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Natural Language Processing (NLP) and Machine Learning (ML) are hot topics in this season even though they have been around since the 1950'. NLP has come to attention because the amount of textual data available on-line is massive and users need software to handle it. There are multiple examples of solutions using NLP, e.g. email spam classification, machine translation, sentiment analysis and named-entity recognition (NER). NER is the task of finding special entities in textual documents, e.g. person names, locations and organizations.

This talk will show you

• how to create a model to a NER framework which can detect named authors in mailing forums messages (documents),

• how to measure the performance (quality) of the model and

• experience about how to improve the model

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