Results 41 to 50 of about 29,791 (235)

Word vs. Class-Based Word Sense Disambiguation [PDF]

open access: yes, 2015
As empirically demonstrated by the Word Sense Disambiguation (WSD) tasks of the last SensEval/SemEval exercises, assigning the appropriate meaning to words in context has resisted all attempts to be successfully addressed.
Izquierdo Beviá, Rubén   +2 more
core   +2 more sources

A Corpus-Based Word Sense Disambiguation For Geez Language

open access: yesEthiopian Journal of Science and Sustainable Development, 2021
In natural language processing, languages have a number of ambiguous words and solving such kind of problem for the language can help the development of word sense disambiguation using corpus­based Approach.
Amlakie Aschale Alemu, Kinde Anlay Fante
doaj   +1 more source

Attention Neural Network for Biomedical Word Sense Disambiguation

open access: yesDiscrete Dynamics in Nature and Society, 2022
In order to improve the disambiguation accuracy of biomedical words, this paper proposes a disambiguation method based on the attention neural network. The biomedical word is viewed as the center. Morphology, part of speech, and semantic information from
Chun-Xiang Zhang   +4 more
doaj   +1 more source

SupWSD: a flexible toolkit for supervised word sense disambiguation [PDF]

open access: yes, 2017
In this demonstration we present SupWSD, a Java API for supervised Word Sense Disambiguation (WSD). This toolkit includes the implementation of a state-of-the-art supervised WSD system, together with a Natural Language Processing pipeline for ...
DELLI BOVI, Claudio   +2 more
core   +1 more source

The interaction of knowledge sources in word sense disambiguation [PDF]

open access: yes, 2001
Word sense disambiguation (WSD) is a computational linguistics task likely to benefit from the tradition of combining different knowledge sources in artificial in telligence research.
Brill Eric   +9 more
core   +5 more sources

Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models

open access: yesAdvanced Robotics Research, EarlyView.
A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki   +2 more
wiley   +1 more source

Biomedical Word Sense Disambiguation Based on Graph Attention Networks

open access: yesIEEE Access, 2022
Biomedical words have many semantics. Biomedical word sense disambiguation (WSD) is an important research issue in biomedicine field. Biomedical WSD refers to the process of determining meanings of ambiguous word according to its context.
Chun-Xiang Zhang   +2 more
doaj   +1 more source

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

open access: yesAdvanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal   +6 more
wiley   +1 more source

Word sense disambiguation for spam filtering

open access: yesElectronic Commerce Research and Applications, 2012
Spam has become a major issue in computer security because it is a channel for threats such as computer viruses, worms, and phishing. More than 86% of received e-mails are spam. Historical approaches to combating these messages, including simple techniques such as sender blacklisting or the use of e-mail signatures, are no longer completely reliable ...
Carlos Laorden   +4 more
openaire   +2 more sources

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

open access: yesAdvanced 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   +4 more
wiley   +1 more source

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