Abstract
Understanding customer's sentiment (satisfaction or dissatisfaction) is considered as valuable information for both the potential customers and restaurant authority. However, analyzing customer reviews (unstructured texts) one by one is a difficult task and also practically impossible when the number of reviews is enormous. Therefore, it seems conceivable to have a mechanism to analyze customer reviews automatically and provide the necessary information in a precise way. Here, we introduce a Natural Language Processing (NLP) based opinion mining methodology to analyze the customer opinion automatically. For that, first, a captive portal is used to collect customer's reviews. Then, the opinion mining technique is applied to analyze the reviews to explore customer sentiment about food quality, service, environment, etc. A data-driven experiment is conducted to evaluate the proposed methodology. The experiment result showed the effectiveness of the proposed method for retrieving and analyzing customer sentiment.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of 2020 IEEE Region 10 Symposium, TENSYMP 2020 |
| Place of Publication | Bangladesh |
| Publisher | IEEE, Institute of Electrical and Electronics Engineers |
| Pages | 295-299 |
| Number of pages | 5 |
| Edition | 1st |
| ISBN (Electronic) | 9781728173665 |
| DOIs | |
| Publication status | Published - 5 Jun 2020 |
| Externally published | Yes |
| Event | IEEE Region 10 Symposium 2020 - Virtual/Online, Dhaka, Bangladesh Duration: 5 Jun 2020 → 7 Jun 2020 https://ieeexplore.ieee.org/xpl/conhome/9230456/proceeding |
Conference
| Conference | IEEE Region 10 Symposium 2020 |
|---|---|
| Abbreviated title | TENSYMP 2020 |
| Country/Territory | Bangladesh |
| City | Dhaka |
| Period | 5/06/20 → 7/06/20 |
| Internet address |
Keywords
- captive portal
- customer opinion
- lexical analysis
- opinion mining
- sentiment analysis