Results 11 to 20 of about 52,118 (285)
Advanced Hierarchical Topic Labeling for Short Text
IEEE Access, 2023 Hierarchical Topic Modeling is the probabilistic approach for discovering latent topics distributed hierarchically among the documents. The distributed topics are represented with the respective topic terms.
Paras Tiwari +3 more
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Transfer learning for topic labeling: Analysis of the UK House of Commons speeches 1935–2014 [PDF]
Research & Politics, 2021 Topic models are widely used in natural language processing, allowing researchers to estimate the underlying themes in a collection of documents. Most topic models require the additional step of attaching meaningful labels to estimated topics, a process ...
Hannah Béchara +3 more
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Systematic Literature Review of Topic Labeling
IEEE AccessThe rapid growth of textual data on the web has led researchers to develop methods in Natural Language Processing (NLP) to process, understand, and identify topics.
Salma Mekaoui +3 more
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Zero-Shot Topic Labeling for Hazard Classification
Information, 2022 Topic classification is the task of mapping text onto a set of meaningful labels known beforehand. This scenario is very common both in academia and industry whenever there is the need of categorizing a big corpus of documents according to set custom ...
Andrea Rondinelli +2 more
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A New Sentence-Based Interpretative Topic Modeling and Automatic Topic Labeling [PDF]
Symmetry, 2021 This article presents a new conceptual approach for the interpretative topic modeling problem. It uses sentences as basic units of analysis, instead of words or n-grams, which are commonly used in the standard approaches.The proposed approach’s specifics
Rustam Mussabayev, Nenad Mladenovic
exaly +3 more sources
Survey of Automatic Labeling Methods for Topic Models [PDF]
Jisuanji kexue yu tansuo, 2023 Topic models are often used in modeling unstructured corpora and discrete data to extract the latent topic. As topics are generally expressed in the form of word lists, it is usually difficult for users to understand the meanings of topics, especially ...
HE Dongbin, TAO Sha, ZHU Yanhong, REN Yanzhao, CHU Yunxia
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AUTOMATIC TOPIC SEGMENTATION AND LABELING IN MULTIPARTY DIALOGUE [PDF]
2006 IEEE Spoken Language Technology Workshop, 2006 This study concerns how to segment a scenario-driven multiparty dialogue and how to label these segments automatically. We apply approaches that have been proposed for identifying topic boundaries at a coarser level to the problem of identifying agenda ...
Johanna Moore, Johanna D Moore
exaly +6 more sources
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 +1 more
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Topic Models and Fusion Methods: a Union to Improve Text Clustering and Cluster Labeling [PDF]
International Journal of Interactive Multimedia and Artificial Intelligence, 2019 Topic modeling algorithms are statistical methods that aim to discover the topics running through the text documents. Using topic models in machine learning and text mining is popular due to its applicability in inferring the latent topic structure of a ...
Mohsen Pourvali +2 more
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Developing Automatic-Labeled Topic Modeling Based on SAO Structure for Technology Analysis. [PDF]
PLoS ONETopic modeling has become essential for identifying emerging technology trends, detecting technological concepts, and forecasting advancements. This study introduces a subject-action-object (SAO) based approach to overcome the limitations of existing ...
Minyoung Park, Sunhye Kim, Byungun Yoon
doaj +2 more sources