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Conversational music recommendation method based on Meta-graph knowledge map representation

A knowledge map and recommendation method technology, applied in the field of conversational music recommendation based on Meta-graph knowledge map representation, can solve the problems of single feedback mode and application scenarios, and the inability to realize real-time music recommendation, and achieve the effect of reducing dimensions

Active Publication Date: 2018-11-23
EAST CHINA NORMAL UNIVERSITY
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  • Abstract
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  • Claims
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AI Technical Summary

Problems solved by technology

However, there are currently several types of conversational music recommendation methods, but their feedback methods and application scenarios are single, and it is impossible to realize real-time music recommendation in the human-machine dialogue scenario.

Method used

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  • Conversational music recommendation method based on Meta-graph knowledge map representation
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  • Conversational music recommendation method based on Meta-graph knowledge map representation

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Embodiment Construction

[0021] Specific embodiments of the present invention will be described below in conjunction with the accompanying drawings, so that those skilled in the art can better understand the present invention. It should be noted that in the following description, when detailed descriptions of known functions and designs may dilute the main content of the present invention, these descriptions will be omitted here.

[0022] There are various types of nodes and edges in the knowledge graph, which can be regarded as a type of heterogeneous information network (Heterogeneous Information Network, HIN). Meta-path is based on a heterogeneous information network to represent complex relationships from one node type to another node type, for example, Among them, A and R represent the types of nodes and edges respectively, and the specific meaning is that node A 1 and node A 2 by side R 1 Make connections to reach from A 1 to A 2 path, the subsequent path is the same as above, and finally ...

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Abstract

The invention discloses a conversational music recommendation method based on Meta-graph knowledge map representation. The method comprises the following steps: generating a feature vector offline based on the Meta-graph knowledge map representation, and performing online conversational recommendation based on the Bandit algorithm. By adoption of the method, the music recommendation based on the Meta-graph knowledge map representation in a conversation scene is realized, that is, in a scene of human-machine dialogue, the preference for music of a user is obtained in real time, the long-term and short-term preference of the user is modeled in combination with a knowledge map, a context-aware recommendation result is provided in time to achieve real-time recommendation, and contextual information, user needs and feedback can be well handled.

Description

technical field [0001] The invention belongs to the technical field of music recommendation in data mining, and more specifically, relates to a dialogue music recommendation method based on a Meta-graph knowledge map representation in which the application scene is a man-machine dialogue scene. Background technique [0002] The rapid development of network information technology has brought great convenience to people's life. At the same time, it has also thrown out new problems and difficulties: information overload. Recommended technology is a good way to alleviate and solve such problems. [0003] Recommendation technology is aimed at information filtering and can actively recommend information that users are interested in. A good recommendation technology can not only improve user stickiness and loyalty, but also obtain commercial benefits and achieve a win-win situation. At present, many well-known Internet companies at home and abroad have also applied recommendation ...

Claims

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Application Information

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IPC IPC(8): G06F17/30
Inventor 王晓玲靳远远周纯伊
Owner EAST CHINA NORMAL UNIVERSITY
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