CN103336827B - Obtain the force search method and system of the most farthest multiple neighbours on road network - Google Patents

Abstract

The invention provides a kind of force search method and system obtaining neighbours the most farthest on road network, by the present invention in that with dijkstra's algorithm with each d ∈ V_GOne extension is carried out as source point, until being accessed to a little in Q, if the institute that q is in Q is accessed to before a little all being traveled through, then the farthest neighbours of q not d, thus d is not belonging to the most farthest neighbours of q；If other points that q is in Q are accessed to after all being traveled through not yet, it is determined that d is p, p ∈ BRFN (q, Q, V_G), it is possible on road network, fast search is to single reversely neighbours of query point.

Description

Obtain the force search method and system of the most farthest multiple neighbours on road network

Technical field

The present invention relates to a kind of force search method and system obtaining neighbours the most farthest on road network.

Background technology

Spatial database (spaitial database) refer to provide Spatial data types (spatial database type, SDT) data base and realizing support accordingly (sees document 1:G ü ting R H.An introduction to Spatial database systems [J] .The VLDB Journal, 1994,3 (4): 357-399).Along with mobile meter Calculation is growing with cloud computing, and the application of spatial correlation algorithm is increasing.Distance query (proximity Query) include that nearest-neighbors (Nearest Neighbor) inquiry, Reverse Nearest occupy (Reverse Nearest Neighbor) inquiry, the most farthest neighbor queries (Reverse Furthest Neighbor) etc., be spatial database One of modal type in inquiry.The present invention focus on road network (road network) data base reversely Remote neighbours (reverse furthest neighbor, RFN) inquiry, i.e. gives data set P on one group of road network and looks into Ask collection Q, it is intended that ask for all points that distance q is farther compared with Q in P.This problem is according to P and Q The most identical it is divided into single the most farthest the most adjacent and multiple adjacent problem.This problem has weight in practice Big meaning, such as when offering new shop, it is intended that learns the point being affected minimum by a certain rival. If the influence degree between different location is represented by we with the limit of cum rights, this problem is equivalent on road Ask for the single the most farthest neighbor adjacency problem with existing trade company place as query point on the net.Furtherly, one is found The individual point minimum by existing all rival's relative effects, can be converted into impact point on this road network Seek the maximization problems answering the most farthest neighbours' quantity for query set Q with rival place.

As far as we know, the unique solution proposed for the most farthest single on road network adjacent problem at present is Tran et al. is for adjacent research the most farthest on road network, and they are with each point of interest in road network for generating Voronoi subregion is set up in some pretreatment, then uses the adjacency confrontation subregion of subregion to travel through, to enumerate The most farthest neighbours (reverse furthest neighbor) that query point is possible.But this method is emerging in road network When interest point quantity is big, will there is no essential distinction with violence algorithm.And for the most farthest adjacent problem again the most still Without relevant solution.

In terms of other correlational studyes, the most interestingly nearest-neighbors (nearest neighbor) problem (sees 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) (see literary composition with Reverse Nearest residence Offer 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 AHigh 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, literary composition Offer 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.Document 13:Guttman A.R-trees:a dynamic index is seen with R-Tree( The degree of depth based on structure for spatial searching [M] .ACM, 1984) (see document 2: Roussopoulos N, Kelley S, Vincent F.Nearest neighbor queries [A] .In1995:71-79) (document 5:Cui B, Ooi B C, Su J, etc.Contorting high dimensional data for is seen with range efficient main memory KNN processing[A].In Proceedings of the2003ACM SIGMOD international conference on Management of data [C], 2003:479-490) preferential Search, increment Euclidean limit (Incremental Euclidean Restriction), ENCREMENT NETWORK extension (Invremental Network Expansion, sees document 14:Papadias D, Zhang J, Mamoulis N, Etc.Query processing in spatial network databases [A] .In2003:802-813) and Voronoi The technology (seeing document 8～12) that figure is relevant is widely used in solving Euclidean space (Euclidean space) and road Online corresponding problem, but owing to the most farthest neighbor adjacency problem does not have this locality that nearest-neighbors problem is had Property feature, these solutions are difficult to apply in problem solved by the invention.

Farthest neighbor adjacency problem on Euclidean space by Yao et al. be been described by (see document 15:Yao B, Li F, Kumar P.Reverse furthest neighbors in spatial databases [A] .In2009:664-675).He Propose go forward one by one far field (progressive furthest cell, PFC) algorithm and convex closure far field (convex Hull furthest cell) algorithm to be to process this problem.Above-mentioned algorithm is based on the concept that farthest Voronoi goes to be come really Determine the most farthest neighbours whether certain point is query point q.Given a certain query point q, it is about certain data Collection Q farthest voronoi district fvc (q, Q) be a polygonal region, in this region be the most all q The most farthest neighbours.PFC algorithm uses R-Tree index, and constantly peek strong point builds perpendicular bisector explanation Space is split and takes side farther out to ask for this region.And CHFC algorithm utilizes the character pair of convex closure This algorithm carries out beta pruning: if q is in the convex closure of query set Q, then problem is certain without solving, and the most also may be used Within hunting zone is limited in the Q convex closure with query point q.Liu et al. uses pivoting point and index to this One algorithm has carried out improving and (has seen 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 due to the point on road network with R-Tree indexes without direct relation, does not also have the convex closure of strict difinition, and these methods all cannot directly apply to Problem solved by the invention.

Other relevant list of references also includes:

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

It is an object of the invention to provide a kind of force search method obtaining on road network the most farthest multiple neighbours and System, it is possible to fast search is to single reversely neighbours of query point on road network.

For solving the problems referred to above, the present invention provides a kind of and obtains the force search of the most farthest multiple neighbours on road network Method, including:

Step one: for a certain node p on given road network G and all node V on road network G_GIf, Road network distance | | q-p | | of node q, q and p is there is not less than p to V on road network G_GCentral any some p's ' Distance | | p '-p | |, then definition q is that p is relative to V_GFarthest neighbours, be designated as fn (p, V_G)；

Step 2: for all node V on given road network G_GWith the query set Q on road network G, definition The multiple the most farthest neighbours of q ∈ Q are all V_GMiddle distance q than in Q other the set of the most remote point, 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_GOne extension is carried out as source point, until Q In be accessed to a little till, if q in Q institute a little all traveled through before be accessed to, then The farthest neighbours of q not d, thus d is not belonging to the most farthest neighbours of q；If other some quilts that q is in Q All it is accessed to not yet after traversal, it is determined that d is p, p ∈ BRFN (q, Q, V_G)；

Step 4: repeating said steps three, until getting the multiple the most farthest neighbours of each query point q, I.e. p ∈ BRFN (q, Q, V_G)。

Another side according to the present invention, it is provided that a kind of force search system obtaining neighbours the most farthest on road network System, including:

First definition module, for for a certain node p on given road network G and all knots on road network G Point V_GIf there is road network distance | | q-p | | of node q, q and p on road network G not less than p to V_GIn the middle of The distance of any some p ' | | p '-p | |, then definition q is that p is relative to V_GFarthest neighbours, be designated as fn (p, V_G)；

Second definition module, for for all node V on given road network G_GWith the query set on road network G The multiple the most farthest neighbours of Q, definition q ∈ Q are all V_GMiddle distance q than in Q other the most remote point Set, i.e. BRFN (q, Q, V_G)={p|p∈V_G,fn(p,Q)=q};

Search module, for obtaining the multiple the most farthest neighbours of each query point q, i.e. p ∈ BRFN (q, Q, V_G), The multiple the most farthest neighbours obtaining each query point q include: use dijkstra's algorithm with each d ∈ V_GMake One extension is carried out for source point, until being accessed to a little in Q, if the institute that q is in Q is a little It is accessed to before all being traveled through, then the farthest neighbours of q not d, thus d is not belonging to the most farthest of q Neighbours；If other points that q is in Q are accessed to after all being traveled through not yet, it is determined that d is p, p∈BRFN(q,Q,V_G)。

Compared with prior art, the present invention passes through step one: for a certain node p on given road network G and All node V on road network G_GIf there is road network distance | | q-p | | of node q, q and p on road network G no Less than p to V_GDistance | | the p '-p | | of central any some p ', then definition q is that p is relative to V_GFarthest neighbours, It is designated as fn (p, V_G)；Step 2: for all node V on given road network G_GWith the query set Q on road network G, The multiple the most farthest neighbours of definition q ∈ Q are all V_GMiddle distance q than in Q other the collection of the most remote point Close, 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_GOne extension is carried out as source point, until being accessed to a little, if q is in Q in Q Institute is accessed to before a little all being traveled through, then the farthest neighbours of q not d, thus d is not belonging to the anti-of q To farthest neighbours；If other points that q is in Q are accessed to after all being traveled through not yet, it is determined that d is P, p ∈ BRFN (q, Q, V_G)；Step 4: repeating said steps three, until getting each query point q Multiple the most farthest neighbours, i.e. p ∈ BRFN (q, Q, V_G), it is possible on road network, fast search is to the list of query point Reversely neighbours.

Accompanying drawing explanation

Fig. 1 is multiple the most farthest neighbor adjacency problem (BRFN) example of one embodiment of the invention.

Detailed description of the invention

Understandable for enabling the above-mentioned purpose of the present invention, feature and advantage to become apparent from, below in conjunction with the accompanying drawings and The present invention is further detailed explanation for detailed description of the invention.

Embodiment one

The present invention provides a kind of and obtains the force search method of the most farthest multiple neighbours on road network, including:

Step S1, as it is shown in figure 1, for owning on a certain node p on given road network G and road network G Node V_GIf there is road network distance | | q-p | | of node q, q and p on road network G not less than p to V_GWhen In distance | | the p '-p | | of any some p ', then definition q is that p is relative to V_GFarthest neighbours, be designated as fn (p, V_G)；

Step S2, for all node V on given road network G_GWith the query set Q on road network G, definition The multiple the most farthest neighbours of q ∈ Q are all V_GMiddle distance q than in Q other the set of the most remote point, 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_GOne extension is carried out as source point, until Q In be accessed to a little till, if q in Q institute a little all traveled through before be accessed to, then The farthest neighbours of q not d, thus d is not belonging to the most farthest neighbours of q；If other some quilts that q is in Q All it is accessed to not yet after traversal, it is determined that d is p, p ∈ BRFN (q, Q, V_G)；Concrete, as generation The shortest path first of table, dijkstra's algorithm is proposed in nineteen fifty-nine by E.W.Dijkstra, and algorithm uses labelling Method from the beginning of source point, the point that the marked set of each extended range is nearest, thus ask and obtain known point Short path (can be found in document 1)；

Step S4, repeating said steps S3, until getting the multiple the most farthest neighbours of each query point q, I.e. p ∈ BRFN (q, Q, V_G).Concrete, by traveling through each node d ∈ V in the present embodiment_GCheck it It is whether the most farthest neighbours of query point q, performs dijkstra's algorithm with d for source point, if interviewed at q Ask that all nodes in front Q are the most accessed, it may be determined that p ∈ BRFN (q, Q, V_G)。

Embodiment two

The present invention also provides for the another kind of force search system obtaining neighbours the most farthest on road network, including:

First definition module, for for a certain node p on given road network G and all knots on road network G Point V_GIf there is road network distance | | q-p | | of node q, q and p on road network G not less than p to V_GIn the middle of The distance of any some p ' | | p '-p | |, then definition q is that p is relative to V_GFarthest neighbours, be designated as fn (p, V_G)；

Second definition module, for for all node V on given road network G_GWith the query set on road network G The multiple the most farthest neighbours of Q, definition q ∈ Q are all V_GMiddle distance q than in Q other the most remote point Set, i.e. BRFN (q, Q, V_G)={p|p∈V_G,fn(p,Q)=q};

Search module, for obtaining the multiple the most farthest neighbours of each query point q, i.e. p ∈ BRFN (q, Q, V_G), The multiple the most farthest neighbours obtaining each query point q include: use dijkstra's algorithm with each d ∈ V_GMake One extension is carried out for source point, until being accessed to a little in Q, if the institute that q is in Q is a little It is accessed to before all being traveled through, then the farthest neighbours of q not d, thus d is not belonging to the most farthest of q Neighbours；If other points that q is in Q are accessed to after all being traveled through not yet, it is determined that d is p, p∈BRFN(q,Q,V_G)。

The present invention passes through step one: for a certain node p on given road network G and all knots on road network G Point V_GIf there is road network distance | | q-p | | of node q, q and p on road network G not less than p to V_GIn the middle of The distance of any some p ' | | p '-p | |, then definition q is that p is relative to V_GFarthest neighbours, be designated as fn (p, V_G)；Step Rapid two: for all node V on given road network G_GWith the query set Q on road network G, definition q ∈ Q answers The most farthest neighbours are all V_GMiddle distance q than in Q other the set of the most remote point, 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_GMake One extension is carried out for source point, until being accessed to a little in Q, if the institute that q is in Q is a little It is accessed to before all being traveled through, then the farthest neighbours of q not d, thus d is not belonging to the most farthest of q Neighbours；If other points that q is in Q are accessed to after all being traveled through not yet, it is determined that d is p, p∈BRFN(q,Q,V_G)；Step 4: repeating said steps three, until getting answering of each query point q The most farthest neighbours, i.e. p ∈ BRFN (q, Q, V_G), it is possible on road network, fast search is reverse to the list of query point Neighbours.

Other detailed content of embodiment two specifically can be found in embodiment one, does not repeats them here.

In this specification, each embodiment uses the mode gone forward one by one to describe, and what each embodiment stressed is With the difference of other embodiments, between each embodiment, identical similar portion sees mutually.For For system disclosed in embodiment, owing to corresponding to the method disclosed in Example, so the comparison described is simple Single, relevant part sees method part and illustrates.

Professional further appreciates that, each example described in conjunction with the embodiments described herein Unit and algorithm steps, it is possible to electronic hardware, computer software or the two be implemented in combination in, for Clearly demonstrate the interchangeability of hardware and software, the most retouch in general manner according to function Composition and the step of each example are stated.These functions perform with hardware or software mode actually, depend on The application-specific of technical scheme and design constraint.Professional and technical personnel specifically should be able to be used for each Use different methods to realize described function, but this realization is it is not considered that exceed the model of the present invention Enclose.

Obviously, those skilled in the art can carry out various change and modification without deviating from the present invention to invention Spirit and scope.So, if the present invention these amendment and modification belong to the claims in the present invention and Within the scope of equivalent technologies, then the present invention is also intended to change and including modification include these.

Claims (2)

1. one kind obtains the force search method of the most farthest multiple neighbours on road network, it is characterised in that bag Include:

Step one: for a certain node p on given road network G and all node V on road network G_GIf, Road network distance | | q-p | | of node q, q and p is there is not less than p to V on road network G_GCentral any some p's ' Distance | | p '-p | |, then definition q is that p is relative to V_GFarthest neighbours, be designated as fn (p, V_G)；

Step 2: for all node V on given road network G_GWith the query set Q on road network G, definition The multiple the most farthest neighbours of q ∈ Q are all V_GMiddle distance q than in Q other the set of the most remote point, 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_GOne extension is carried out as source point, until Q In be accessed to a little till, if q in Q institute a little all traveled through before be accessed to, then The farthest neighbours of q not d, thus d is not belonging to the most farthest neighbours of q；If other some quilts that q is in Q All it is accessed to not yet after traversal, it is determined that d is p, p ∈ BRFN (q, Q, V_G)；

Step 4: repeating said steps three, until getting the multiple the most farthest neighbours of each query point q, I.e. p ∈ BRFN (q, Q, V_G)。

2. one kind obtains the force search system of the most farthest multiple neighbours on road network, it is characterised in that including:

First definition module, for for a certain node p on given road network G and all knots on road network G Point V_GIf there is road network distance | | q-p | | of node q, q and p on road network G not less than p to V_GIn the middle of The distance of any some p ' | | p '-p | |, then definition q is that p is relative to V_GFarthest neighbours, be designated as fn (p, V_G)；

Second definition module, for for all node V on given road network G_GWith the query set on road network G The multiple the most farthest neighbours of Q, definition q ∈ Q are all V_GMiddle distance q than in Q other the most remote point Set, i.e. BRFN (q, Q, V_G)={p|p∈V_G,fn(p,Q)=q};

Search module, for obtaining the multiple the most farthest neighbours of each query point q, i.e. p ∈ BRFN (q, Q, V_G), The multiple the most farthest neighbours obtaining each query point q include: use dijkstra's algorithm with each d ∈ V_GMake One extension is carried out for source point, until being accessed to a little in Q, if the institute that q is in Q is a little It is accessed to before all being traveled through, then the farthest neighbours of q not d, thus d is not belonging to the most farthest of q Neighbours；If other points that q is in Q are accessed to after all being traveled through not yet, it is determined that d is p, p∈BRFN(q,Q,V_G)。