Results 131 to 140 of about 1,989 (220)

Large scale retrieval for the LinkedIn feed using causal language models

AI Magazine, Volume 47, Issue 3, Fall 2026.
Abstract In large‐scale recommendation systems like LinkedIn's, the retrieval stage is critical for narrowing billions of potential candidates to a manageable subset for ranking. LinkedIn's feed now serves suggested content based on the topical interests of members, where 2000 candidates are retrieved from several million candidates with a latency ...
Sudarshan Srinivasa Ramanujam, Antonio Alonso, Saurabh Kataria, Siddharth Dangi, Akhilesh Gupta, Birjodh Singh Tiwana, Manas Haribhai Somaiya, Luke Simon, David Byrne, Madhu Arun, Sojeong Ha, Sen Zhou, Andrei Akterskii, Zhanglong Liu, Samira Sriram, Zihan Xiong, Zhoutao Pei, Angela Shao, Alex Li, Annie Xiao, Caitlin Kolb, Thomas Kistler, Zach Moore, Hamed Firooz   +23 more
wiley   +1 more source

Applying active learning to supervised word sense disambiguation in MEDLINE. [PDF]

J Am Med Inform Assoc, 2013
Chen Y, Cao H, Mei Q, Zheng K, Xu H.
europepmc   +1 more source

An Update on the Model of Connectivity of the Hippocampal Formation (I): The Perforant Pathway to the Dentate Gyrus

Hippocampus, Volume 36, Issue 5, September 2026.
ABSTRACT The hippocampus participates in crucial functions such as memory consolidation, spatial processing and emotional regulation that require diverse input from multiple cortical areas that is funneled through the upper layers of the entorhinal cortex (EC), mostly from layer II to the dentate gyrus (DG).
Jon I. Arellano, Pasko Rakic
wiley   +1 more source

A Systematic Review and Taxonomy of Fall Detection in Geriatric Care: Current State, Challenges, and Applications

WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 3, September 2026.
Overview of fall‐detection approaches and technologies in geriatric care. ABSTRACT This systematic review provides a critical examination of fall detection (FD) technologies in geriatric care, analyzing both technological innovations and implementation challenges across diverse healthcare environments.
Hamid Ali, Ji Zhang, Xiaohui Tao, Raj Gururajan, Xujuan Zhou, Yuquan Gan, Josh Jia‐Ching Ying   +6 more
wiley   +1 more source

Word sense disambiguation in the clinical domain: a comparison of knowledge-rich and knowledge-poor unsupervised methods. [PDF]

J Am Med Inform Assoc, 2014
Chasin R, Rumshisky A, Uzuner O, Szolovits P.   +3 more
europepmc   +1 more source

When Is Social Value Proportionate to Research Risks?

Bioethics, Volume 40, Issue 7, Page 707-716, September 2026.
ABSTRACT Ethical human subjects research must have an acceptable risk‐benefit ratio, which requires that the net risks participants face be proportionate to the research's social value. Yet existing scholarship does not explain what makes risks proportionate to social value.
Robert Steel
wiley   +1 more source

Collocation analysis for UMLS knowledge-based word sense disambiguation. [PDF]

BMC Bioinformatics, 2011
Jimeno-Yepes A, McInnes BT, Aronson AR.
europepmc   +1 more source

Hedgehog Pillows and Squirrel Plates: Priming Semantic Structure in Children's Comprehension

Language Learning, Volume 76, Issue 3, Page 992-1026, September 2026.
Abstract We report three expression–picture‐matching experiments targeting preschoolers’ semantic processing. We assessed whether 3‐ and 4‐year‐olds’ interpretations of ambiguous novel noun–noun combinations (e.g., hedgehog pillow) were affected by immediate language experience and what role lexical items played in this process.
Judit Fazekas, Leone Buckle, Holly Branigan   +2 more
wiley   +1 more source

Entity Linking meets Word Sense Disambiguation: a Unified Approach

Transactions of the Association for Computational Linguistics, 2021
Andrea Moro, Alessandro Raganato, Roberto Navigli   +2 more
doaj   +1 more source

Exploiting domain information for Word Sense Disambiguation of medical documents. [PDF]

J Am Med Inform Assoc, 2012
Stevenson M, Agirre E, Agirre E, Soroa A.   +3 more
europepmc   +1 more source