Self-learning accident text label and abstract generation system and method
A text label, self-learning technology, applied in the field of big data processing, can solve the problems of text labels and abstracts that cannot be standardized, timeliness deviation, etc.
Active Publication Date: 2019-07-02
HANGZHOU XUJIAN SCI & TECH CO LTD
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Problems solved by technology
[0002] The text labels and abstracts of current accidents are generally generated manually, and the timeliness will deviate. Due to the differences in the description habits of different people, the final text labels and abstracts cannot be standardized
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[0085] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
[0086] see figure 1 , the present invention provides a technical solution: a self-learning accident text label and abstract generation system, including a word segmentation module 1, a word vector training module 2, a word vector model module 3, a keyword generation module 4, and a keyword library module 5 , text label generation module 6, text label library module 7, text label separation module 8, accident summary generation module 9, accident library module...
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The invention provides a self-learning accident text label and abstract generation system and method. The self-learning accident text label and abstract generation system comprises a word segmentationmodule, a word vector training module, a word vector model module, a keyword generation module, a keyword library module, a text label generation module, a text label library module, a text label separation module, an accident abstract generation module and an accident library module. According to the technical scheme of the invention, the word vector model and the keyword library of the accidentare generated according to the existing accident set; a keyword library is used to combine upper and lower parts to obtain a file label; a word vector model is used to merge the similar character tags to generate character label libraries, and new accidents are automatically classified by using the character label library to obtain standardized accident character labels; and the text labels are summarized to obtain standardized accident abstract information, so that the manual accident classification and summarization delay is reduced, the accident analysis speed is increased, the induction difference caused by the difference of description habits of different persons is reduced, and convenient accident information standardized retrieval and classification statistics and accident analysisare provided.
Description
technical field [0001] The invention relates to the technical field of big data processing, in particular to a self-learning accident text label and abstract generation system and method thereof. Background technique [0002] The text labels and abstracts of current accidents are generally generated manually, and the timeliness will deviate. Due to the differences in the description habits of different people, the final text labels and abstracts cannot be standardized. The text label here refers to the description of the accident in only one dimension, which is used for classification retrieval and retrieval keywords, and the accident summary is a simple description of the accident mixed with various text labels. Contents of the invention [0003] In order to solve the problems raised in the above-mentioned background technology, the object of the present invention is to provide a self-learning accident text label and abstract generation system and method thereof, which ge...
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Login to View More IPC IPC(8): G06K9/62G06F16/33G06F17/27
CPCG06F40/284G06F18/2411G06F18/214
Inventor 鲁立虹陈尚武卢锡芹胡松涛倪仰张慧娟赵伯亮邬奇龙
Owner HANGZHOU XUJIAN SCI & TECH CO LTD