Rapid Text Retrieval and Analysis Supporting Latent Dirichlet Allocation Based on Probabilistic Models

Text mining, also known as text analysis, is the process of converting unstructured text data into meaningful and functional information. Text mining uses different AI technologies to automate data and generate valuable insights, allowing enterprises to make data-based decisions. Text mining enables...

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Bibliographic Details
Published in:Mobile information systems 2022-08, Vol.2022, p.1-12
Main Authors: Gnanavel, S., Mani, Vinodhini, Sreekrishna, M., Amshavalli, R. S., Reta Gashu, Yomiyu, Duraimurugan, N., Srinivasa Rao, Namburi
Format: Article
Language:English
Subjects:
Algorithms
Big Data
Blockchain
Clustering
Communication
Data analysis
Data mining
Data models
Data processing
Datasets
Dirichlet problem
E-books
Libraries
Machine learning
Medical research
Natural language processing
Optimization techniques
Probabilistic models
Search engines
Semantics
Sentiment analysis
Social networks
Social research
Structured data
Text analysis
Unstructured data
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Summary:Text mining, also known as text analysis, is the process of converting unstructured text data into meaningful and functional information. Text mining uses different AI technologies to automate data and generate valuable insights, allowing enterprises to make data-based decisions. Text mining enables the user to extract important content from text data sets. Text analysis encourages machine learning ability for research areas such as medical and pharmaceutical innovation fields. Apart from this, text analysis converts inaccessible data into a structured format, which can be used for further analysis. Text analysis emphasizes facts and relationships from large data sets. This information is extracted and converted into structured data for visualization, analysis, and integration as structured data and refines the information using machine-learning methods. Like most things related to Natural Language Processing, text mining can seem like a difficult concept to understand. But the fact is, it does not have to be. This research article will go through the basics of text mining, clarify its different methods and techniques, and make it easier to understand how it works. We implemented Latent Dirichlet Allocation techniques for mining the data from the data set; it works properly and will be in future development data mining techniques.
ISSN:1574-017X
1875-905X
DOI:10.1155/2022/6028739