Results 81 to 90 of about 179,841 (273)

Neural Collective Entity Linking

, 2018
Entity Linking aims to link entity mentions in texts to knowledge bases, and neural models have achieved recent success in this task. However, most existing methods rely on local contexts to resolve entities independently, which may usually fail due to ...
Cao, Yixin, Hou, Lei, Li, Juanzi, Liu, Zhiyuan   +3 more
core  

Determinants of local food producer participation in state‐sponsored marketing programs: Evidence from Missouri

Agribusiness, EarlyView.
Abstract This study examines producer participation choices considering a variety of potential benefits linked to state‐sponsored marketing programs, using a real choice dataset of farmers in Missouri. Multinomial logit models are employed to predict determinants of farmer enrollment in three tiers of the Missouri Grown local food marketing program ...
Lan Tran, Ye Su, Laura McCann
wiley   +1 more source

Harnessing Large Language Models to Advance Microbiome Research: From Sequence Analysis to Clinical Applications

Advanced Intelligent Discovery, EarlyView.
Large language models are transforming microbiome research by enabling advanced sequence profiling, functional prediction, and association mining across complex datasets. They automate microbial classification and disease‐state recognition, improving cross‐study integration and clinical diagnostics.
Jieqi Xing, He Wang, Yangyang Sun, Xiaoquan Su, Shunyao Wu   +4 more
wiley   +1 more source

OGER++: hybrid multi-type entity recognition

Journal of Cheminformatics, 2019
Background We present a text-mining tool for recognizing biomedical entities in scientific literature. OGER++ is a hybrid system for named entity recognition and concept recognition (linking), which combines a dictionary-based annotator with a corpus ...
Lenz Furrer, Anna Jancso, Nicola Colic, Fabio Rinaldi   +3 more
doaj   +1 more source

Automating AI Discovery for Biomedicine Through Knowledge Graphs and Large Language Models Agents

Advanced Intelligent Discovery, EarlyView.
This work proposes a novel framework that automates biomedical discovery by integrating knowledge graphs with multiagent large language models. A biologically aligned graph exploration strategy identifies hidden pathways between biomedical entities, and specialized agents use this pathway to iteratively design AI predictors and wet‐lab validation ...
Naafey Aamer, Muhammad Nabeel Asim, Shan Munir, Andreas Dengel   +3 more
wiley   +1 more source

Single‐Injection Multi‐Omics Analysis by Direct Infusion Mass Spectrometry

Angewandte Chemie, EarlyView.
A high‐throughput direct infusion mass spectrometry platform, enabled by gas‐phase ion mobility separation, supports single‐injection analysis of peptides, polar metabolites, and lipids. Coupled with custom software, it identified ∽1,300 proteins and ∽600 metabolites in ∽4.3 minutes per sample, and demonstrated broad utility in macrophage polarization ...
Yuming Jiang, Ivan Salladay‐Perez, Amanda Momenzadeh, Jesús Muñoz‐Estrada, Uktarsh Tripathi, Anthony J. Covarrubias, Jesse G. Meyer   +6 more
wiley   +2 more sources

Context-Driven Image Caption With Global Semantic Relations of the Named Entities

IEEE Access, 2020
Automatic image captioning has achieved a great progress. However, the existing captioning frameworks basically enumerate the objects in the image. The generated captions lack the real-world knowledge about named entities and their relations, such as the
Yun Jing, Xu Zhiwei, Gao Guanglai
doaj   +1 more source

OntoLogX: Ontology‐Guided Knowledge Graph Extraction From Cybersecurity Logs With Large Language Models

Advanced Intelligent Systems, EarlyView.
OntoLogX is an autonomous AI agent that uses large language models to transform unstructured cyber security logs into ontology grounded knowledge graphs. By integrating retrieval augmented generation, iterative correction, and a light‐weight log ontology, OntoLogX produces semantically consistent intelligence that links raw log events to MITRE ATT & CK
Luca Cotti, Idilio Drago, Anisa Rula, Devis Bianchini, Federico Cerutti   +4 more
wiley   +1 more source

Innovative Artificial Intelligence‐Assisted Systems for Social Science Research: Architecture Design and Applied Practice

AI &Innovation, EarlyView.
ABSTRACT The rapid advancement of large language model (LLM) technology is profoundly transforming the practice of social science research. Scholarly discussions on Artificial Intelligence (AI)'s role in social science research can be organised into three levels: AI as a research tool, AI as a methodological infrastructure and AI as a quasi‐cognitive ...
Jie Xiong
wiley   +1 more source

Automated Construction Method of Knowledge Graphs for Pirate Events

Applied Sciences
With the development of seaborne trade, international maritime crime is becoming increasingly complex. Detecting maritime threats by fusing the physical movement data from traditional physical sensors is not sufficient.
Cunxiang Xie, Zhaogen Zhong, Limin Zhang
doaj   +1 more source