Results 61 to 70 of about 191,564 (306)

Linguistic Markers of Influence in Informal Interactions

, 2017
There has been a long standing interest in understanding `Social Influence' both in Social Sciences and in Computational Linguistics. In this paper, we present a novel approach to study and measure interpersonal influence in daily interactions. Motivated
Black, Alan W, Bogart, Christopher, Choudhary, Samridhi, Prabhumoye, Shrimai, Rose, Carolyn Penstein, Spiliopoulou, Evangelia   +5 more
core   +1 more source

Recent Advancements in Topic Modeling Techniques for Healthcare, Bioinformatics, and Other Potential Applications

Advanced Intelligent Systems, EarlyView.
This article offers a comprehensive review of topic modeling techniques, tracing their evolution from inception to recent developments. It explores methods such as latent Dirichlet allocation, latent semantic analysis, non‐negative matrix factorization, probabilistic latent semantic analysis, Top2Vec, and BERTopic, highlighting their strengths ...
Pratima Kumari, Sachin Kadian, Mukund Vora, Pradyumna Vemuri, Sumit Kumar, Om Prakash Verma, Roger J. Narayan   +6 more
wiley   +1 more source

Parallel Multimodal Language Model: Enhanced Breast Nodule Diagnosis through Parallel Multimodal Representations and Large Language Models

Advanced Intelligent Systems, EarlyView.
This study introduces the Parallel Multimodal Language Model (PMLM), a multimodal diagnostic framework that integrates medical images and textual data to enhance early breast cancer detection. By addressing the limitations of text‐only large language models, PMLM significantly improves diagnostic performance.
Dashun Zheng, Patrick Cheong‐Iao Pang, Ping He, Yue Sun, Hongju Yan, Xiangyu Xiong, Ligang Cui, Tao Tan, Lingyun Bao   +8 more
wiley   +1 more source

Towards authentic tasks and experiences: The example of parser-based CALL

Canadian Journal of Applied Linguistics, 2000
Authenticity of language learning tasks, authenticity of learning experiences and the use of authentic language are important characteristics of communicative language teaching and learning.
Mathias Schulze, Marie-Josée Hamel
doaj  

COMPUTATIONAL LINGUISTICS AND ARTIFICIAL INTELLIGENCE [PDF]

Ziglôbitha
: Computational linguistics, as an interdisciplinary field combining linguistics and computer science, aims to enable computers to process natural language.
Affas MAAMAR & Hadjer HADJCHERIF
doaj   +1 more source

Documentary Linguistics and Computational Linguistics: A response to Brooks [PDF]

, 2015
National Foreign Language Resource ...
Bird, Steven, Chiang, David, Frowein, Friedel, Hanke, Florian, Vaswani, Ashish   +4 more
core  

From Droplet to Diagnosis: Spatio‐Temporal Pattern Recognition in Drying Biofluids

Advanced Intelligent Systems, EarlyView.
This article integrates machine learning (ML) with the spatio‐temporal evolution of biofluid droplets to reveal how drying and self‐assembly encode distinctive compositional fingerprints. By leveraging textural features and interpretable ML, it achieves robust classification of blood abnormalities with over 95% accuracy.
Anusuya Pal, Amalesh Gope, Miho Yanagisawa   +2 more
wiley   +1 more source

Evaluating Richer Features and Varied Machine Learning Models for Subjectivity Classification of Book Review Sentences in Portuguese

Information, 2020
Texts published on social media have been a valuable source of information for companies and users, as the analysis of this data helps improving/selecting products and services of interest.
Luana Balador Belisário, Luiz Gabriel Ferreira, Thiago Alexandre Salgueiro Pardo   +2 more
doaj   +1 more source

Medieval Irish and computational linguistics [PDF]

, 2012
This paper will consider the application of some NLP (Natural Language Processing) techniques to Medieval Irish texts to provide an alternative perspective on linguistic analyses of such texts.
Lynn, Teresa
core  

Parsing Argumentation Structures in Persuasive Essays

, 2016
In this article, we present a novel approach for parsing argumentation structures. We identify argument components using sequence labeling at the token level and apply a new joint model for detecting argumentation structures.
Gurevych, Iryna, Stab, Christian
core   +1 more source