Results 91 to 100 of about 1,142,269 (203)

English address terms in Australian, British and North American English on Twitter/X

World Englishes, EarlyView.
ABSTRACT This study analyses address terms on Twitter/X across three English‐speaking regions: Australia, the United Kingdom and the United States. Using a random sample, we examine the frequency and regional distribution of address forms, including @‐mentions, vocatives, titles, kinship terms and greetings.
Martin Schweinberger, Amir Sheikhan
wiley   +1 more source

Global Landscape and Thematic Evolution of Selective GLP‐1 Receptor Agonists and GLP‐1–Based Multi‐Receptor Agonists in Type 2 Diabetes Mellitus: A Bibliometric Analysis

Endocrinology, Diabetes &Metabolism, Volume 9, Issue 6, November 2026.
Bibliometric analysis of 3736 publications (2004–2025) reveals rapid growth in GLP‐1–based T2DM research. The US leads, with Novo Nordisk and Eli Lilly as top contributors. Thematic shifts from glycemic control toward cardiovascular‐kidney‐metabolic outcomes and real‐world evidence, driven by landmark trials like LEADER and REWIND.
Yanbing Wang, Zhanru Liu, Shifeng Wang, Cuiyan Lv, Hesham R. El‐Seedi, Shaden A. M. Khalifa, Haiyan Wang   +6 more
wiley   +1 more source

ArGemma: A Multi‐Task Fine‐Tuning Framework for Adapting Gemma to Arabic

Expert Systems, Volume 43, Issue 11, November 2026.
ABSTRACT Open‐source large language models (LLMs) have significantly advanced natural language processing (NLP), particularly for English. However, their performance in Arabic has remained limited due to the scarcity of high‐quality datasets and the high computational cost of full fine‐tuning.
Taha Alselwi, Serap Çakar Kaman, Beyza Eken   +2 more
wiley   +1 more source

Disambiguating named entities by semantic web

Advances in Intelligent Systems Research, 2014
There are many words in natural language sentences which describe an object or event in real world. An important step to understand a sentence is finding the exact meaning of all words. In this paper we propose an approach to identify meaning of each named entity of a text by using web of data (LOD) as a large scale knowledge base.
Koohpeyma Fateme, Azari Ideh
openaire   +2 more sources

Leveraging Linked Open Data to Automatically Answer Arabic Questions

IEEE Access, 2019
The interchangeably connected Web technologies and the advancements that accompany the semantic web content's leaps, have raised many challenges in the results' retrieval process especially for the Arabic Language. This research targets an important, yet
Mohammad Al-Smadi, Islam Al-Dalabih, Yaser Jararweh, Patrick Juola   +3 more
doaj   +1 more source

Risk–Benefit of Phase 2 Monotherapy Trials in Adult Solid Cancers: A Systematic Review and Meta‐Analysis

International Journal of Cancer, Volume 159, Issue 8, Page 2015-2024, 15 October 2026.
The therapeutic status of drug administration in phase 2 cancer trials is ambiguous, as these studies test efficacy without strong evidence of clinical benefit. Nonetheless, patients face meaningful risks. This review compared efficacy and safety of monotherapy drugs in phase 2 and phase 3 trials across six cancer types.
Charlotte Ouimet, Monica Rosu, Jonathan Kimmelman   +2 more
wiley   +1 more source

Optimising Selective Sampling for Bootstrapping Named Entity Recognition [PDF]

, 2005
Training a statistical named entity recognition system in a new domain requires costly manual annotation of large quantities of in-domain data. Active learning promises to reduce the annotation cost by selecting only highly informative data points.
Hachey, Benjamin Clayton, Hachey, Ben, Grover, Claire, Grover, Claire; id_orcid, Alex, Beatrice, Becker, Markus   +5 more
core  

Research on High-Quality Knowledge Acquisition Methods and Intelligent Office Knowledge Value-Added Strategies for Large-Scale Documents in the Cloud

Journal of Applied Science and Engineering
In response to the growing demand for knowledge-intensive operations and the widespread adoption of cloud-based document management systems, this study proposes a comprehensive framework for high-quality knowledge acquisition and intelligent value ...
Haohong Zhou, Shichao Huang, Guoxin Zhong, Jun Huang   +3 more
doaj   +1 more source

An Advanced Natural Language Processing Framework for Arabic Named Entity Recognition: A Novel Approach to Handling Morphological Richness and Nested Entities

Applied Sciences
Named Entity Recognition (NER) is a fundamental task in Natural Language Processing (NLP) that supports applications such as information retrieval, sentiment analysis, and text summarization.
Saleh Albahli
doaj   +1 more source

Improving Named Entity Disambiguation by Iteratively Enhancing Certainty of Extraction [PDF]

, 2011
Named entity extraction and disambiguation have received much attention in recent years. Typical fields addressing these topics are information retrieval, natural language processing, and semantic web.
Keulen, M. van, Habib, M. B.
core   +1 more source