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A method for automatically generating movie labels based on movie reviews

An automatic generation and labeling technology, applied in the fields of electrical digital data processing, special data processing applications, instruments, etc., can solve the problems of time-consuming and laborious, difficult to cover movies, and few social labels.

Active Publication Date: 2019-02-01
SUN YAT SEN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, currently, for unreleased movies or unpopular movies, due to the very small number of users watching them, these movies usually have very few or no social tags, and the number of these movies is far greater than that of movies with richer social tags
Manually labeling this part of the movie is not only time-consuming and laborious, but also difficult to cover all aspects of the movie more comprehensively

Method used

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  • A method for automatically generating movie labels based on movie reviews

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Embodiment 1

[0025] A method for automatically generating movie tags based on movie reviews, comprising the following steps:

[0026] Step S1: Obtain movie reviews, attributes and their corresponding social tags of all movies on the platform as a training set;

[0027] Step S2: If the number of social tags of a certain movie is lower than the set threshold, tags are automatically extracted from its movie reviews through the tag completion algorithm, so as to add tags to the movie;

[0028] Step S3: Calculate the similarity of attributes for every two movies in the training set, and calculate the similarity of social label sets for every two movies, so as to construct a new data set, and use it to build a regression learner to learn from attributes to similarity map;

[0029] Step S4: Based on the similarity predicted by the regression learner, the K-nearest neighbor method is used to determine the top K most similar movies in the training set for each unlabeled movie, and the multiple set...

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Abstract

The invention provides an algorithm for automatically generating movie labels based on movie reviews. The algorithm in the invention fully considers the missing problem existing in the data set of thecurrently labeled movies. Firstly, an unsupervised algorithm with weights is adopted to automatically replenish the labels for the training set from the movie reviews. At the same time, the inventionalso fully considers the relationship between the similarity of each attribute and the similarity of labels of two movies, and predicts the mapping from each attribute to the similarity of labels bya machine learning method, instead of adopting simple similarity such as cosine similarity to calculate the rough similarity relationship. Finally, after the candidate multisets of labels are obtainedby using the traditional K-nearest neighbor algorithm, the method does not use simple evaluation criteria to sort and select the label set, but uses the graph algorithm based on label co-occurrence relationship to determine the order of the candidate labels, thus deciding the final label set.

Description

technical field [0001] The invention relates to the field of artificial intelligence, and more specifically, to a method for automatically generating movie labels based on movie reviews. Background technique [0002] Because of its rich elements, movies quickly become one of the necessary leisure ways in people's daily life. The market for movies is getting bigger and bigger, and there are more and more types of movies. A wide variety of movies and the length of the movie make it impossible for users to browse a movie in its entirety. For upcoming movies, a better way for users to know about a movie usually includes introduction, trailer, other users’ reviews and movie tags. But for some older or less popular movies, users usually only know the introduction and movie tags. Therefore, the social tags of movies are of great significance. They can help recommendation systems improve the accuracy of movies recommended for users, help platforms that provide movie information fi...

Claims

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Application Information

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IPC IPC(8): G06F16/783
Inventor 吴迪吴灿锐
Owner SUN YAT SEN UNIV
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