Method for predicting attributes of users of film rating/review site on basis of deep neural network

A technology of deep neural network and prediction method, applied in the fields of deep learning, data mining, and matrix decomposition, can solve the problem of poor prediction effect of data sparsity of the number of labels or the number of categories, and achieve the effect of improving the classification effect and accuracy.

Active Publication Date: 2018-11-16
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

[0009] The technical problem to be solved by the present invention is to provide a method for predicting attributes of movie review website users based on a deep ...

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  • Method for predicting attributes of users of film rating/review site on basis of deep neural network
  • Method for predicting attributes of users of film rating/review site on basis of deep neural network
  • Method for predicting attributes of users of film rating/review site on basis of deep neural network

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[0053] In order to make the objectives, technical solutions and advantages of the present invention clearer, the following further describes the present invention in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, but not to limit the present invention.

[0054] See figure 1 , A method for predicting user attributes of movie review websites based on deep neural networks. First, extract the user's historical scoring data from the movie review website. These historical scoring data can be expressed as the user's degree of like or interest in each movie. The user’s historical scoring data is preprocessed with the help of techniques such as matrix decomposition to obtain a high-dimensional user feature vector. The user's feature vector (user vector, that is, the user’s rating of all movies) is used as the input of the deep neural network and combine...

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Abstract

The invention discloses a method for predicting attributes of users of a film rating/review site on the basis of a deep neural network and belongs to the fields of data excavation, machine learning and the like. The method comprises the following steps: performing matrix decomposition on sparse user rating data in the film rating/review site to form a user-feature matrix and a film-feature matrix,performing partial filling on user vectors by utilizing the two matrixes, and taking the filled user rating data as user feature vectors; inputting the user feature vector data into a fully connecteddeep neural network, combining a multi-task learning technology, training a network model, and obtaining tags and scores of all the tasks; and according to the tags and the scores of all the tasks, performing decision-making analysis, and obtaining a final classification result. The method disclosed by the invention automatically predicts the attributes of the users of the film rating/review siteby virtue of a deep neural network technology, solves the problem of data sparsity and has relatively high classification accuracy and efficiency.

Description

Technical field [0001] A method for predicting the attributes of film review website users based on deep neural networks is used to predict each attribute-people's preference for movies based on film reviews. It belongs to the technical fields of data mining, deep learning, matrix decomposition and so on. Background technique [0002] Deep learning is derived from artificial neural networks. It can use modern neurological ideas to simulate the structure and mechanism of biological brain neurons and build artificial neural network models. Deep learning is to establish multiple hidden layers between the input layer and output layer of the network to form a complex neural network. Through the unlabeled or labeled learning of sample data, optimize and adjust the parameters between the networks to solve the classification after regression problem. [0003] The essence of deep learning is to build a multi-layer neural network model to learn useful features from massive data, and to accu...

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Application Information

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IPC IPC(8): G06F17/30G06N3/08
CPCG06N3/08
Inventor 屈鸿刘永胜房展舒扬杨舰邓悟季江舟张晓敏
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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