Keyword extraction method based on deep learning language model fused with semantic features
A language model and deep learning technology, applied in the research field of keyword extraction in natural language processing, can solve unrealistic problems and achieve a good domain-independent effect
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[0029] The technical solutions in the embodiments of the present invention will be described clearly and in detail below with reference to the drawings in the embodiments of the present invention. The described embodiments are only some of the embodiments of the invention.
[0030] The technical scheme that the present invention solves the problems of the technologies described above is:
[0031] Such as figure 1 As shown, a keyword extraction method based on deep learning language model fusion semantic features, the basic implementation process is as follows:
[0032] Step S1, given a target document d, first use natural language text processing tools to perform word segmentation and part-of-speech tagging on document d, select nouns or noun phrases in it as candidate keywords, and obtain a set of candidate keywords W={ w 1 ,w 2 ,...,w n}; At the same time, split the target document by sentence to get the sentence set D={s 1 ,s 2 ,...,s n}.
[0033] Step S2, input the...
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