Results 51 to 60 of about 620,805 (282)

Perbandingan Cosine Similarity dan Mean Squared Difference dalam Rekomendasi Buku Fiksi berbasis Item

Edumatic
The need for recommendations is increasingly crucial in the digital era, especially with the abundance of fiction book data from e-book platforms and digital libraries.
Lucyta Qutsyaning Rosydah, Triyanna Widiyaningtyas   +1 more
doaj   +1 more source

Similarity Identification of Large-scale Biomedical Documents using Cosine Similarity and Parallel Computing

Knowledge Engineering and Data Science, 2022
Document similarity computation is an important research topic in information retrieval, and it is a crucial issue for automatic document categorization.
Merlinda Wibowo, Christoph Quix, Nur Syahela Hussien, Herman Yuliansyah, Faisal Dharma Adhinata   +4 more
doaj   +1 more source

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

Metaporicity, Creativity, and Cosine Similarity

, 2021
This study uses norms to create a measure of conceptual distance in adjective-noun pairs. The cosine similarity measures the degree to which the adjective has a different "sensory profile" than the noun, that is, refers to different senses. For example, "
Francesca Strik Lievers, Bodo Winter
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

Penerapan Analisis Sentimen pada Pengguna Twitter Menggunakan Metode K-Nearest Neighbor

JISKA (Jurnal Informatika Sunan Kalijaga), 2018
This research is made to implement the KNN (K-Nearest Neighbor) algorithm for sentiment analysis Twitter about Jakarta Governor Election 2017. The object is 2000 data tweets in Indonesia collected from Twitter during Januari 2017 using Python package ...
Akhmad Deviyanto, Muhammad Didik Rohmad Wahyudi   +1 more
doaj   +1 more source

Adversarial Detection Based on Inner-Class Adjusted Cosine Similarity

Applied Sciences, 2022
Deep neural networks (DNNs) have attracted extensive attention because of their excellent performance in many areas; however, DNNs are vulnerable to adversarial examples.
Dejian Guan, Wentao Zhao 
doaj   +1 more source

The Hidden Pitfalls of the Cosine Similarity Loss

CoRR
We show that the gradient of the cosine similarity between two points goes to zero in two under-explored settings: (1) if a point has large magnitude or (2) if the points are on opposite ends of the latent space. Counterintuitively, we prove that optimizing the cosine similarity between points forces them to grow in magnitude.
Andrew Draganov, Sharvaree P. Vadgama, Erik J. Bekkers   +2 more
openaire   +2 more sources

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

Symbolic Regression and Multi‐Objective Optimization of the Flory–Huggins Interaction Parameter for Hydrogels

Advanced Engineering Materials, EarlyView.
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang, Adrian Ehrenhofer, Thomas Wallmersperger   +2 more
wiley   +1 more source