Development of a Web Application for Intelligent Analysis of Customer Reviews Using a Modified seq2seq Model with an Attention Mechanism
( Pp. 151-161)
More about authors
Budaev Evgeny S.
Cand. Sci. (Eng.), Associate Professor; associate professor, Department of Data Analysis and Machine Learning, Faculty of Information Technology and Big Data Anlysis
Financial University under the Government of the Russian Federation
Moscow, Russian Federation
Financial University under the Government of the Russian Federation
Moscow, Russian Federation
Abstract:
Machine learning, and neural networks in particular, are having a huge impact on business and marketing by providing convenient tools for analytics and customer feedback. The article proposes an intelligent analysis of customer feedback based on the use of a modified seq2seq deep learning model. Since the basic seq2seq model has a significant disadvantage – the inability to concentrate on the main parts of the input sequence, the results of machine learning may give an inadequate assessment of customer feedback. This disadvantage is eliminated by means of a model proposed in the work called the “attention mechanism”. The model formed the basis for the development of a web application that solves the problem of flexible interaction with customers by parsing new reviews, analyzing them and generating a response to a review using a neural network.
How to Cite:
Budaev E.S. Development of a Web Application for Intelligent Analysis of Customer Reviews Using a Modified seq2seq Model with an Attention Mechanism. Computational Nanotechnology. 2024. Vol. 11. No. 1. Pp. 151–161. (In Rus.) DOI: 10.33693/2313-223X-2024-11-1-151-161. EDN: ELOCZJ
Reference list:
Labintsev A., Khasanshin I., Balashov D. et al. Recognition Punches in Karate Using Acceleration Sensors and Convolution Neural Networks. IEEE Access. 2021. Vol. 9. Pp. 138106-138119. DOI: 10.1109/ACCESS.2021.3118038.
Dipankar Das, Anup Kumar Kolya, Abhishek Basu, Soham Sarkar. Computational intelligence applications for text and sentiment data analysis. Academic Press, 2023. P. 252. ISBN: 9780323905350. DOI: 10.1016/B978-0-32-390535-0.00007-0.
Gated recurrent unit networks: Efficient neural architecture for sequential data. URL: https://askanydifference.com/gated-recurrent-unit-networks/ (data of accesses: 14.12.2023).
LSTM и GRU. URL: https://habr.com/ru/companies/mvideo/articles/780774/ (data of accesses: 03.12.2023).
NLP from scratch: machine translation using seq2seq with the attention mechanism. URL: https://pytorch.org/tutorials/intermediate/seq2seq_translation_tutorial.html#loading-data-files (date of application: 12/01/2023).
Sansano E., Montoliu R., Belmonte Fernández Ó. A study of deep neural networks for human activity recognition. Computational Intelligence. 2020. No. 36. Pp. 1113–1139. DOI: 10.1111/coin.12318.
Shahriar Akter, Saradhi Motamarri, Umme Hani. et al. Building dynamic service analytics capabilities for the digital marketplace. Journal of Business Research. 2020. Vol. 118. Pp. 177–188. ISSN: 0148-2963. DOI: 10.1016/j.jbusres.2020.06.016.
Introduction to Text Mining and preprocessing of text data. URL: https://nagornyy.me/it/vvedenie-v-text-mining-i-predvaritelnaia-obrabotka-tekstovykh-dannykh / (data of accesses: 05.12.2023).
Introduction to deep learning: a step-by-step guide. URL: https://pythonist.ru/vvedenie-v-glubokoe-obuchenie-po-shagam/? (data of accesses: 02.12.2023).
Visualizing neural machine translation (seq2seq models with an attention mechanism). URL: https://habr.com/ru/post/486158/ (data of accesses: 03.12.2023).
How to display a product card in the top on Wildberries. URL: https://ritm-z.ru/blog/Ritm-Z/kak-vyvesti-kartochku-tovara-v-top-na-wildberries/ (data of accesses: 02.12.2023).
Makarova E.S., Budaev E.S. Intelligent analysis of customer reviews using the seq2seq model. Internauka: Electron. Scientific Journal. 2022. No. 22 (245). URL: https://internauka.org/journal/science/internauka/245 (data of accesses: 14.12.2023). DOI: 10.32743/26870142.2022.22.245.342556
Marketplaces: definition, types, sites. URL: https://investprofit.info/marketplace/? (data of accesses: 02.12.2023).
Mechanism of attention. URL: https://neerc.ifmo.ru/wiki/index.php?title=Mechanism_of_attention (data of accesses: 12/16/2023).
Models of deep neural networks sequence-to-sequence on PyTorch. URL: https://habr.com/ru/post/567142/ (data of accesses: 12/17/2023).
Recurrent GRU blocks. An example of their implementation in the task of sentiment analysis. URL: https://proproprogs.ru/neural_network/rekurrentnye-bloki-gru-primer-realizacii-v-zadache-sentiment-analiza? (data of accesses: 14.12.2023).
Dipankar Das, Anup Kumar Kolya, Abhishek Basu, Soham Sarkar. Computational intelligence applications for text and sentiment data analysis. Academic Press, 2023. P. 252. ISBN: 9780323905350. DOI: 10.1016/B978-0-32-390535-0.00007-0.
Gated recurrent unit networks: Efficient neural architecture for sequential data. URL: https://askanydifference.com/gated-recurrent-unit-networks/ (data of accesses: 14.12.2023).
LSTM и GRU. URL: https://habr.com/ru/companies/mvideo/articles/780774/ (data of accesses: 03.12.2023).
NLP from scratch: machine translation using seq2seq with the attention mechanism. URL: https://pytorch.org/tutorials/intermediate/seq2seq_translation_tutorial.html#loading-data-files (date of application: 12/01/2023).
Sansano E., Montoliu R., Belmonte Fernández Ó. A study of deep neural networks for human activity recognition. Computational Intelligence. 2020. No. 36. Pp. 1113–1139. DOI: 10.1111/coin.12318.
Shahriar Akter, Saradhi Motamarri, Umme Hani. et al. Building dynamic service analytics capabilities for the digital marketplace. Journal of Business Research. 2020. Vol. 118. Pp. 177–188. ISSN: 0148-2963. DOI: 10.1016/j.jbusres.2020.06.016.
Introduction to Text Mining and preprocessing of text data. URL: https://nagornyy.me/it/vvedenie-v-text-mining-i-predvaritelnaia-obrabotka-tekstovykh-dannykh / (data of accesses: 05.12.2023).
Introduction to deep learning: a step-by-step guide. URL: https://pythonist.ru/vvedenie-v-glubokoe-obuchenie-po-shagam/? (data of accesses: 02.12.2023).
Visualizing neural machine translation (seq2seq models with an attention mechanism). URL: https://habr.com/ru/post/486158/ (data of accesses: 03.12.2023).
How to display a product card in the top on Wildberries. URL: https://ritm-z.ru/blog/Ritm-Z/kak-vyvesti-kartochku-tovara-v-top-na-wildberries/ (data of accesses: 02.12.2023).
Makarova E.S., Budaev E.S. Intelligent analysis of customer reviews using the seq2seq model. Internauka: Electron. Scientific Journal. 2022. No. 22 (245). URL: https://internauka.org/journal/science/internauka/245 (data of accesses: 14.12.2023). DOI: 10.32743/26870142.2022.22.245.342556
Marketplaces: definition, types, sites. URL: https://investprofit.info/marketplace/? (data of accesses: 02.12.2023).
Mechanism of attention. URL: https://neerc.ifmo.ru/wiki/index.php?title=Mechanism_of_attention (data of accesses: 12/16/2023).
Models of deep neural networks sequence-to-sequence on PyTorch. URL: https://habr.com/ru/post/567142/ (data of accesses: 12/17/2023).
Recurrent GRU blocks. An example of their implementation in the task of sentiment analysis. URL: https://proproprogs.ru/neural_network/rekurrentnye-bloki-gru-primer-realizacii-v-zadache-sentiment-analiza? (data of accesses: 14.12.2023).
Keywords:
intelligent analysis, marketing, seq2seq model, artificial neural network, web application.
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