Calculation method, device, equipment and storage medium for text similarity
A text similarity and calculation method technology, applied in the text similarity calculation method, equipment, storage media, and device fields, can solve the problem of reducing the number of users' search for similar text content, failing to represent similarity, and weakening the similarity of text-related content and other issues to achieve the effect of increasing the number of references, increasing diversity, and accurately understanding
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Embodiment 1
[0030] Figure 1A It is a flowchart of a method for calculating text similarity provided by Embodiment 1 of the present invention. This embodiment can be applied to any document management system or expert system that needs to analyze text data. A text similarity calculation method provided in this embodiment can be executed by the text similarity calculation device provided in the embodiment of the present invention, the device can be implemented by software and / or hardware, and integrated in the implementation of the method Among the devices, the device executing the method in this embodiment may be any device capable of querying and analyzing document data, such as a tablet computer, a desktop computer, and a notebook. Specifically, refer to Figure 1A , the method may include the following steps:
[0031] S110. Obtain the target text and at least one target text according to user requirements, and perform word segmentation processing on the at least one target text to obta...
Embodiment 2
[0057] figure 2 In the method provided by Embodiment 2 of the present invention, each word in the word sequence of the target text is clustered, and the method flow chart of the subject and the corresponding keyword in the target text is respectively obtained. This embodiment is based on the above-mentioned On the basis of the embodiments, each word in the word sequence of the target text is clustered, and the topics and corresponding keywords in the target text are respectively obtained for further explanation. Specifically, such as figure 2 As shown, the method may include the following steps:
[0058] S210. Determine text feature words and corresponding word vectors in the benchmarking text according to the weights of each word in the word sequence of the benchmarking text.
[0059] Among them, when the word sequence after word segmentation of the benchmarking text is obtained, in order to filter out the words of little contribution or importance in the benchmarking tex...
Embodiment 3
[0086] image 3 It is a flowchart of a method for calculating text similarity provided by Embodiment 3 of the present invention. This embodiment is optimized on the basis of the foregoing embodiments. Specifically, refer to image 3 , this embodiment may include the following steps:
[0087] S310. Obtain the target text and at least one target text according to user requirements, and perform word segmentation processing on the at least one target text to obtain a corresponding word sequence.
[0088] S320. Perform clustering processing on each word in the word sequence of the target text, and respectively obtain topics and corresponding keywords in the target text.
[0089] S330, perform word segmentation processing on the target text, and obtain all target words in the target text.
[0090] S340. According to the word vectors and weights of all keywords in each topic of at least one target text, respectively determine the similarity between each target word and each keywo...
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