CN103336827A - Violence searching method and system for obtaining composite reverse furthest neighbor on road network - Google Patents
Violence searching method and system for obtaining composite reverse furthest neighbor on road network Download PDFInfo
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Abstract
The invention provides a violence searching method and system for obtaining a composite reverse furthest neighbor on a road network. The Dijkstra algorithm is used; each d<VG serves as a source point for primary expansion until all points in Q are visited; if q is visited before all the points in the Q are visited, the q is not the furthest neighbor of the d, and accordingly the d is not the reverse furthest neighbor of the q; if the q is still not visited after the other points in the Q are all visited, the d is confirmed to be the p, and the p<BRFN (q, Q and VG). By means of the violence searching method and system, single reverse neighbors of a query point can be found out rapidly on the road network.
Description
Technical field
The present invention relates to a kind of obtain multiple reverse neighbours' violence searching method and system farthest on the road network.
Background technology
Spatial database (spaitial database) refers to provide spatial data type (spatial database type, SDT) and the database supported of corresponding realization (referring to document 1:G ü ting R H.An introduction to spatial database systems[J] .The VLDB Journal, 1994,3 (4): 357-399).Growing along with mobile computing and cloud computing, the application of space correlation algorithm is increasing.Distance inquiry (proximity query) comprises nearest-neighbors (Nearest Neighbor) inquiry, oppositely nearest-neighbors (Reverse Nearest Neighbor) inquiry, oppositely neighbours' inquiries (Reverse Furthest Neighbor) etc. farthest, is one of modal type in the spatial data library inquiry.The present invention focuses on oppositely neighbours (the reverse furthest neighbor farthest on road network (road network) database, RFN) inquiry, be data set P and the query set Q on given one group of road network, we wish to ask for, and all compare the point farther apart from q among the P with Q.This problem is divided into single oppositely adjacent and multiple oppositely adjacent problem farthest farthest according to P and Q be whether identical.This problem has important meaning in practice, and for example when offering new shop, we wish to learn the point that is subjected to a certain rival to influence minimum.If we represent the influence degree between the different location with the limit of cum rights, it is the reverse neighbor adjacency problem farthest of list of query point that this problem just is equivalent to ask for existing trade company place at road network.Furtherly, seek one and be subjected to existing all rivals to influence minimum point relatively, can be converted into that impact point asks with the rival place at this road network is the multiple oppositely maximization problems of neighbours' quantity farthest of query set Q.
As far as we know, at present on the road network single oppositely farthest unique solution of proposing of adjacent problem be people such as Tran for oppositely adjacent research farthest on the road network, they serve as to generate the some pre-service to set up the Voronoi subregion with each point of interest in the road network, use the adjacency confrontation subregion of subregion to travel through then, to enumerate the possible oppositely neighbours (reverse furthest neighbor) farthest of query point.But this method will not have essential distinction with the violence algorithm when point of interest quantity is big in road network.And for multiple oppositely farthest adjacent problem still do not have relevant solution at present.
Aspect other correlative studys, the most attractive is that nearest-neighbors (nearest neighbor) problem is (referring to document 2, document 3:Hjaltason G R, Samet H.Distance browsing in spatial databases[J] .ACM Transactions on Database Systems (TODS), 1999,24 (2): 265-318, document 4:Berchtold S
C, Keim D A, etc.A cost model for nearest neighbor search in high-dimensional data space[A] .In Proceedings of the sixteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems[C], 1997:78-86, document 5, document 6:Jagadish H, Ooi B C, Tan K-L, etc.iDistance:An adaptive B+-tree based indexing method for nearest neighbor search[J] .ACM Transactions on Database Systems (TODS), 2005,30 (2): 364-397, document 7:Tao Y, Papadias D, Shen Q.Continuous nearest neighbor search[A] .In Proceedings of the28th international conference on Very Large Data Bases[C], 2002:287-29) with reverse nearest-neighbors (referring to document 8:Korn F, Muthukrishnan S.Influence sets based on reverse nearest neighbor queries[J] .ACM SIGMOD Record, 2000,29 (2): 201-212, document 9:Singh A, Ferhatosmanoglu H, Tosun A
High dimensional reverse nearest neighbor queries[A] .In Proceedings of the twelfth international conference on Information and knowledge management[C], 2003:91-98, document 10:Tao Y, Papadias D, Lian X.Reverse kNN search in arbitrary dimensionality[A] .In Proceedings of the Thirtieth international conference on Very large data bases-Volume30[C], 2004:744-755, document 11:Achtert E
C,
P, etc.Efficient reverse k-nearest neighbor search in arbitrary metric spaces[A] .In Proceedings of the2006ACM SIGMOD international conference on Management of data[C], 2006:515-526, document 12:Sankaranarayanan J, Samet H.Distance oracles for spatial networks[A] .In Data Engineering, 2009.ICDE'09.IEEE25th International Conference on[C], 2009:652-663) problem.With R-Tree(referring to document 13:Guttman A.R-trees:a dynamic index structure for spatial searching[M] .ACM, 1984) be the basis the degree of depth (referring to document 2:Roussopoulos N, Kelley S, Vincent F.Nearest neighbor queries[A] .In1995:71-79) with range (referring to document 5:Cui B, Ooi B C, Su J, etc.Contorting high dimensional data for efficient main memory KNN processing[A] .In Proceedings of the2003ACM SIGMOD international conference on Management of data[C], 2003:479-490) first search, increment Euclidean restriction (Incremental Euclidean Restriction), ENCREMENT NETWORK expansion (Invremental Network Expansion, referring to document 14:Papadias D, Zhang J, Mamoulis N, etc.Query processing in spatial network databases[A] .In2003:802-813) technology (referring to document 8～12) relevant with Voronoi figure be widely used in solving the corresponding problem on Euclidean space (Euclidean space) and the road network, but because reverse neighbor adjacency problem does not farthest have the locality characteristics that the nearest-neighbors problem has, these solutions are difficult to be applied on the problem solved by the invention.
Neighbor adjacency problem farthest on the Euclidean space is described (referring to document 15:Yao B, Li F, Kumar P.Reverse furthest neighbors in spatial databases[A] .In2009:664-675) by people such as Yao.They have proposed to go forward one by one, and (progressive furthest cell, PFC) the far field (convex hull furthest cell) of algorithm and convex closure algorithm is to handle this problem in far field.The concept that above-mentioned algorithm all goes based on Voronoi farthest determines that whether certain a bit be the oppositely neighbours farthest of query point q.Given a certain query point q, it about the district fvc of voronoi farthest of certain data set Q (q is a polygonal region Q), in this zone to have a few all be the oppositely neighbours farthest of q.The PFC algorithm uses the R-Tree index, and the strong point of constantly peeking makes up perpendicular bisector explanation space segmentation and gets a side far away and ask for this zone.And the CHFC algorithm utilizes the character of convex closure that this algorithm is carried out beta pruning: if q in the convex closure of query set Q, then problem does not necessarily have solution, otherwise the hunting zone can also be limited within the convex closure of Q and query point q.People such as Liu use pivoting point and index that this algorithm has been carried out improving (referring to document 16:Liu J, Chen H, Furuse K, etc.An efficient algorithm for reverse furthest neighbors query with metric index[A] .In Database and Expert Systems Applications[C], 2010:437-451, document 17:Jianquan L.Efficient query processing for distance-based similarity search[J] .2012).But because point and R-Tree index on the road network do not have direct relation, also do not have the convex closure of strict difinition, these methods all can't directly apply to problem solved by the invention.
Other relevant list of references also comprises:
Document 18:Goldberg A V, Harrelson C.Computing the shortest path:A search meets graph theory[A] .In Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms[C], 2005:156-165;
Document 19:Jing N, Huang Y-W, Rundensteiner E A.Hierarchical encoded path views for path query processing:An optimal model and its performance evaluation[J] .Knowledge and Data Engineering, IEEE Transactions on, 1998,10 (3): 409-432;
Document 20:Erwig M, Hagen F.The graph Voronoi diagram with applications[J] .Networks, 2000,36 (3): 156-163;
Document 21:Jung S, Pramanik S.An efficient path computation model for hierarchically structured topographical road maps[J] .Knowledge and Data Engineering, IEEE Transactions on, 2002,14 (5): 1029-1046;
Document 22:Aurenhammer F.Voronoi diagrams-a survey of a fundamental geometric data structure[J] .ACM Computing Surveys (CSUR), 1991,23 (3): 345-405.
Summary of the invention
The object of the present invention is to provide a kind of obtain multiple reverse neighbours' violence searching method and system farthest on the road network, can on road network, search the reverse neighbours of list of query point fast.
For addressing the above problem, the invention provides a kind of multiple reverse violence searching method of neighbours farthest on the road network that obtains, comprising:
Step 1: for a certain node p on the given road network G and all the node V on the road network G
GIf have node q on the road network G, the road network distance of q and p || q-p|| is not less than p to V
GThe distance of central any some p ' || p '-p||, then defining q is that p is with respect to V
GNeighbours farthest, be designated as fn (p, V
G);
Step 2: for all the node V on the given road network G
GWith the query set Q on the road network G, definition q ∈ Q multiple oppositely farthest neighbours are all V
GMiddle distance q is than other has a few the set of point all far away among the Q, i.e. BRFN (q, Q, V
G)={ p|p ∈ V
G, fn (p, Q)=q};
Step 3: use dijkstra's algorithm with each d ∈ V
GCarry out one extension as source point, till the institute in Q was accessed to a little, if the have a few of q in Q be accessed to before all traveling through, then q was not the neighbours farthest of d, thereby d does not belong to the oppositely neighbours farthest of q; If q other points in Q all are not accessed to after the traversal yet, determine that then d is p, p ∈ BRFN (q, Q, V
G);
Step 4: repeating said steps three, up to neighbours, i.e. p ∈ BRFN (q, Q, the V farthest of answering oppositely that gets access to each query point q
G).
According to another side of the present invention, a kind of multiple reverse violence search system of neighbours farthest on the road network of obtaining is provided, comprising:
First definition module is used for for a certain node p on the given road network G and all the node V on the road network G
GIf have node q on the road network G, the road network distance of q and p || q-p|| is not less than p to V
GThe distance of central any some p ' || p '-p||, then defining q is that p is with respect to V
GNeighbours farthest, be designated as fn (p, V
G);
Second definition module is used for for all the node V on the given road network G
GWith the query set Q on the road network G, definition q ∈ Q multiple oppositely farthest neighbours are all V
GMiddle distance q is than other has a few the set of point all far away among the Q, i.e. BRFN (q, Q, V
G)={ p|p ∈ V
G, fn (p, Q)=q};
Search module is for neighbours, i.e. p ∈ BRFN (q, Q, the V farthest of answering oppositely that obtains each query point q
G), obtain each query point q multiple oppositely farthest neighbours comprise: use dijkstra's algorithm with each d ∈ V
GCarry out one extension as source point, till the institute in Q was accessed to a little, if the have a few of q in Q be accessed to before all traveling through, then q was not the neighbours farthest of d, thereby d does not belong to the oppositely neighbours farthest of q; If q other points in Q all are not accessed to after the traversal yet, determine that then d is p, p ∈ BRFN (q, Q, V
G).
Compared with prior art, the present invention passes through step 1: for a certain node p on the given road network G and all the node V on the road network G
GIf have node q on the road network G, the road network distance of q and p || q-p|| is not less than p to V
GThe distance of central any some p ' || p '-p||, then defining q is that p is with respect to V
GNeighbours farthest, be designated as fn (p, V
G); Step 2: for all the node V on the given road network G
GWith the query set Q on the road network G, definition q ∈ Q multiple oppositely farthest neighbours are all V
GMiddle distance q is than other has a few the set of point all far away among the Q, i.e. BRFN (q, Q, V
G)={ p|p ∈ V
G, fn (p, Q)=q}; Step 3: use dijkstra's algorithm with each d ∈ V
GCarry out one extension as source point, till the institute in Q was accessed to a little, if the have a few of q in Q be accessed to before all traveling through, then q was not the neighbours farthest of d, thereby d does not belong to the oppositely neighbours farthest of q; If q other points in Q all are not accessed to after the traversal yet, determine that then d is p, p ∈ BRFN (q, Q, V
G); Step 4: repeating said steps three, up to neighbours, i.e. p ∈ BRFN (q, Q, the V farthest of answering oppositely that gets access to each query point q
G), can on road network, search the reverse neighbours of list of query point fast.
Description of drawings
Fig. 1 is neighbor adjacency problem (BRFN) example farthest of answering oppositely of one embodiment of the invention.
Embodiment
For above-mentioned purpose of the present invention, feature and advantage can be become apparent more, the present invention is further detailed explanation below in conjunction with the drawings and specific embodiments.
Embodiment one
The invention provides a kind of multiple reverse violence searching method of neighbours farthest on the road network that obtains, comprising:
Step S1, as shown in Figure 1, for a certain node p on the given road network G and all the node V on the road network G
GIf have node q on the road network G, the road network distance of q and p || q-p|| is not less than p to V
GThe distance of central any some p ' || p '-p||, then defining q is that p is with respect to V
GNeighbours farthest, be designated as fn (p, V
G);
Step S2 is for all the node V on the given road network G
GWith the query set Q on the road network G, definition q ∈ Q multiple oppositely farthest neighbours are all V
GMiddle distance q is than other has a few the set of point all far away among the Q, i.e. BRFN (q, Q, V
G)={ p|p ∈ V
G, fn (p, Q)=q};
Step S3 uses dijkstra's algorithm with each d ∈ V
GCarry out one extension as source point, till the institute in Q was accessed to a little, if the have a few of q in Q be accessed to before all traveling through, then q was not the neighbours farthest of d, thereby d does not belong to the oppositely neighbours farthest of q; If q other points in Q all are not accessed to after the traversal yet, determine that then d is p, p ∈ BRFN (q, Q, V
G); Concrete, as representational shortest path first, dijkstra's algorithm is proposed in nineteen fifty-nine by E.W.Dijkstra, and algorithm usage flag method is from source point, each extended range is the nearest point of tag set, thereby asks the shortest path that obtains known point (can referring to document 1);
Step S4, repeating said steps S3 is up to neighbours, i.e. p ∈ BRFN (q, Q, the V farthest of answering oppositely that gets access to each query point q
G).Concrete, pass through each node d ∈ V of traversal in the present embodiment
GChecking that whether it be the oppositely neighbours farthest of query point q, is that source point is carried out dijkstra's algorithm with d, if the node of all among the Q is all accessed before q is accessed, can determine p ∈ BRFN (q, Q, V
G).
Embodiment two
The present invention also provides another kind to obtain multiple reverse neighbours' violence search system farthest on the road network, comprising:
First definition module is used for for a certain node p on the given road network G and all the node V on the road network G
GIf have node q on the road network G, the road network distance of q and p || q-p|| is not less than p to V
GThe distance of central any some p ' || p '-p||, then defining q is that p is with respect to V
GNeighbours farthest, be designated as fn (p, V
G);
Second definition module is used for for all the node V on the given road network G
GWith the query set Q on the road network G, definition q ∈ Q multiple oppositely farthest neighbours are all V
GMiddle distance q is than other has a few the set of point all far away among the Q, i.e. BRFN (q, Q, V
G)={ p|p ∈ V
G, fn (p, Q)=q};
Search module is for neighbours, i.e. p ∈ BRFN (q, Q, the V farthest of answering oppositely that obtains each query point q
G), obtain each query point q multiple oppositely farthest neighbours comprise: use dijkstra's algorithm with each d ∈ V
GCarry out one extension as source point, till the institute in Q was accessed to a little, if the have a few of q in Q be accessed to before all traveling through, then q was not the neighbours farthest of d, thereby d does not belong to the oppositely neighbours farthest of q; If q other points in Q all are not accessed to after the traversal yet, determine that then d is p, p ∈ BRFN (q, Q, V
G).
The present invention passes through step 1: for a certain node p on the given road network G and all the node V on the road network G
GIf have node q on the road network G, the road network distance of q and p || q-p|| is not less than p to V
GThe distance of central any some p ' || p '-p||, then defining q is that p is with respect to V
GNeighbours farthest, be designated as fn (p, V
G); Step 2: for all the node V on the given road network G
GWith the query set Q on the road network G, definition q ∈ Q multiple oppositely farthest neighbours are all V
GMiddle distance q is than other has a few the set of point all far away among the Q, i.e. BRFN (q, Q, V
G)={ p|p ∈ V
G, fn (p, Q)=q}; Step 3: use dijkstra's algorithm with each d ∈ V
GCarry out one extension as source point, till the institute in Q was accessed to a little, if the have a few of q in Q be accessed to before all traveling through, then q was not the neighbours farthest of d, thereby d does not belong to the oppositely neighbours farthest of q; If q other points in Q all are not accessed to after the traversal yet, determine that then d is p, p ∈ BRFN (q, Q, V
G); Step 4: repeating said steps three, up to neighbours, i.e. p ∈ BRFN (q, Q, the V farthest of answering oppositely that gets access to each query point q
G), can on road network, search the reverse neighbours of list of query point fast.
Other detailed content of embodiment two specifically can not repeat them here referring to embodiment one.
Each embodiment adopts the mode of going forward one by one to describe in this instructions, and what each embodiment stressed is and the difference of other embodiment that identical similar part is mutually referring to getting final product between each embodiment.For the disclosed system of embodiment, because corresponding with the embodiment disclosed method, so description is fairly simple, relevant part partly illustrates referring to method and gets final product.
The professional can also further recognize, unit and the algorithm steps of each example of describing in conjunction with embodiment disclosed herein, can realize with electronic hardware, computer software or the combination of the two, for the interchangeability of hardware and software clearly is described, composition and the step of each example described in general manner according to function in the above description.These functions still are that software mode is carried out with hardware actually, depend on application-specific and the design constraint of technical scheme.The professional and technical personnel can specifically should be used for using distinct methods to realize described function to each, but this realization should not thought and exceeds scope of the present invention.
Obviously, those skilled in the art can carry out various changes and modification to invention and not break away from the spirit and scope of the present invention.Like this, if of the present invention these revise and modification belongs within the scope of claim of the present invention and equivalent technologies thereof, then the present invention also is intended to comprise these change and modification.
Claims (2)
1. one kind is obtained multiple reverse neighbours' violence searching method farthest on the road network, it is characterized in that, comprising:
Step 1: for a certain node p on the given road network G and all the node V on the road network G
GIf have node q on the road network G, the road network distance of q and p || q-p|| is not less than p to V
GThe distance of central any some p ' || p '-p||, then defining q is that p is with respect to V
GNeighbours farthest, be designated as fn (p, V
G);
Step 2: for all the node V on the given road network G
GWith the query set Q on the road network G, definition q ∈ Q multiple oppositely farthest neighbours are all V
GMiddle distance q is than other has a few the set of point all far away among the Q, i.e. BRFN (q, Q, V
G)={ p|p ∈ V
G, fn (p, Q)=q};
Step 3: use dijkstra's algorithm with each d ∈ V
GCarry out one extension as source point, till the institute in Q was accessed to a little, if the have a few of q in Q be accessed to before all traveling through, then q was not the neighbours farthest of d, thereby d does not belong to the oppositely neighbours farthest of q; If q other points in Q all are not accessed to after the traversal yet, determine that then d is p, p ∈ BRFN (q, Q, V
G);
Step 4: repeating said steps three, up to neighbours, i.e. p ∈ BRFN (q, Q, the V farthest of answering oppositely that gets access to each query point q
G).
2. one kind is obtained multiple reverse neighbours' violence search system farthest on the road network, it is characterized in that, comprising:
First definition module is used for for a certain node p on the given road network G and all the node V on the road network G
GIf have node q on the road network G, the road network distance of q and p || q-p|| is not less than p to V
GThe distance of central any some p ' || p '-p||, then defining q is that p is with respect to V
GNeighbours farthest, be designated as fn (p, V
G);
Second definition module is used for for all the node V on the given road network G
GWith the query set Q on the road network G, definition q ∈ Q multiple oppositely farthest neighbours are all V
GMiddle distance q is than other has a few the set of point all far away among the Q, i.e. BRFN (q, Q, V
G)={ p|p ∈ V
G, fn (p, Q)=q};
Search module is for neighbours, i.e. p ∈ BRFN (q, Q, the V farthest of answering oppositely that obtains each query point q
G), obtain each query point q multiple oppositely farthest neighbours comprise: use dijkstra's algorithm with each d ∈ V
GCarry out one extension as source point, till the institute in Q was accessed to a little, if the have a few of q in Q be accessed to before all traveling through, then q was not the neighbours farthest of d, thereby d does not belong to the oppositely neighbours farthest of q; If q other points in Q all are not accessed to after the traversal yet, determine that then d is p, p ∈ BRFN (q, Q, V
G).
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| CN102156756A (en) * | 2011-05-16 | 2011-08-17 | 复旦大学 | Method for finding optimal path in road network based on graph embedding |
| CN102637227A (en) * | 2012-03-29 | 2012-08-15 | 武汉大学 | Land resource assessment factor scope dividing method based on shortest path |
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