Utilizing Deep Learning Techniques for Text and Image Capturing Summarization in Information Retrievals

Authors

  • Dr. S. Selvakani  Assistant Professor and Head, PG Department of Computer Science, Government Arts and Science College, Arakkonam, Tamil Nadu, India
  • Mrs K. Vasumathi  Assistant Professor, PG Department of Computer Science, Government Arts and Science College, Arakkonam, Tamil Nadu, India
  • S. Divya  PG Scholar, PG Department of Computer Science, Government Arts and Science College, Arakkonam, Tamil Nadu, India

DOI:

https://doi.org/10.32628/CSEIT2390218

Keywords:

Semantics, Information retrieval, Feature extraction, Data mining, Deep learning, Task analysis.

Abstract

In this paper, a novel information retrieval and text summarization model based on deep learning (DL) is introduced. The model comprises three primary stages, including information retrieval, template generation, and text summarization. The initial step involves utilizing a bidirectional long short term memory (BiLSTM) technique to retrieve textual data. This approach considers each word in a sentence, extracts relevant information, and converts it into a semantic vector.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2023-04-30

Issue

Volume 9, Issue 2, March-April-2023

Section

Research Articles

License

Copyright (c) IJSRCSEIT

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Dr. S. Selvakani, Mrs K. Vasumathi, S. Divya, " Utilizing Deep Learning Techniques for Text and Image Capturing Summarization in Information Retrievals" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 9, Issue 2, pp.202-207, March-April-2023. Available at doi : https://doi.org/10.32628/CSEIT2390218