Structuring Unstructured Data—Or: How Machine Learning Can Make You a Wine Sommelier
Textual data, for example in the form of e-mails, instant messages, or social media posts, is ubiquitous today. As textual data typically comes in unstructured formats and is often ambiguous in meaning, it is difficult to analyze it using computational tools. However, advances in machine learning and the increasing availability of training data make it now possible to extract useful knowledge from large amounts of unstructured textual data. In this chapter, we showcase the use of unsupervised machine learning algorithms and visualization techniques to bring structure to—and thereby learn from—more than 100,000 professional wine reviews. Something that could be useful, for example, when choosing suitable wines for the celebration of your 60th birthday.
KeywordsUnstructured data Machine learning Topic modelling Online reviews Wine
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