Information recommendation method and system considering compactness of social network user group

Abstract

The invention discloses an information recommendation method and system considering the compactness of a social network user group. The method comprises the steps of obtaining all users in a to-be-analyzed user group in a social network; constructing a graph structure according to all users in the to-be-analyzed user group; regarding each user as a vertex of the graph structure, if friend relationships or attention relationships exist among the users, indicating that correspondingly connected edges exist among the vertexes corresponding to the users, and regarding the interaction times among the users as the weights of the edges; obtaining a vertex set based on the graph structure, and querying the shortest distance between any two vertexes in the vertex set; performing weighted summationon the shortest distance between any two vertexes to obtain the relationship closeness of the to-be-analyzed user group; judging whether the relationship closeness of the to-be-analyzed user group isgreater than a set threshold value or not, and if so, performing information recommendation on each user in the to-be-analyzed user group, namely recommending commodities or services preferred by other users in the to-be-analyzed user group to the current user; otherwise, not recommending the information.

Description

technical field [0001] The present application relates to the technical field of social network mining, in particular to an information recommendation method and system considering the closeness of social network user groups. Background technique [0002] The statements in this section merely mention the background art related to this application, and do not necessarily constitute the prior art. [0003] The problem of calculating the shortest distance between multiple points based on a graph is to give a directed or undirected non-negative weighted graph G, select a set S of any number of points on the graph G, and calculate the distance between any two points in the set S. The shortest distance on G. The shortest distance between two points is the sum of the weights of all edges on the shortest path between these two points. In reality, the data models of several applications can be abstracted as directed or undirected graphs. A social network can be abstracted into a g...

AI Technical Summary

Problems solved by technology

[0007] (2) The entire calculation process is executed sequentially. When the number of vertices in the set V is large, it takes a lot of time

[0008] (3) When traversing the graph starting from each vertex in the set S, there are a lot of repeated calculations, and it is difficult to realize the shared utilization of existing calculation results

[0009] (4) Although some existing work uses a bidirectional breadth-first traversal strategy to calculate the shortest route between two points, it needs to maintain a large number of routes and the search range of the breadth-first traversal strategy is too large, resulting in low query efficiency

[0010] (5) In the process of information recommendation in the prior art, the closeness of user group relationship is not considered, and it is meaningless and valuable to recommend information or products between users in a group that is not close enough, and even waste the cost of the merchant

[0011] To sum up, in the prior art, how to design an efficient parallel computing strategy to improve the computing efficiency of the shortest distance between multiple points on a very large graph still lacks an effective solution

Images