Personalized information recommendation method by information fusion

A technology of recommendation method and learning method, which is applied in the field of information fusion and personalized recommendation to improve the accuracy rate and solve the effect of cold start

Active Publication Date: 2018-11-30
BEIJING INSTITUTE OF TECHNOLOGYGY
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  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to solve the cold start problem of new items in existing recommendation methods and optimize the accuracy of recommendation results, the present invention proposes an information fusion personalized recommendation method, which optimizes the recommendation effect by exploring and utilizing the value of item information to supplement user interaction information

Method used

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  • Personalized information recommendation method by information fusion
  • Personalized information recommendation method by information fusion
  • Personalized information recommendation method by information fusion

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Embodiment Construction

[0030] The present invention provides a recommendation method based on representation learning. Representation learning can represent the original information as a low-dimensional dense real-valued vector under the condition of retaining the semantics of the original information, and use different representation learning methods to construct different morphological information. The model extracts its feature vector and applies it to the recommendation task, which effectively solves the cold start problem of new items and optimizes the accuracy and recall rate of the recommendation results. The process steps of the whole method will be introduced and illustrated in detail below with reference to the accompanying drawings.

[0031] In this embodiment, the steps in the summary of the invention are applied to a movie recommendation scene to reflect technical effects. This embodiment applies the movie data set of Movielens1M, which includes 1,000,209 ratings of 3,900 movies by 6,04...

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Abstract

The invention relates to a personalized information recommendation method by information fusion, belonging to the technical field of Internet information recommendation. The method includes first pre-processing a data set to extract item shape information: determining a relationship type between items, constructing a relationship network between items, determining item text information, and determining item image information; using a network representation learning method to extract network relationship features, extracting text features by using a text representation learning method, and extracting image features by using an image feature extraction method; then calculating a user's preference feature value for each item in each dimension; finally inputting preference features into a sorting model, and recommending items with scores TOP-N in an alternative set to the user. Compared with the prior art, the method improves the accuracy of recommendation results by excavating and utilizing attribute information of the items to supplement sparse user active interaction data; and the integration of the item attribute information can make the recommendation not only rely on rating data,but also help solve the problem of cold boot of new items.

Description

technical field [0001] The invention relates to an information recommendation method in the Internet field, in particular to an information fusion personalized recommendation method, which belongs to the technical field of Internet information recommendation. Background technique [0002] With the development of information technology and the Internet, the current society has gradually changed from an era of information scarcity and slow communication to an era of information overload and information redundancy. For the information receiver, it is impossible to quickly find the target information from the massive information; for the information producer, it is impossible to expose the information to the target users. The recommendation system emerged as a bridge between the two. The effect of the recommendation system depends on the performance of the recommendation algorithm, and the research on the recommendation algorithm in the academic circle has never stopped. [00...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
Inventor 礼欣杨璐王一拙
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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