Sparse group query method based on position
A query method, a sparse technique, applied in the field of spatial databases and social networks
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Embodiment 1
[0031] A location-based sparse group query method, comprising the following steps:
[0032] S1: use the distance order to the query point to traverse the users and combine them;
[0033] S2: During the query process, some invalid user combinations are cut by distance pruning.
[0034] In step S1, in order to quickly find the neighbors beyond the k-hops of each user, the c-neighbors of each user are pre-calculated before the query arrives; when the sparsity threshold k≤c, it is possible to determine which nodes are the current nodes The neighbors beyond the k-hop, but when k>c, according to the information of the c-neighbors, it is impossible to judge which neighbors are beyond the k-hops. In this case, it is necessary to calculate the k-neighbors through the information of the c-neighbors , where, for a given social network graph G=(V,E), the c-neighborhood of point v is expressed as: the set of points u satisfying social_dis(u,v)≤c in graph G.
[0035] In step S1, the dista...
Embodiment 2
[0046] A location-based sparse group query method, comprising the following steps:
[0047] S1: use the distance order to the query point to traverse the users and combine them;
[0048] S2: During the query process, some invalid user combinations are cut by distance pruning.
[0049] In step S1, in order to quickly find the neighbors beyond the k-hops of each user, the c-neighbors of each user are pre-calculated before the query arrives; when the sparsity threshold k≤c, it is possible to determine which nodes are the current nodes The neighbors beyond the k-hop, but when k>c, according to the information of the c-neighbors, it is impossible to judge which neighbors are beyond the k-hops. In this case, it is necessary to calculate the k-neighbors through the information of the c-neighbors , where, for a given social network graph G=(V,E), the c-neighborhood of point v is expressed as: the set of points u satisfying social_dis(u,v)≤c in graph G.
[0050] In step S1, the dista...
Embodiment 3
[0062] The invention provides a location-based sparse group query method. Before the problem definition of the location-based sparse group query is given, the concept of a location-based social network graph is first given.
[0063] Definition 1 (location-based social network graph) For a location-based social network graph G=(V,E,L), each point v in V represents a user, and e(u,v)∈E represents u , There is a social relationship between v, l(u) represents the geographic location coordinates of user u, and L is the set of location coordinates of all users.
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