An application of text mining
A practical approach to manage account feedback using text mining algorithms
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The account visit feedback given by account and product managers of a sales department is collected and saved into a database. Besides the basic structure created by the storage in a database, the feedback is free text which contains a lot of abbreviations and spoken language. The concepts of text mining are used to create an editorial tool with the goal to present the information to the analysts in a way that they are able to aggregate it to useful and meaningful phrases. Principles like text tokenization, lemmatization and categorization are explained. Approaches like Document Clustering, In...
The account visit feedback given by account and product managers of a sales department is collected and saved into a database. Besides the basic structure created by the storage in a database, the feedback is free text which contains a lot of abbreviations and spoken language. The concepts of text mining are used to create an editorial tool with the goal to present the information to the analysts in a way that they are able to aggregate it to useful and meaningful phrases. Principles like text tokenization, lemmatization and categorization are explained. Approaches like Document Clustering, Information Retrieval and Information Extraction are consolidated into a general Text Mining model. A practical implementation of this model, including some code snippets in PHP and MySQL, leads to the implementation of an integrated piece of software.
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