Heterogeneous network community discovery method integrating deep learning and social recommendation

The invention discloses a heterogeneous network community discovery method integrating deep learning and social recommendation, which comprises the following steps: arranging heterogeneous data into a heterogeneous information network through a network mode, selecting an effective meta path, and con...

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Bibliographische Detailangaben
Hauptverfasser:	LIU YONGJUN, LIU JINGLIAN, ZHANG ZIXIAO, ZHAO WEIJI, SI YALI
Format:	Patent
Sprache:	chi ; eng
Schlagworte:	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ELECTRIC DIGITAL DATA PROCESSING PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
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Beschreibung
Zusammenfassung:	The invention discloses a heterogeneous network community discovery method integrating deep learning and social recommendation, which comprises the following steps: arranging heterogeneous data into a heterogeneous information network through a network mode, selecting an effective meta path, and constructing a user-user social network and a user-community bipartite network; training and optimizing a user-user social network and a user-community bipartite network through a graph neural network and a marking mechanism, and fusing the user-user social network and the user-community bipartite network to construct a user-community expansion graph; based on the user-community expansion graph, selecting a meta-path, measuring the similarity between a target user and a target community based on the meta-path, and obtaining a target user-target community node pair; and training the target user-target community node pair input into the graph neural network, outputting the probability that the target user joins in the t