Text Mining Techniques for Intelligent Grievances Handling System: WECARE Project Improvements in EgyptAir
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2019, Vol 10, Issue 2
Abstract
The current work provides quick responding and minimize the required time of processing of the incoming grievances by using automated categorization that analyses the English text contents and predict the category. This work built a model by text mining and NLP processing to extract the useful information from customer grievances data ,to be used as a guidelines to air transport industry. Since soon , a customer grievances ‘system in EGYPTAIR called WECARE has had large feeds of data which can be collected in data sets through various channels such as e-mail, website or mobile Apps. Then the incoming data sets are analyzed and assessed by organization's staff then it is assigned to related department through manual classification. Finally, it provides proposed solution for the issue. Thence grievances categorization that handled manually is time consuming process. So, this work decided a model to improve WECARE system in Egypt Airlines. Classification based data mining Techniques are used to identify data into groups of categories across the variable touch points. The system has 166 categories of problems, but for experimental purposes we decide to study 6 categories only. We have applied four commonly used classifiers namely, Support Vector Machine (SVM), K-Nearest Neighbours(KNN), Naïve Bayesian and Decision Tree on our data set to classify the grievances data set then selecting the best of them to be the candidate grievances classifier in enhanced WECARE system. Among four classifiers applied on the dataset, KNN achieved the highest average accuracy (97.5% ) with acceptable running time. Also, the work is extended to make hint to the system user, about how to solve this grievance issue based on previous issues saved in Knowledge Base (KB). Several experiments were conducted to test solution hint module by changing similarity score. The benefits of performing a thorough analysis of problems include better understanding of service performance.
Authors and Affiliations
Shahinaz M. Al-Tabbakh, Hanaa M. Mohammed, Hayam A. El- Shrief
Keywords
Related Articles
- EP ID EP468745
- DOI 10.14569/IJACSA.2019.0100275
- Views 106
- Downloads 0
Comparative Study of Bayesian and Energy Detection Including MRC Under Fading Environment in Collaborative Cognitive Radio Network
The most important component of Cognitive Radio Network (CRN) is to sense the underutilised spectrum efficiently in fading environment for incorporating the increasing demand of wireless applications. The result of spect...
A Students Attendance System Using QR Code
Smartphones are becoming more preferred companions to users than desktops or notebooks. Knowing that smartphones are most popular with users at the age around 26, using smartphones to speed up the process of taking atten...
Handsets Malware Threats and Facing Techniques
- Nowadays, mobile handsets combine the functionality of mobile phones and PDAs. Unfortunately, mobile handsets development process has been driven by market demand, focusing on new features and neglecting security...
Task Allocation Model for Rescue Disabled Persons in Disaster Area with Help of Volunteers
In this paper, we present a task allocation model for search and rescue persons with disabilities in case of disaster. The multi agent-based simulation model is used to simulate the rescue process. Volunteers and d...
Negotiation as a Collaborative Tool for Determining Permissions and Detection of Malicious Applications
In Android OS users find it very difficult to understand and comprehend its permission mechanism. Frequently, users tend to ignore permission negotiations dialogs during installation of an application. Users, who pay att...