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An integrated method for financial product recommendation system

A technology of recommendation system and integrated method, which is applied in the field of online product recommendation, can solve problems such as cold start of the recommendation system, achieve the effects of reducing cold start problems, improving adaptability, and improving recommendation performance

Active Publication Date: 2021-01-05
SHANGHAI DIGITAL CHINA INFORMATION TECH SERVICE CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0015] The invention provides an integration method for a financial product recommendation system, which reduces the impact of data sparsity and solves the cold start problem of the recommendation system
The recommendation algorithm based on demographics does not require historical data and does not depend on the attributes of items, which can solve the user's cold start problem

Method used

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  • An integrated method for financial product recommendation system
  • An integrated method for financial product recommendation system
  • An integrated method for financial product recommendation system

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Embodiment Construction

[0018]Such asfigure 1 As shown, the present invention provides an integrated method for a financial product recommendation system, including the following steps:

[0019]Input data are: user characteristic information, item-attribute matrix, user-item scoring matrix; output data: product recommendation model, user recommendation results.

[0020]Step 1: Recommendation algorithm based on demographics.

[0021]The traditional demographic-based recommendation algorithm is improved, and different user attributes are assigned different weights. The present invention selects four characteristics of age, gender, occupation, and hobbies as the considered range, and preprocesses each attribute information into a digital representation form. Calculate the similarity between users to obtain user preferences.

[0022]1. Age attribute, the present invention takes 5 years as the increment, for example, the age of 32 years can be recorded as 7, and the age of 56 years can be recorded as 12. Euclidean distance...

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Abstract

The invention discloses an integrated method used for a finance product recommending system. Based on a data smooth collaborative filtering algorithm, filling can be conducted on sparse data, and theproblem of sparsity of the data is solved. Based on a recommendation algorithm of population statistics, historic data is not needed, dependency on attributes of objects is not needed, and the problemof cold start can be solved for a user; the two kinds of algorithms are integrated with a recommendation algorithm which is good in expressive performance and is based on item clustering and matrix decomposition, the range of application scenes is enlarged for the recommendation algorithm, and the self-adaptability of the recommendation algorithm is improved. The integrated method can effectivelyreduce the sparsity of the data and solve the problem of cold start, and promotes recommendation performance for each user.

Description

Technical field[0001]The invention belongs to the technical field of online product recommendation, and in particular relates to an integration method for a financial product recommendation system.Background technique[0002]Traditional recommendation algorithms mostly use user rating data to calculate users' interest preferences and resource similarity. Recommendations for sparse data and new users are of low quality and cannot maximize the information contained in the hidden data.[0003]In recent years, in response to the problems caused by data sparseness, in order to improve the recommendation effect, scholars have introduced principal component analysis, cluster analysis, singular value decomposition and other algorithms into the traditional collaborative filtering recommendation algorithm to reduce the target users through dimensionality reduction. Searching the range of nearest neighbors has significantly improved the accuracy and real-time performance of recommendations, but th...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q30/02G06Q30/06G06Q40/06
CPCG06Q30/0255G06Q30/0631G06Q40/06
Inventor 李建强李倩张丝雨
Owner SHANGHAI DIGITAL CHINA INFORMATION TECH SERVICE CO LTD