST APIs over RDF #graphDBs; and more #OpenScience #OA https://arxiv.org/abs/1906.11964

Pinterest is a popular Web application that has over 250 million active users. It is a visual discovery engine for finding ideas for recipes, fashion, weddings, home decoration, and much more. In...

Roles are sets of structurally similar nodes that are more similar to nodes inside the set than outside, whereas communities are sets of nodes with more connections inside the set than outside...

In order to facilitate the accesses of general users to knowledge graphs, an increasing effort is being exerted to construct graph-structured queries of given natural language questions. At the...

Automatic KB completion for commonsense knowledge graphs (e.g., ATOMIC and ConceptNet) poses unique challenges compared to the much studied conventional knowledge bases (e.g., Freebase)....

#Knowledgegraphs have proven to be effective for high-quality recommendation. This #research designs a novel attentive knowledge graph embedding (AKGE) framework for recommendation, which exploits both semantics & topology in interaction-specific manner

Reasoning over paths in large scale #knowledgegraphs has many applications. @healx #research on approach to automatically build & rank paths between source & target entity pair with learned embeddings using a knowledge base completion model #EmergingTech

Same Stats, Different Graphs: Exploring the Space of Graphs in Terms of Graph Properties. #Data analysts use statistics to summarize large datasets, but it can be misleading. #Research considers similar problem in graph mining #knowledgegraph #analytics http://arxiv.org/abs/1911.01527

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

#Semantic Scholar Graph of References in Context: a large contextual citation graph of 81.1M academic publications, including parsed full text for 8.1M open access papers, across broad #science domains #research #knowledgegraph #openscience #AI @allen_ai

Commonsense #knowledgegraphs are rich repositories that encode how the world is structured. Scene graphs are powerful representations that encode images into their abstract #semantic elements. #Research presents a unified formulation #AI #EmergingTech

An accurate representation of knowledge is essential for teaching systems. This #research gives insight into different knowledge representation techniques and their categorization into various problem domains in #AI #taxonomy #applications h/t @aaranged https://arxiv.org/abs/2001.04835

mannheim.de/41307/1/Ristoski_RDF2Vec.pdf ​ If you have any questions, problems running the code, or an interesting use case. Get in touch with us! submitted by

This Stardog Training teaches you the basics of the RDF data model and best practices for ontology development. To learn more, visit stardog.com

A "definitive feature of knowledge graphs is the ability to connect concepts to external resources using Linked Data". ✔️ @taxobob bit.ly/2SDis4h

This article, based on a comprehensive history and definitions of the concept, provides a common-sense view of how to understand knowledge graphs.

A story about graph databases and how you can leverage the tech to turn companies and products around.