Named-entity recognition through sequence of classification using a deep learning neural network

An illustrative embodiment provides a computer implemented method for extracting named entity information from full text includes obtaining text data from a document. The method also includes tokenizing the text data as numbers to produce a tokenized layer. The method also includes creating an embed...

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Bibliographische Detailangaben
Hauptverfasser: An, Hongguo, Chopra, Akshay, Desai, Paren
Format: Patent
Sprache:eng
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Beschreibung
Zusammenfassung:An illustrative embodiment provides a computer implemented method for extracting named entity information from full text includes obtaining text data from a document. The method also includes tokenizing the text data as numbers to produce a tokenized layer. The method also includes creating an embedded layer from the tokenized layer by encoding the text data by indices. The method also includes creating a one-dimensional Xception layer from the embedded layer according to a one-dimensional convolution. The method also includes determining a sequence of classification for the text data according to the one-dimensional Xception layer. The method also includes determining a named entity value from the text data according to the sequence of classification, wherein each sequence of classification predicts one character of the named entity value.