Results 111 to 120 of about 1,195,838 (307)

Field Report from Collaborative Research Center 1625: Heterogeneous Research Data Management Using Ontology Representations

Advanced Engineering Materials, EarlyView.
A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed, Samuel García Vázquez, Behnam Mardani, Victor Dudarev, Alfred Ludwig, Maribel Acosta, Markus Stricker   +6 more
wiley   +1 more source

Multi-type relational clustering approaches : current state-of-the-art and new directions [PDF]

, 2008
The proliferation of multi-type relational datasets in a number of important real-world applications and the limitations resulting from the transformation of such datasets to fit propositional data mining approaches have led to the emergence of the ...
Anand, Sarabjot Singh, Li, Tao
core   +1 more source

Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization

Advanced Engineering Materials, EarlyView.
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier, Moritz Blum, Luana Caron, Alisa Chirkova, Philipp Cimiano, Basil Ell, Inga Ennen, Michael Feige, Maik Gaerner, Thomas Hilbig, Andreas Hütten, Günter Reiss, Tapas Samanta, Sonja Schöning, Christian Schröder, Lennart Schwan, Chris Taake, Martin Wortmann   +17 more
wiley   +1 more source

Group Fairness in Recommendation Systems: The Importance of Hierarchical Clustering in Identifying Latent Groups in MovieLens and Amazon Books

Journal on Interactive Systems
Fairness in recommendation systems is a critical area of study, particularly when addressing group disparities based on sensitive attributes such as gender, age, activity levels, or user location.
Rafael Vargas Mesquita dos Santos, Giovanni Ventorim Comarela   +1 more
doaj   +1 more source

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

Advanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch, Maximilian Holland, Klaus Drechsler, Johannes Schilp   +3 more
wiley   +1 more source

DCOPA: a distributed clustering based on objects performances aggregation for hierarchical communications in IoT applications

, 2022
Developing clustering algorithms for energy optimization, for the Internet of Things (IoT) applications based mainly on wireless sensors networks services, is a major research challenge.
Mir, F., Meziane, F.
core   +1 more source

Hierarchical clustering using the arithmetic-harmonic cut: complexity and experiments.

PLoS ONE, 2010
Clustering, particularly hierarchical clustering, is an important method for understanding and analysing data across a wide variety of knowledge domains with notable utility in systems where the data can be classified in an evolutionary context.
Romeo Rizzi, Pritha Mahata, Luke Mathieson, Pablo Moscato   +3 more
doaj   +1 more source

A Lightweight Procedural Layer for Hybrid Experimental–Computational Workflows in Materials Science

Advanced Engineering Materials, EarlyView.
We unveil a prototype hybrid‐workflow framework that fuses automatedcomputation with hands‐on experiments. Built atop pyiron, a lightweight, parameterized layer translates procedure descriptions into executable manual steps, syncing instrument settings, human interventions, and data capture in real‐time today.
Steffen Brinckmann, Sarath Menon, Raphael Röske, Johannes Steinhülb, Michael Selzer, Jan Janssen, Tilmann Hickel, Ruth Schwaiger, Jörg Neugebauer   +8 more
wiley   +1 more source

Clustering On Large Numeric Data Sets Using Hierarchical Approach: Birch [PDF]

, 2012
The paper is about the clustering on large numeric data sets using hierarchical method In this BIRCH approach is used to reduce the amount of data for this a hierarchical clustering method was applied to pre-process the dataset Now a day s web ...
T. Swarna Latha, Dr. A. Senguttuvan, D. Pramodh Krishna   +2 more
core  

Hierarchical topological clustering

CoRR
not peer reviewed, reviewed version to appear in Soft ...
Ana Carpio, Gema Duro
openaire   +3 more sources