GraphNews

A project on optical graph recognition with OpenCV and yFiles WPF.

A thorough introduction to knowledge graphs

sided issue when it comes to sourcing a pool of candidates. While they need to provide their hiring managers with a solid list of professionals, these professionals also need to be relevant, qualified and interested in the opportunity being offered – otherwise, they’re likely to drop out during the interviewing process because the job isn’t right for them, or they won’t respond to begin with. This sourcing challenge drastically grows when sudden growth or reorganization increases the number of roles that recruiters need to fill. And ev

.@RedisLabs has implemented openCypher query language over a specialized #data structure. Coverage currently ~60% growing -> 80% soon. Redis Labs is participating in effort to define new standard for graph query languages #graphDB #opensource #innovation

An #opensource #software framework to build Games with Purpose for #linkeddata refinement: Web applications to crowdsource partial ground truth, by motivating user participation through fun incentives #knowledgegraph #datascience #data #opendata #research

eBay researchers recently published a paper about a method for KG relation embedding using dihedral group. Experimental results on benchmark KGs show that the model outperforms existing bilinear form models and even deep learning methods.

A relational graph #neuralnetwork w bi-directional attention mechanism & hierarchical representation learning for open-domain question answering. Can learn contextual representation by jointly learning & updating query, #knowledgegraph, document #research

RDF support in #Neo4j. Neosemantics Release 3.5.0.4 for Neo4j 3.5.x by @jbarrasa. Example use: Importing @wikidata fragments into #Neo4j #Semantics #data #datamodel #knowledgegraph #tech #analytics #datascience

Dgraph is an open-source, transactional, distributed, native graph database. Ever since the internet explosion, the data not just has been growing in size, but also in its complexity and connectedness.

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.

Recently we started getting involved in Netezza replacement opportunities with AnzoGraph, our Graph Online Analytical Processing (Graph OLAP) database. AnzoGraph Netezza users can have all the value of Netezza plus more. More analytical capabilities. Faster performance. Cheaper operations.

phase approach to adapt unsupervised entity name embeddings to a knowledge graph subspace and jointly learn the adaptive matrix and knowledge representation. Experiments on Freebase show that our method can

Representing Graph #Data Structures: Edge Lists, Adjacency Matrices, Adjacency Lists #datascience #analytics #tutorial #datamodel #softwareengineering #data #tech

https://t.co/4Ohse28toR

Graph Data (Image credit actify)eCommerce catalogs are created by sourcing data from sellers(3P), suppliers/brands(1P). The data provided by partners (sellers, suppliers, brands) are often incomplete, sometimes missing crucial bits of information that our customers are looking for. Even though partners adhere to a spec (an agreed format for sending product data) there is a vast amount of data buried in the title, description and images. Besides the data provided by our partners there are lots of unstructured data on the internet in the form of product manual, product reviews, blogs, social media sites etc.At Walmart we are working on building a Retail Graph that captures the knowledge about product and its related entities to help our customers better discover products in our catalog. It’s a product knowledge graph that can answer questions about products and related knowledge in the retail context. Such a system can be used to power semantic search, recommendation system etc.

A case for response time focused query processing by @olafhartig at #ISWC19 Rethinking optimization criteria for Web querying. Optimizing Query execution time is not the same as optimizing Query Response time #research #www #linkeddata #keynote

How we used the Gremlin Graph API to manage role-based access control to resources in a knowledge base application.

Understanding the role of Graph Databases in Big Data Analytics, Types of Graph Databases and Guide to Best Data Visualization Tools

down in that approach. Data analysis (and modeling)

Learn advanced Cypher queries for one approach to analyzing data inconsistencies directly in your flexible and forgiving Neo4j graph database.

answering is a natural human cognitive mechanism that plays a key ole in the acquisition of knowledge. We are constantly…

We are very happy to announce the 0.5 release of the SANSA (Semantic ANalytics StAck) framework - large-scale analysis, inference and querying of knowledge graphs! https://t.co/eVWy98MHso #AI #machinelearning #semanticweb #apachespark #apacheflink #knowledgegraphs— SANSA (@SANSA_Stack) December 12, 2018

We are very happy to announce the 0.6 release of the SANSA (Semantic ANalytics StAck) framework - for large-scale analysis, inference, and querying of knowledge graphs! https://t.co/zAFgEaslgU #AI #machinelearning #semanticweb #apachespark #apacheflink #knowledgegraphs— SANSA (@SANSA_Stack) July 2, 2019

The SPARQL 1.2 Community Group has been launched. They are looking for members to help with the new spec. Go on over and take a look.#sparql #w3c #webstandardshttps://t.co/THjGsaEoTN— Saveoney Software Consultants (@saveoney) April 2, 2019

hand that when trying to apply graph machine learning techniques to identify fraudulent behaviour in the bitcoin blockchain data, scalability was the biggest roadblock. The bitcoin blockchain graph we are using has millions of wallets (nodes) and billions of transactions (edges) which makes most graph machine learning methods infe