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Personalized Music Recommendation Ranking Method Based on Exponential Decay Window

An exponential decay and sorting method technology, applied in the field of data processing, can solve the problem of low degree of recommendation personalization and achieve high recommendation accuracy

Inactive Publication Date: 2019-03-22
COMMUNICATION UNIVERSITY OF CHINA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0006] In view of this, the technical problem to be solved by the present invention is to provide a personalized music recommendation sorting method based on an exponential decay window, which solves the problem that the existing music recommendation is not highly personalized

Method used

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  • Personalized Music Recommendation Ranking Method Based on Exponential Decay Window
  • Personalized Music Recommendation Ranking Method Based on Exponential Decay Window
  • Personalized Music Recommendation Ranking Method Based on Exponential Decay Window

Examples

Experimental program
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Effect test

specific Embodiment approach

[0117] (1) Example analysis of similar rule generation

example

[0118] Example: The input to the algorithm includes the user's music playlist and audio content information. The example given in Table 1 is a playlist of music selected by 6 users on a certain music website:

[0119] Table 1. User playlists

[0120] user

playlist

U1

t1,t3,t5

U2

t3,t5,t2,t1,t4

U3

t1,t3,t5,t2

U4

t4,t1,t5,t2

U5

t1,t4,t3

U6

t3, t5

U7

t5,t1

[0121] The calculation steps of this example are as follows:

[0122] (1) To divide the music in the user's playlist in order, such as playlist will be split into R(t 1 ,t 3 ,1) and R(t 3 ,t 5 ,1)(R(t i ,t j , n) in t i represents the parent node, t j represents a child node, and n represents the jump frequency between the parent node and the child node). Count the playlists of all users in the table, that is, get the jump frequency map between music, such as Figure 10 shown, for example, t 1 jump to t 5 The number of times...

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Abstract

The invention provides a personalized music recommendation sorting method based on an exponential decay window. The personalized music recommendation sorting method comprises the steps that similarity rule transition probability matrixes of all pieces of music in twos in a music library are acquired; different weights are given to data of corresponding rows of the similarity rule transition probability matrixes corresponding to user playlists, and then operation is performed, so that a row of user recommendation transition probabilities are obtained; according to the user recommendation transition probabilities, the transformation probabilities of corresponding user music recommendation lists are obtained; according to the transformation probabilities, the music in the user music recommendation lists is sorted. The personalized music recommendation sorting method solves the cold start problem of new music and can guarantee high personalized music recommendation accuracy.

Description

technical field [0001] The present invention relates to data processing technology, in particular to a music recommendation method, specifically a personalized music recommendation sorting method based on an exponential decay window. Background technique [0002] With the rapid development of the music Internet, people can gradually obtain massive music resources through the Internet. However, the simultaneous presentation of massive amounts of information makes it difficult for users to choose music, and on the other hand, makes it impossible for potential users to discover a large amount of music, making this part of music seldom appreciated. Personalized music recommendation can establish a binary relationship between users and music, through the relationship between music and users to mine the music that each user is potentially interested in, and then perform personalized music recommendations. In fact, personalized music recommendation has an important application pro...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/638G06F16/635
CPCG06F16/635G06F16/639
Inventor 李樱张颜南王永滨吴林刘静
Owner COMMUNICATION UNIVERSITY OF CHINA
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