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Mining Structured and Unstructured Data

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Oracle Advanced Analytics (OAA) Database Option leverages Oracle Text, a free feature of the Oracle Database, to pre-process (tokenize) unstructured data for ingestion by the OAA data mining algorithms. By moving, parallelized implementations of machine learning algorithms inside the Oracle Database, data movement is eliminated and we can leverage other strengths of the Database such as Oracle Text (not to mention security, scalability, auditing, encryption, back up, high availability, geospatial data, etc.. This YouTube video presents an overview of the capabilities for combing and data mining structured and unstructured data, includes several brief demonstrations and instructions on how to get started--either on premise or on the Oracle Cloud.
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Text Comments (2)
Richard Chan (1 year ago)
tokenising text is all well and good but how is sentiment analysed ? the same words grouped and ordered in different ways can give completely opposite meaning
Kristofer Älvring (1 year ago)
In the example it appears as if the SVM partitioned tokenized data between positive and negative sentiment. Where did this labelling come from? Was it embedded in the tokens? ie there's some pre-computed rule which states that with 0.2% probability the word "flabbergasted" is a negative sentiment?

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