Optimized bidirectional convolutional recurrent neural network architecture with group-wise enhancement mechanism of sentiments for the perspective of customer review summarization (Record no. 22708)
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| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250424113014.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 250424b xxu||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | AIKTC-KRRC |
| Transcribing agency | AIKTC-KRRC |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| 9 (RLIN) | 25975 |
| Author | Sriguru, V. |
| 245 ## - TITLE STATEMENT | |
| Title | Optimized bidirectional convolutional recurrent neural network architecture with group-wise enhancement mechanism of sentiments for the perspective of customer review summarization |
| 250 ## - EDITION STATEMENT | |
| Volume, Issue number | Vol.15(2), Oct |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Chennai |
| Name of publisher, distributor, etc. | ICT Academy |
| Year | 2024 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Pagination | 3523-3531p. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Customer reviews play pivotal roles in consumers’ purchase decisions,<br/>but the sheer volume of text data can be overwhelming. In existing<br/>system, while ensemble methods can enhance performance, the<br/>associated computational complexity and resource intensiveness<br/>should be carefully considered, and appropriate measures should be<br/>taken to address these challenges in the context of Customer Review<br/>Summarization. This study introduces a Particle Swarm Optimization<br/>(PSO) based optimized architecture for a Bidirectional Convolutional<br/>Recurrent Neural Network (BiCRNN) with a group-wise enhancement<br/>mechanism tailored for Customer Review Summarization and named<br/>as OBiCRNN. This model is designed for the perspective of customer<br/>review summarization, aiming to effectively capture sentiments and<br/>generate concise summaries. The integration of PSO optimizes the<br/>network parameters, enhancing the learning process. Feature<br/>extraction is done by Modified Principal Component Analysis (MPCA)<br/>which uses correlated feature sets and extracts most informative<br/>features for given datasets. BiCRNN utilizes bidirectional LSTM and<br/>GRU layers for comprehensive context understanding, while the group-<br/>wise enhancement mechanism categorizes sentiment-related features,<br/>amplifying essential sentiments and attenuating less relevant ones.<br/>With this novel approach, the architecture leverages both PSO and<br/>BiCRNN for an advanced framework in customer review<br/>summarization where outcomes demonstrate the effectiveness of the<br/>deep learning (DL) model in producing coherent and informative<br/>summaries, enhancing the accessibility of customer feedback for both<br/>consumers and businesses. The study contributes to the field of natural<br/>language processing (NLP) and customer sentiment analysis, offering<br/>a scalable solution for managing the wealth of information present in<br/>online customer reviews. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| 9 (RLIN) | 4622 |
| Topical term or geographic name entry element | Computer Engineering |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| 9 (RLIN) | 25976 |
| Co-Author | Shanmuga Rajathi, D. |
| 773 0# - HOST ITEM ENTRY | |
| Place, publisher, and date of publication | Chennai ICT Academy |
| Title | ICTACT Journal on Soft Computing (IJSC) |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| URL | https://ictactjournals.in/paper/IJSC_Vol_15_Iss_2_Paper_7_3523_3531.pdf |
| Link text | Click here |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | Articles Abstract Database |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Home library | Current library | Shelving location | Date acquired | Total Checkouts | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | School of Engineering & Technology | School of Engineering & Technology | Archieval Section | 24/04/2025 | 2025-0657 | 24/04/2025 | 24/04/2025 | Articles Abstract Database |