The application of data and text analysis in understanding and improving the service: A case study based on Operational Research conference
Machine learning plays a significant role in managing business organisations since it can utilise the data from customer feedback and have a better understanding about customers’ perceptions on the organisations by analysing the data. This research is carried out to find out how machine learning can...
| Main Author: | |
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| Format: | Dissertation (University of Nottingham only) |
| Language: | English |
| Published: |
2019
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| Online Access: | https://eprints.nottingham.ac.uk/58719/ |
| _version_ | 1848799559986184192 |
|---|---|
| author | Feng, Yue |
| author_facet | Feng, Yue |
| author_sort | Feng, Yue |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Machine learning plays a significant role in managing business organisations since it can utilise the data from customer feedback and have a better understanding about customers’ perceptions on the organisations by analysing the data. This research is carried out to find out how machine learning can assist to analyse the data from customer feedback and give some suggestions on how to improve the quality of the Operational Research Conference. The data is collected from five OR annual conference questionnaires, including OR 54, OR 55, OR 56, OR 58 and OR 59. In data mining part, some basic rating information will be presented to show delegates’ satisfaction on different aspects of the conference. Specifically, the data shows that there is a decreasing trend on the average overall score across five years. Then, use Random forest classification to find out the most important variables that will influence the overall score of the conference, which give information about which aspects to focus on for the organisers of this annual conference. In the text mining part, several text mining algorithms are utilised to analyse the reviews given by the delegates in order to give the organisers some useful ideas on how to improve the conference. Finally; the results from these two parts will be combined to explain the reasons why the average overall score is decreasing every year along with some improvement suggestions. |
| first_indexed | 2025-11-14T20:37:36Z |
| format | Dissertation (University of Nottingham only) |
| id | nottingham-58719 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T20:37:36Z |
| publishDate | 2019 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-587192022-12-08T15:54:27Z https://eprints.nottingham.ac.uk/58719/ The application of data and text analysis in understanding and improving the service: A case study based on Operational Research conference Feng, Yue Machine learning plays a significant role in managing business organisations since it can utilise the data from customer feedback and have a better understanding about customers’ perceptions on the organisations by analysing the data. This research is carried out to find out how machine learning can assist to analyse the data from customer feedback and give some suggestions on how to improve the quality of the Operational Research Conference. The data is collected from five OR annual conference questionnaires, including OR 54, OR 55, OR 56, OR 58 and OR 59. In data mining part, some basic rating information will be presented to show delegates’ satisfaction on different aspects of the conference. Specifically, the data shows that there is a decreasing trend on the average overall score across five years. Then, use Random forest classification to find out the most important variables that will influence the overall score of the conference, which give information about which aspects to focus on for the organisers of this annual conference. In the text mining part, several text mining algorithms are utilised to analyse the reviews given by the delegates in order to give the organisers some useful ideas on how to improve the conference. Finally; the results from these two parts will be combined to explain the reasons why the average overall score is decreasing every year along with some improvement suggestions. 2019-12-01 Dissertation (University of Nottingham only) NonPeerReviewed application/pdf en https://eprints.nottingham.ac.uk/58719/1/Yue%20Feng%20dissertation%2014317421.pdf Feng, Yue (2019) The application of data and text analysis in understanding and improving the service: A case study based on Operational Research conference. [Dissertation (University of Nottingham only)] |
| spellingShingle | Feng, Yue The application of data and text analysis in understanding and improving the service: A case study based on Operational Research conference |
| title | The application of data and text analysis in understanding and improving the service:
A case study based on Operational Research conference |
| title_full | The application of data and text analysis in understanding and improving the service:
A case study based on Operational Research conference |
| title_fullStr | The application of data and text analysis in understanding and improving the service:
A case study based on Operational Research conference |
| title_full_unstemmed | The application of data and text analysis in understanding and improving the service:
A case study based on Operational Research conference |
| title_short | The application of data and text analysis in understanding and improving the service:
A case study based on Operational Research conference |
| title_sort | application of data and text analysis in understanding and improving the service:
a case study based on operational research conference |
| url | https://eprints.nottingham.ac.uk/58719/ |