Results 51 to 60 of about 52,118 (285)
CoRR, 2016 In order to create a corpus exploration method providing topics that are easier to interpret than standard LDA topic models, here we propose combining two techniques called Entity linking and Labeled LDA. Our method identifies in an ontology a series of descriptive labels for each document in a corpus. Then it generates a specific topic for each label.
Nanni, Federico, Ruiz Fabo, Pablo
openaire +4 more sources
, 2021 Replication data and code for Transfer Learning for Topic Labeling: Analysis of the UK House of Commons Speeches 1935-2014 .
Herzog, Alexander +3 more
core +2 more sources
Unsupervised Topic Labeling of Text Based on Wikipedia Categorization [PDF]
Journal of Systemics, Cybernetics and Informatics, 2019 Defining text topicality is often an expensive problem that requires significant resources for text labeling. Though many packages already exist that provide dictionaries of labeled text, synonyms, and Part-of-Speach tagging, the problem is ongoing as ...
Tetyana Loskutova
doaj
Fluorine-18: Radiochemistry and Target-Specific PET Molecular Probes Design
Frontiers in Chemistry, 2022 The positron emission tomography (PET) molecular imaging technology has gained universal value as a critical tool for assessing biological and biochemical processes in living subjects.
Yunze Wang +11 more
doaj +1 more source
Ground Truth Data Generator for Eye Location on Infrared Driver Recordings
Journal of Imaging, 2021 Labeling is a very costly and time consuming process that aims to generate datasets for training neural networks in several functionalities and projects.
Sorin Valcan, Mihail Gaianu
doaj +1 more source
Automatic Labelling of Topics with Neural Embeddings
CoRR, 2016 11 pages, 3 figures, published in ...
Shraey Bhatia +2 more
openaire +3 more sources
A Knowledge-Based Topic Modeling Approach for Automatic Topic Labeling
, 2017 Probabilistic topic models, which aim to discover latent topics in text corpora define each document as a multinomial distributions over topics and each topic as a multinomial distributions over words.
Pouriyeh, Seyedamin +7 more
core +1 more source
Topic Segmentation and Labeling in Asynchronous Conversations
Journal of Artificial Intelligence Research, 2013 Topic segmentation and labeling is often considered a prerequisite for higher-level conversation analysis and has been shown to be useful in many Natural Language Processing (NLP) applications. We present two new corpora of email and blog conversations annotated with topics, and evaluate annotator reliability for the segmentation and labeling tasks in ...
Shafiq Rayhan Joty +2 more
openaire +3 more sources
Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Objective To compare the efficacy and safety of roxarestat versus recombinant human erythropoietin (rhEPO) in the management of renal anemia in patients undergoing maintenance hemodialysis. Methods This was a prospective, open‐label, randomized controlled trial.
Lingling Chen, Junjie Zhu, Qiaonan Ge
wiley +1 more source
Topic Model or Topic Twaddle? Re-evaluating Semantic Interpretability Measures [PDF]
, 2021 When developing topic models, a critical question that should be asked is: How well will this model work in an applied setting? Because standard performance evaluation of topic interpretability uses automated measures modeled on human evaluation tests ...
Buntine, Wray +3 more
core +1 more source