Results 41 to 50 of about 187,791 (308)

TLATR: Automatic Topic Labeling Using Automatic (Domain-Specific) Term Recognition

IEEE Access, 2021
Topic modeling is a probabilistic graphical model for discovering latent topics in text corpora by using multinomial distributions of topics over words. Topic labeling is used to assign meaningful labels for the discovered topics.
Ciprian-Octavian Truica, Elena-Simona Apostol   +1 more
doaj   +1 more source

Topic-Weighted Kernels: Text Kernels Integrating Topic Weights and Deep Word Embeddings for Semantic Text Analytics

IEEE Access
Traditional text classification models, such as text kernels, primarily consider the syntactic aspects of text data. This paper introduces Topic-Weighted Kernels, a new text analytics framework that combines global topical themes with word-level ...
Nikhil V. Chandran, V. S. Anoop, S. Asharaf   +2 more
doaj   +1 more source

Normalized Datasets of Harnack’s Reconstruction of Marcion’s 'Gospel'

Journal of Open Humanities Data, 2021
These two datasets are the first born-digital, normalized, peer-reviewed datasets of Harnack’s classic reconstruction of Marcion’s 'Gospel'. The first consists of human-readable postclassical Greek, the second of lemmatized and morphologically tagged ...
Mark G. Bilby
doaj   +1 more source

Topic-Conversation Relevance (TCR) Dataset and Benchmarks

Advances in Neural Information Processing Systems 37
To be published in 38th Conference on Neural Information Processing Systems (NeurIPS 2024) Track on Datasets and ...
Yaran Fan, Jamie Pool, Senja Filipi, Ross Cutler   +3 more
openaire   +3 more sources

Guidelines for Pediatric Radiotherapy Simulation: A Report From the Children's Oncology Group Radiation Oncology Discipline

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Pediatric radiation therapy presents unique challenges compared to adult treatments, including those of immobilization, potential need for sedation, and the critical importance of accurate, reproducible positioning. Additionally, heightened attention to imaging doses is necessary to minimize long‐term toxicity in survivors.
Parham Alaei, Stephen Mihalcik, Sujith Baliga, Young Kwok, Dana Casey, Eric Ehler, Christiane Burton, John C. Breneman, Daphne A. Haas‐Kogan, Suzanne L. Wolden, Arnold C. Paulino, Nadia N. Laack, Natia Esiashvili, Sarah Milgrom, Christine Hill‐Kayser, Thomas J. Fitzgerald, John A. Kalapurakal, Chia‐Ho Hua   +17 more
wiley   +1 more source

Concept Extraction and Clustering for Topic Digital Library Construction [PDF]

, 2008
This paper is to introduce a new approach to build topic digital library using concept extraction and document clustering. Firstly, documents in a special domain are automatically produced by document classification approach.
Dan, Wu, Chengzhi, Zhang
core  

Multilingual Dynamic Topic Model [PDF]

, 2019
Dynamic topic models (DTMs) capture the evolution of topics and trends in time series data. Current DTMs are applicable only to monolingual datasets.
Elaine Zosa, Mark Granroth-Wilding, Granroth-Wilding, Mark, Zosa , Elaine, Zosa, Elaine   +4 more
core   +1 more source

Topic Detection and Tracking Based on Event Ontology

IEEE Access, 2020
In recent years, Topic Detection and Tracking (TDT) has served as a core technology for searching, organizing and structuring news oriented textual materials from a variety of internet news and social media. The biggest challenges of TDT are the sparsity
Wei Liu, Lei Jiang, Yusen Wu, Tingting Tang, Weimin Li   +4 more
doaj   +1 more source

Multilingual Topic Classification in X: Dataset and Analysis

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
In the dynamic realm of social media, diverse topics are discussed daily, transcending linguistic boundaries. However, the complexities of understanding and categorising this content across various languages remain an important challenge with traditional techniques like topic modelling often struggling to accommodate this multilingual diversity.
Dimosthenis Antypas, Asahi Ushio, Francesco Barbieri, José Camacho-Collados   +3 more
openaire   +2 more sources

Topic modeling for cluster analysis of large biological and medical datasets [PDF]

BMC Bioinformatics, 2014
The big data moniker is nowhere better deserved than to describe the ever-increasing prodigiousness and complexity of biological and medical datasets. New methods are needed to generate and test hypotheses, foster biological interpretation, and build validated predictors.
Weizhong Zhao, Wen Zou, James J. Chen
openaire   +2 more sources