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based, and connectionist reasoning”

We announce the first release of the knowledge graph for public procurement, integrating tender and company data. TheyBuyForYou is a three year initiative bringing together researchers, innovators and public administrations from 5 European countries. It is supported by EU H2020. The aim of the programme is to make procurement data more easily accessible and hence facilitate better decisions in areas such as economic development, demand management, competitive markets and vendor intelligence.

Introduction

In this paper we introduce the latest version (Version 2.0) of OSCAR, the OpenCitations RDF Search Application, which has several improved features and extends the query workflow comparing with the previous version (Version 1.0) that we presented at

It’s no longer necessary to choose between RDF & LPG #knowledgegraphs. RDF* offers the best of both worlds so you don’t have to give up anything. #AI #EmergingTech #data #analytics #datascience

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A knowledge graph connects all data without moving or copying it. A knowledge graph seamlessly layers atop the existing data infrastructure, and reveals the relationships within the data, regardless of its source or format. These graphs are highly scalable, and retain each analysis, which acts as a reusable asset.

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This paper attempts to compare and combine different approaches for

Alethio brings you more than 18,000,000,000 facts about Ethereum

What is more important than data consolidation? Making sense of that data and communicating it to others. With data volumes growing and time for analysis decreasing, this doesn't seem like an easy task. Data visualisation, however, may be the most reliable way to get on with this daunting process and make it seamless. Data visualisation and more specifically graph visualisation helps you organize all your data and make it readable and insightful.

With the constant growth of Internet of Things (IoT) ecosystems, allowing them to interact transparently has become a major issue for both the research and the software development communities. In this paper we propose a novel approach that builds semantically interoperable ecosystems of IoT devices. The approach provides a SPARQL query-based mechanism to transparently discover and access IoT devices that publish heterogeneous data. The approach was evaluated in order to prove that it provides complete and correct answers without affecting the response time and that it scales linearly in la...

How can investigation into money distribution and tracking funds cross the borders of blockchains?

Graph machine learning (graphML) is a subset of deep learning with much higher accuracy because big data records are linked together by their relationships.

Artificial Intelligence company Expert System today announced the availability in its Cogito® AI platform of the Creative Works Ontology developed by MovieLabs, the non-profit R&D joint venture started by the major Hollywood studios. MovieLabs’s Creative Works Ontology, published late last year helps fill the need of media companies to adapt their infrastructures to an increasingly … Continue reading "Expert System supports media organizations with the MovieLabs Creative Works Ontology"

Most #machinelearning #algorithms work well w/ either text or structured #data. #Semantic data models can close the gap. Relationships between business/data objects can be made available for further analysis #knowledgegraph #AI #datascience #EmergingTech

Recent #research proved #deeplearning can be used to learn RDFS inference rules. A deficiency: lack of derivations for inferred triples, or explainability in #AI terms. @IBMResearch @jahendler provide inferred graph, explain how triples were inferred

Incorporating knowledge graphs into recommender systems has attracted increasing attention in recent years. By exploring the interlinks within a knowledge graph, the connectivity between users and items can be discovered as paths, which provide rich and complementary information to user-item interactions. Such connectivity not only reveals the semantics of entities and relations, but also helps to comprehend a user’s interest. However, existing efforts have not fully explored this connectivity to infer user preferences, especially in terms of modeling the sequential dependencies within and ...

And of course, querying it with SPARQL.

SciBite CTO James Malone gives his views on the most useful ways to visualise an ontology.

A series on how the decentralised XRP ledger can be used to explore relationships between wallets using a graph database. This first part focuses on graph databases versus “normal database” and my process of establishing the database.

19 data lake. A large amount of data on coronavirus exists in research publications. One of the datasets in the data lake is a massive corpus of these publications, which the Allen Institute for AI aggregates and updates. The problem lies in how to find and extract the information you need. This post walks you through solving this problem using knowledge graphs. Amazon Neptune is a fast, reliable, fully managed graph database service that makes it easy to build and run applications that work with highly connected datasets. T

[Submitted on 17 Apr 2020] Download PDF Abstract: ``Classical'' word embeddings, such as Word2Vec, have been shown to capture

distanceFeature engineering

Extracting Novel Facts from Tables for Knowledge Graph Completion (Extended version) Benno Kruit et al. https://t.co/FMyQ0Nd8lv pic.twitter.com/8ecT8VenYE— Aaron Bradley (@aaranged) July 3, 2019

based search systems do not reflect the semantics of individual input words of search queries. For example, a query for the word “house” would not return records for the words “building” or “real estate”. How can such relationships be represented in a technical system? One approach is to include synonyms. Search engines like Elasticsearch provide methods to integrate synonym lists. However, a list of synonyms itself is required for configuration.

Facebook appears to be testing the addition of Wikipedia knowledge panels in search results, according to reports from multiple users.Based on the screenshots shared on Twitter, this feature is reminiscent of Google’s integration with Wikipedia.Here’s an example that was spotted a few days ago:New? Facebook shows Wikipedia snippits in search resultsh/t @jc_zijl pic.twitter.com/zcbQJmauhE— Matt Navarra | 🚨 #StayAtHome (@MattNavarra) June 9, 2020Just like in Google’s search results, the Wikipedia knowledge box in Facebook search shows key details about the entity being searched for.You’ll also notice there’s a lone Instagram link, which is a stark contrast to Google’s search results containing links to all popular social media profiles.Unlike Google’s knowledge panels, which link to a number of domains where people can learn more about a entity, Facebook is trying to keep people within the Facebook ecosystem as much as possible.Here’s another example that looks

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Facebook’s recent $5.7 billion investment in Indian telecommunications behemoth Jio Platforms goes beyond the typical tech deal and will help the American social media titan finally unlock the world's biggest democracy.