Leveraging Multiple Representations of Topic Models for Knowledge Discovery

Leveraging Multiple Representations of Topic Models for Knowledge Discovery

Topic models are often useful in categorization of related documents in information retrieval and knowledge discovery systems, especially for large datasets. Interpreting the output of these models remains an ongoing challenge for the research community. The typical practice in the application of to...

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Bibliographic Details
Main Authors: Colin M. Potts, Akshat Savaliya, Arnav Jhala
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Artificial intelligence
big data applications
data analysis
data visualization
knowledge discovery
natural language processing
Online Access:https://ieeexplore.ieee.org/document/9905590/

Internet

https://ieeexplore.ieee.org/document/9905590/

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