This work presents a study related to the methods of text mining applications, more specifically, data clustering, in call center's databases, whose texts are in the Portuguese language. The main objective is to identify new and useful knowledge, based on customers' claims. Through the information agreement, it will be possible to identify better ways to help the customer, increasing their satisfaction with company services as well as supplying the call center staff and other related areas with a set of procedures and information concerning the most common customers questions.
This paper describes the development and implementation of a practical and efficient methodology to construct a knowledge extraction environment that contemplates the search of information from Portuguese language Web sites. The application includes some text mining facilities, such as similarity and difference identification between pages and sites, content classification and document clustering.The application conception has its origin on the evaluation environment of competitive intelligence tasks over the Web. The increasing availability of information in the Web has motivated the proposal of an environment that presents the solutions in an integrated form, supplying results analysis according to the user indication.
The objective of this paper is to present a database marketing analysis through data and text mining tools. A case study of a Brazilian Power Energy distribution was developed indoors. The main idea is to transform the database information into strategic marketing knowledge. Thus a data warehouse sample was treated, reduced and clustered. Principal component analysis was used to reduce the original number of variables. The entire database was classified after creation by the decision trees and neural networks approach. In this work, text mining techniques were used to process customers' claims in order to improve cluster results. The CRM group has developed a powerful tool to gather knowledge regarding the skills and habits of customers, thereby gaining their confidence and loyalty.
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