The automated keyword extraction task is to define a collection of representative terms for the text. Extracting keywords defines a small collection of terms, key phrases and keywords that define the document’s context. Keyword search allows large document collections to be searched effectively. To allocate suitable key-phrases to new documents, text categorization techniques can be applied. A predefined collection of key-phrases from which all key-phrases for new documents are selected is given in the training documents. The training data for each key-phrase describes a collection of documents associated with it. Standard machine learning techniques are used for each key-phrase to construct a "classifier" from the training materials, using those relevant to it as positive examples and the rest as negative examples. Provided a new text, it is processed by the classifier of each key-phrase.
Text mining, Keyphrases, clustering, supervised learning, unsupervised learning etc
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