A word association prompting method, device, equipment and computer storage medium for intelligent input
A technology of intelligent input and words, applied in the computer field, can solve the problems of no semantic association function and low recall rate, and achieve the effect of improving friendliness, good enlightenment and intuition, and improving the recall rate of recommendation.
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Embodiment 1
[0065] Such as Figure 1-7 As shown, the word association prompting method for intelligent input provided in this embodiment may, but is not limited to, include the following steps.
[0066] S101. Acquire a corpus containing a large number of documents.
[0067] In the step S101, the corpus is used to provide a sufficient amount of training corpus for the training process of the LDA topic model, and the training corpus can be provided by the user or constitute various document data collected by existing acquisition software, each A document may, but is not limited to, consist of a part or several fields of title, abstract, keywords, text, attachment title, attachment content, and author information. In addition, the mass of documents is generally more than 10,000 documents, for example, 100,000 documents are selected to form the corpus.
[0068] S102. Perform numerical processing on the word sets of each document in the corpus, and then execute step S1031 and step S1032 sync...
Embodiment 2
[0093] Such as Figure 8As shown, this embodiment provides a hardware device for implementing the word association and prompting method for intelligent input described in Embodiment 1, including an acquisition module, a processing module, a training module, a search module and an output module that are sequentially connected by communication, wherein , the training module includes a Word2Vec model training submodule and an LDA topic model training submodule; the acquisition module is used to obtain a corpus containing a large number of documents; the processing module is used to collect words of each document in the corpus Perform numerical processing; the Word2Vec model training submodule is used to import the numerical processing results as training samples into the Word2Vec model for training, obtain the word vector of each word, and then obtain the set of related words of each word according to the word vector; The LDA topic model training submodule is used to import the n...
Embodiment 3
[0096] Such as Figure 9 As shown, this embodiment provides a hardware device for implementing the word association and prompting method for intelligent input described in Embodiment 1, including a memory and a processor connected by communication, wherein the memory is used to store computer programs, and the The processor is used to execute the computer program to realize the steps of the word association prompting method for intelligent input as described in the first embodiment.
[0097] For the working process, working details and technical effects of the word association prompting device provided in this embodiment, please refer to Embodiment 1, and details will not be repeated here.
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