A quiz method for literary works based on word vector model

Abstract

The invention relates to a literature guessing method based on a word vector model, and belongs to the technical field of information processing. The method includes the stages of establishing a literature knowledge base and guessing literature knowledge. In the establishing stage, specific literature small-scale linguistic data is collected, and literature feature words are mined from the data; a word vector correlation model is obtained by training a word vector neural network through the small-scale linguistic data; related words highly related to all the feature words are calculated on the basis of the model, and therefore the literature guessing knowledge base is established. In the guessing stage, a system randomly selects a feature word as a guessing object, extracts the related word of the feature word from the knowledge base, and sequentially displays the related word to guessers, and the guessers reason and solve the problem. The feature word relation of the specific literature is found through a word vector model analysis method, the familiarity degree of readers to literatures is inspected in the form of guessing, the interaction between the literatures and the readers is enhanced, and meanwhile reading interestingness is improved.

Description

technical field [0001] The invention relates to a method for guessing literary works based on a word vector model, in particular to a method for guessing literary works based on a word vector model that automatically mines deep complex information relationships in literary works, and belongs to the field of information processing technology. Background technique [0002] Specific literary works refer to literary works or collections of works with specific story backgrounds and plots. Such literary works are often long in length and have complex contextual relationships between characters and things. On the one hand, it takes a lot of energy and time to read such literary works. In today's fast pace of life, it is difficult for people to spare a lot of time to read the whole work completely, so there is an urgent need for a fast and interesting On the other hand, after reading a specific literary work, readers will have a certain understanding of the literary work, and the de...

AI Technical Summary

Problems solved by technology

The manual construction method has the following disadvantages: the quiz knowledge base construction process is very slow, each question requires domain experts to manually construct questions and answers, and the quiz knowledge base generally has many questions, and manual construction is difficult; it relies too much on domain expert knowledge , If you are not familiar with the literature in this field, you will not be able to build a high-quality quiz knowledge base; for literary works of different themes, the portability of artificial construction methods is poor, and the construction method applicable to literary works on a certain theme can be used in another theme Poor effect on literature

Images