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Aspect-Based Sentiment Analysis for Odisha's Eco-Retreat Center
Details
In the sustainable global goals, economic growth is one of the major challenges faced by any part of the world. Odisha, one of the developing eastern state of India, has many well-known tourist places which can contribute to revenue generation and economic growth. Recently, its government has planned to make some tourist places as "eco-retreat centers" which can attract more tourist to these places. To achieve this objective, the tourist feedback must be analyzed thoroughly which will enhance both quality of service and growth in tourism sector. In this context, an aspect-based sentiment analysis framework is proposed based on Google map reviews given by tourists on Konark tourist spot. Initially, the online reviews are scrapped using Selenium. Then a transfer learning method is proposed utilizing and fine tuning BERT model. The performance is compared with other state-of-the-art models. Further, to enhance the reviews scrapping speed, an Incremental Review Aggregator (IRA) algorithm is proposed. Prompt engineering and few-shot learning with GPT3 is also proposed for better understanding of the aspects. Finally, a web-based application is developed to automate the tasks.
Autorentext
Dr. Niranjan Panigrahi has completed his M.Tech in Computer Science & Engineering from NIT, Rourkela, India in the year 2009 and Ph.D. from NIT, Rourkela, India in the year 2017. Presently, He is working as an assistant professor in the department of CSE, Parala Maharaja Engineering College, Berhampur, Odisha.
Weitere Informationen
- Allgemeine Informationen
- Sprache Englisch
- Anzahl Seiten 52
- Herausgeber LAP LAMBERT Academic Publishing
- Gewicht 96g
- Untertitel A Case Study on Konark
- Autor Niranjan Panigrahi , Sudhanshu Kumar , Pratyush Parida
- Titel Aspect-Based Sentiment Analysis for Odisha's Eco-Retreat Center
- Veröffentlichung 09.04.2024
- ISBN 6207484231
- Format Kartonierter Einband
- EAN 9786207484232
- Jahr 2024
- Größe H220mm x B150mm x T4mm
- GTIN 09786207484232