How to Build An Automated Complaint System Using Text Mining Technique
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The problem of increasing the cost and efforts required to manage the complaints manually leads to the need to develop automated solutions to handle this problem by including text-mining techniques to substitute the human part. In this book, we propose a new solution to overcome the manual system limitations that consist of three phases. First, we analyze the text message contents, categorize it by using text categorization algorithms and try to decide where to direct the question request automatically to the right person in order to get it answered. Then, we will use text similarity technique...
The problem of increasing the cost and efforts required to manage the complaints manually leads to the need to develop automated solutions to handle this problem by including text-mining techniques to substitute the human part. In this book, we propose a new solution to overcome the manual system limitations that consist of three phases. First, we analyze the text message contents, categorize it by using text categorization algorithms and try to decide where to direct the question request automatically to the right person in order to get it answered. Then, we will use text similarity techniques to suggest the answers automatically. Finally, the system will use summarization techniques to update the FAQ library with the most asked questions. As a result, the automated complaints system will improve the quality of answering questions by speeding the process and minimizing the required time and effort. Also, the system will be capable to answer questions directly based on the previous similar cases.
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