Text error correction method based on knowledge graph
A knowledge map and text error correction technology, applied in the field of speech recognition, can solve problems such as difficulty in getting started, high personnel requirements, and low levels, and achieve the effect of assisting in scheduling words
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Embodiment 1
[0034] refer to figure 1 , is the first embodiment of the present invention, which provides a text error correction method based on knowledge graph, including:
[0035] S1: Build a knowledge graph based on substation information and equipment switch information.
[0036] (1) Extract and integrate the organization, personnel, and phone number information in the DCCS database to obtain call information;
[0037] (2) Semantically analyze the operation ticket instruction data to obtain substation information and equipment switch information;
[0038] (3) Perform word sense disambiguation and synonym conversion processing on substation information and equipment switch information, and then store the processed information in the knowledge map, such as figure 1 shown.
[0039] Specifically, the steps of word sense disambiguation are as follows:
[0040] ① Mark the entities to be disambiguated in the substation information and equipment switch information, and then use the context...
Embodiment 2
[0069] The technical effect adopted in this method is verified and explained. In this embodiment, the traditional technical solution is selected and this method is used for comparative testing, and the test results are compared by means of scientific demonstration to verify the real effect of this method.
[0070] The traditional technical solution mainly corrects text errors through empirical judgment and comparison with operation tickets, which has a high error rate and low efficiency.
[0071] In order to verify that this method has a higher text error correction capability than the traditional technical solution, in this embodiment, the traditional technical solution and this method will be used to correct and compare the collected texts respectively.
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