Results 51 to 60 of about 4,047 (208)

Knowledge Graph Publication and Browsing Using Neo4J

, 2021
Slides of the presentation during the SCG Workshop in Amsterdam, on September 6th. Link: https://mosaicrown.github.io/scg2021/The slides covered three main proposals: - A set of mappings from RDF to Neo4J Property Graph - An implementation in Neo4J ...
Ghislain Atemezing (3330090)
core   +1 more source

Knowledge graphing in forensics: Modeling forensic case trajectories using news media

Journal of Forensic Sciences, Volume 71, Issue 4, Page 1693-1705, July 2026.
Abstract We employ a knowledge graph (KG) approach to aggregate qualitative information to harness and systematically incorporate contextual information into a forensic investigation. We are interested in tracing the spatial distribution and what happens to unidentified human remains after discovery—relationships and successive movements that are not ...
Molly Miranker, Min‐Hsueh Chiu, Mayank Kejriwal, Alberto Giordano   +3 more
wiley   +1 more source

RELATIONAL DATABASE AND GRAPH DATABASE: A COMPARATIVE ANALYSIS [PDF]

Journal of Process Management and New Technologies, 2017
Since 1970, relational database models have been in use for storing, manipulating and retrieving data. The importance of relational databases is going to decrease due to the exponential growth of data as it is difficult to work with large number of ...
Surajit Medhi, Hemanta K. Baruah
doaj   +1 more source

Applying knowledge graphs: Migrant decedent case trajectories in South Texas

Journal of Forensic Sciences, Volume 71, Issue 4, Page 1706-1717, July 2026.
Abstract The phenomenon of migrant death at the Texas‐Mexico border is well documented, but questions remain as concerns its spatial distribution and what happens to human remains after discovery. To start exploring these questions, we developed a knowledge graph (KG) approach to aggregate qualitative information concerning migrant death and elucidate ...
Molly Miranker, Min‐Hsueh Chiu, Mayank Kejriwal, Alberto Giordano   +3 more
wiley   +1 more source

The metadata ecosystem and AI: Enabling FAIR and AI‐ready data

AI Magazine, Volume 47, Issue 2, Summer 2026.
Abstract Reproducibility is a foundational tenet of science. As artificial intelligence (AI) becomes increasingly embedded across science, the need to accurately document the provenance, structure, and behavior of training data, models, and workflows grows correspondingly. Metadata, understood as explicit and structured knowledge about data and related
Jane Greenberg, Joel Pepper, Xintong Zhao, Richard Marciano, David Breen, Yuan An   +5 more
wiley   +1 more source

Prediction Model for Soybean Productivity [PDF]

Database Systems Journal
This paper presents a holistic approach to biological and agricultural research focused on the use of interconnected technologies in the context of climate change.
Ion GANEA
doaj  

Ontology-driven development of dialogue systems

South African Computer Journal, 2023
A new technique and its software implementation are presented to create a deeply semantically structured ontology using plain natural language text as input, without regular structure or any previous tagging and markup.
Anna Litvin, Oleksandr Palagin, Vladislav Kaverinsky, Kyrylo Malakhov   +3 more
doaj   +1 more source

A multi‐source fusion and dynamic verification framework for scientific knowledge graph construction: Methods, evaluation, and applications

AI Magazine, Volume 47, Issue 2, Summer 2026.
Abstract The exponential growth of scientific literature—over 2.5 million papers and 3.5 million patents annually—poses critical challenges for knowledge discovery. To address these, we propose SCIMKG (Scientific Knowledge Graph), a framework for constructing scientific knowledge graphs via multi‐source heterogeneous multi‐source.
Erxi Zhu, Yuan Hu
wiley   +1 more source

DeepSeek‐Lattice‐KG: A Compact Language Model With Knowledge Graph Augmentation for Lattice Structure Design

Materials Genome Engineering Advances, Volume 4, Issue 2, June 2026.
DeepSeek‐Lattice‐KG integrates a domain‐adapted 14B LLM with a Neo4j lattice knowledge graph distilled from 50,000 papers. It analyzes queries, retrieves supporting subgraphs, and generates grounded answers; on a 2100‐question, six‐domain benchmark, it achieves 94.8% accuracy.
Zhiyang Shu, Chao Wang, Changsheng Feng, Feiyu Zhou, Xueyan Chen, Yan Chen, Yilun Liu   +6 more
wiley   +1 more source

Fast power flow calculation for distribution networks based on graph models and hierarchical forward-backward sweep parallel algorithm

Frontiers in Energy Research
IntroductionIn response to the issues of complexity and low efficiency in line loss calculations for actual distribution networks, this paper proposes a fast power flow calculation method for distribution networks based on Neo4j graph models and a ...
Xinrui Wang, Wengang Chen, Ruimin Tian, Yuze Ji, Jianfei Zhu   +4 more
doaj   +1 more source