Results 41 to 50 of about 49,185 (256)

Word Sense Disambiguation by Web Mining for Word Co-occurrence Probabilities

CoRR, 2004
This paper describes the National Research Council (NRC) Word Sense Disambiguation (WSD) system, as applied to the English Lexical Sample (ELS) task in Senseval-3. The NRC system approaches WSD as a classical supervised machine learning problem, using familiar tools such as the Weka machine learning software and Brill's rule-based part-of-speech tagger.
openaire   +5 more sources

Co-occurrence graphs for word sense disambiguation in the biomedical domain [PDF]

Artificial Intelligence in Medicine, 2018
Word sense disambiguation is a key step for many natural language processing tasks (e.g. summarization, text classification, relation extraction) and presents a challenge to any system that aims to process documents from the biomedical domain. In this paper, we present a new graph-based unsupervised technique to address this problem. The knowledge base
Andres Duque Fernandez, Mark Stevenson 0001, Juan Martínez-Romo, Lourdes Araujo   +3 more
openaire   +3 more sources

Soft motions encoded by the fold and mediated by conserved hinge sites drive V‐ATPase allosteric machinery and autoinhibition

FEBS Letters, EarlyView.
Vacuolar H+‐ATPase (V‐ATPase) is a multisubunit rotary proton pump that acidifies intracellular compartments. Using elastic network models, we identified conserved hinge residues that govern its large‐scale functional motions. We show that intrinsically encoded ‘soft modes’ drive critical functional transitions, including rotary catalysis and ...
Diksha Parwana, Xiaowei Bogetti, Stuti Sharma, Ivet Bahar   +3 more
wiley   +1 more source

Predicting co-word links via heterogeneous graph convolutional networks

Scientific Reports
Co-word analysis, which explores the co-occurrence of key terminology within a specific field, is a valuable tool for identifying research themes and their networks.
Yangmin Li, Xin Zhang, Xin Bai, Sen Bai, Zhengang Jiang   +4 more
doaj   +1 more source

Extracting word correspondences from bilingual corpora based on word co-occurrences information [PDF]

Proceedings of the 16th conference on Computational linguistics -, 1996
A new method has been developed for extracting word correspondences from a bilingual corpus. First, the co-occurrence information for each word in both languages is extracted from the corpus. Then, the correlations between the co-occurrence features of the words are calculated pairwisely with the assistance of a basic word bilingual dictionary. Finally,
Hiroyuki Kaji, Toshiko Aizono
openaire   +2 more sources

Attitudes of cancer patients toward ctDNA‐based liquid biopsy for follow‐up

Molecular Oncology, EarlyView.
This mixed‐methods study explored cancer patients' experiences, knowledge, and preferences regarding ctDNA‐based liquid biopsy for follow‐up. Awareness of ctDNA was low and recall of previous liquid biopsy was imperfect, yet acceptance was high.
Siddharth Chhajlani, Laura Mariën, Caro De Weerdt, Sanne Wouters, Laure‐Anne Teuwen, Hans Prenen, Katleen Janssens, Timon Vandamme   +7 more
wiley   +1 more source

Self‐Regulated Learning Meets AI: Reinterpreting Self‐Regulation, Co‐Regulation, and Socially Shared Regulation in Human–AI Interaction

New Directions for Adult and Continuing Education, EarlyView.
ABSTRACT Advancing artificial intelligence (AI) has transformed learning and work, yet higher education and professional development programs have not systematically equipped learners for AI‐prevalent environments. This lack of preparation creates uncertainty regarding control, responsibility, trust, and accountability.
Moon‐Heum Cho, Jerusalem Merkebu
wiley   +1 more source

Analysis and Classification of Word Co-Occurrence Networks From Alzheimer’s Patients and Controls

Frontiers in Computer Science, 2021
In this paper we construct word co-occurrence networks from transcript data of controls and patients with potential Alzheimer’s disease using the ADReSS challenge dataset of spontaneous speech.
Tristan Millington, Saturnino Luz
doaj   +1 more source

Comparing the Effect of Semi‐Immersive Virtual Reality, Computerized Cognitive Training, and Traditional Rehabilitation on Cognitive Function in Multiple Sclerosis: A Randomized Clinical Trial

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Cognitive impairment is a common non‐motor symptom in Multiple Sclerosis (MS), negatively affecting autonomy and Quality of Life (QoL). Innovative rehabilitation strategies, such as semi‐immersive virtual reality (VR) and computerized cognitive training (CCT), may offer advantages over traditional cognitive rehabilitation (TCR ...
Maria Grazia Maggio, Desiree Latella, Lilla Bonanno, Paulo Cezar Rocha dos Santos, Marcos Maldonado‐Díaz, Meir Plotnik, Rosaria De Luca, Angelo Quartarone, Rocco Salvatore Calabrò   +8 more
wiley   +1 more source

Dual-Graph Convolutional Network with Context Fusion for Chinese Sentiment Classification

Information
Existing research on sentiment classification primarily focuses on textual contextual semantics while neglecting word co-occurrence and syntactic structure information.
Lei Bai, Zhenguo Chen
doaj   +1 more source