CN101467150A - Nearest search on adaptive index with variable compression - Google Patents
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Abstract
A search system can search nodes of a tree to find the object stored in the tree that is nearest to a position input by the user. The tree can be constructed using object keys with interlaced coordinates such that nodes in the tree correspond to a bounding box that bounds a subset of objects. The search algorithm can find the nearest object to a position.
Description
Claim of priority
The application's case is advocated the right of priority of following common application case co-pending, the full text of described application case all is incorporated herein: people such as Cai's Boris Kuznetsov are in the 60/806th, No. 366 U.S. Provisional Application case (attorney docket is TELA-07780US0) that is entitled as " adaptive index (ADAPTIVE INDEX WITH VARIABLE COMPRESSION) with variable compressive " of application on June 30th, 2006; Cai's Boris Kuznetsov is in the 60/806th, No. 367 U.S. Provisional Application case (attorney docket is TELA-07781US0) of being entitled as of on June 30th, 2006 application " to the nearest search (NEAREST SEARCH ON ADAPTIVEINDEX WITH VARIABLE COMPRESSION) of adaptive index with variable compressive "; People such as Cai's Boris Kuznetsov are in the 11/770th, No. 058 novel application case of U.S. utility (attorney docket is TELA-07780US1) that is entitled as " adaptive index (ADAPTIVE INDEX WITH VARIABLE COMPRESSION) with variable compressive " of application on June 28th, 2007; And Cai's Boris Kuznetsov is in the 11/770th, No. 426 novel application case of U.S. utility (attorney docket is TELA-07781US1) of being entitled as of on June 28th, 2007 application " to the nearest search (NEAREST SEARCH ON ADAPTIVE INDEX WITH VARIABLE COMPRESSION) of adaptive index with variable compressive ".
Technical field
Do not have
Background technology
Many application programs can use the spatial data of being stored to provide the space search service to the user.Described application program can comprise and moving or fixing mapped system that it can comprise map reproduction, spatial object search, route searching, direction and location.
Such situation usually occurs, the user wishes to be positioned at object in the given coordinate system and obtains further information about described object.In having the complex database of many objects, can be difficult to find fast the object of close input position.Especially, be subjected under the situation of memory limitations (as in the mobile navigation device) in system.
Summary of the invention
Do not have
Description of drawings
Fig. 1 illustrates the system based on map that uses search of the present invention.
Fig. 2 A is to the structure of the tree of 2E explanation one embodiment of the present of invention.
Fig. 3 is the process flow diagram of the searching method of one embodiment of the present of invention.
Fig. 4 A is to the qualification frame of the node of an example of 4B explanation.
Fig. 5 A is to the exemplary search of an embodiment of 5F explanation.
Fig. 6 illustrates that node wherein contains the example of the indication (for example getting rid of information) of other search criterion.
Embodiment
One embodiment of the present of invention are a kind of computer-implemented methods, and its node that comprises search tree 102 is to obtain the search system near object.Can construct described tree at a group objects, each has the volume coordinate key word described object, makes node in the described tree corresponding to the qualification frame of the child group that limits these objects.Search can find a position near object.
In one embodiment, the qualification frame that is positioned at the tree node of root below only covers the zone that wherein has object.But the storage of this optimization objects and to potential near the retrieval of object.Similarly, in one embodiment, the qualification frame of child node only covers the zone that wherein has object.The qualification frame of root node can make it not comprise some zone with related object.
In one embodiment, can use latitude and longitude coordinate.For instance, the numeral of latitude and longitude coordinate can be interlocked in the character string key word, as described below.
The degree of accuracy of encoded object keywords all increases at each node on the path from root to leaf.The scope of the qualification frame that is associated reduces from the root to the leaf.Described scope can be that the coordinate key word system is intrinsic.For instance, scope can be the parasang under the pinpoint accuracy of key word at assigned direction.Hereinafter an example of the staggered coordinate system of the warp of Lun Shuing has such qualification frame scope, and it all reduces ten times for each child node on any coordinate direction.
In alternate embodiment, can use the value range of being stored.
In one embodiment, leaf node can point to a plurality of objects.Described tree can reach maximum leaf node to produce the number that trends towards making the object in the leaf based on given standard through structure.In one embodiment, the pruning standard of regulation is that each tree node has several objects at least in its offspring, otherwise that branch can be pruned away and object is distributed to leaf node.
Can keep the maximum search radius value with limit search.The search radius value can reduce based on limiting frame information.Can use node to limit frame and calculate minimum and ultimate range from a position to each node.Can several nodes be got rid of outside considering based on the maximum search radius value.In an example, can ignore it and limit the node of the minor increment of frame distance one position greater than the maximum search radius.
The object keywords information of node can be enough to coding and limit frame corner location and scope.In an example, when coordinate information was staggered, the corner of the qualification frame of node (for example corner, lower-left) can be determined by the coordinate through release of an interleave, and can determine the scope of the qualification frame of each coordinate from the composition of coordinate.
Described computer-implemented method can be the part of map system 100 or navigational system.Object can comprise spatial object, for example highway section, focus (POI) or other spatial object.Spatial object can be by one or more coordinate indications.
One embodiment of the present of invention are the systems 100 that comprise application program 104.Application program 104 can comprise in order to obtain the interface of position.But the search of application program usage space, the node of its search tree is to obtain near object.Tree 102 can be based on the spatial key with coordinate coding, makes node in the described tree corresponding to the qualification frame of the child group that limits these objects.Described search can find a position near object.
How following providing can use the object coordinate to create the example of tree:
In order to create key word from latitude and longitude:
1. the decimal system number of degrees are converted to rounded coordinate, wherein the circumference of the bit representation earth of given number
2. coordinate is moved in the positive space
3. change each integer into character string
4. fill out each character string in advance so that its equal in length with " 0 "
5. become keyword strings by the tens digit of latitude and longitude is interlocked and form search key
The chosen latitude character string contains " 00123 "
The chosen longitude character string contains " 00078 "
Gained will be " 0000102738 " through staggered character string key word
Can use this spatial key to make up coordinated indexing a.The degree of accuracy of key word can all increase by each node on the path from root to leaf.
Optimize for storage and retrieval, can be with the leaf node key word brachymemma in the index so that it equal the key word of its parent, thereby force leaf to merge.This can need to search for to follow in final step selects near object the object reference of object memories.
Can implement nearest search to setting 102.Can recover the qualification frame of each node on the searching route from the spatial key of node.Limit frame in order to retrieve node at space search:
But the prefix of each tree node storage key wherein has the key word prefix of minimum degree of accuracy and has the key word prefix of pinpoint accuracy at Ye Chu at the root place.In having the adaptive index of variable compressive, these key word prefixes can be through reduction so that the whole key word of each node be the cascade of all the key word prefixes from root to described node.This cascade then produces the whole key word of described node; The corner, lower-left and the scope of the qualification frame of the described node of key word codified of each node.
In one embodiment, for the corner, lower-left of computing node and the spatial dimension of its qualification frame:
With the spatial key release of an interleave of node, add " 0 " of losing, reach the gained latitude and the corner, longitude string representation lower-left of complete length (being 5 in this example).
A) in an example, suppose that the node key word is " 0000102 "
Latitude is " 00120 ", wherein " 0 " of Tian Jiaing mean described node the latitude of filial generation between 120 to 129, so the scope of the latitude of node is 10 to 1 powers.
Longitude is " 00000 ", wherein " 00 " of Tian Jiaing mean described node the longitude of filial generation between 0 to 99, so the scope of the longitude of node is 10 to 2 powers.
B) in another example, suppose that the node key word is " 00001027 "
Latitude be the latitude of filial generation of " 00120 " and described node between 120 to 129, so the scope of the latitude of node is 10 to 1 powers.
Longitude be the longitude of filial generation of " 00070 " and described node between 70 to 79, so the scope of the longitude of node is 10 to 1 powers.
In order to finish calculating, character string latitude and longitude are converted to rounded coordinate and integer is turned back in the original coordinates space the corner, lower-left of node.
Can extend according to corner, the lower-left integer latitude and longitude coordinate in corner, lower-left and space comes computing node to limit frame.
Fig. 2 A is to the structure of the tree of an example of 2E explanation.
Fig. 2 A shows exemplary map, and wherein the highway section point is shown as X.As shown in Fig. 2 B, can be key word with reference to the latitude of point coordinate and longitude are staggered.Described key word can be used for constructing the node tree shown in Fig. 2 C.The part of the key word at each node place can be used for the qualification frame of decode node in the above described manner.In the example of Fig. 2 C, node 210 (0000102738) is corresponding to the qualification frame 202 of Fig. 2 A; Node 212 (000010273) is corresponding to the qualification frame 204 of Fig. 2 A; Node 214 (00001027) is corresponding to the qualification frame 206 of Fig. 2 A.
But object in the leaf node 210 point at objects storage arrangements 216 or direct storage object.Object can contain title and out of Memory, and one or more coordinates.In an example, the object coordinate can be highway section mid point or terminal point.Therefore pointer can be used for using specific latitude and longitude coordinate limiting frame 202 anchored objects.
As " the adaptive index " of on June 30th, 2006 application with variable compressive and be incorporated herein by reference the 60/806th, described in No. 366 U.S. patent application case (corresponding to attorney docket TELA-07780US0), leaf node can contain a plurality of object references.In the example of Fig. 2 D, leaf node points to two objects that limit in the frame 204.In the example of Fig. 2 E, leaf node points to 26 objects that limit in the frame 206.
Exemplary search to node tree is described below:
Space search to the index of self-adapting compressing
Given some P with coordinate latitude, longitude:
Read root node r and recover it and limit frame
Calculate the maximum radius maxR from P to the highest distance position in the root
Rreturn value can be tuple (object, distance); It can calculate by following program:
(object is to the distance of object)=find near object () (tree node, maxR)
If node is a leaf, then
Retrieval is near object and " to the distance of object ";
If " to the distance of object "＜maxR then upgrades:
MaxR=" to the distance of object "
Return (object is to the distance of object)
Read child node
At each child node, calculate the distance of P: minD and maxD,
To have minD〉filial generation of maxR gets rid of outside considering
Below root r, the initial child node of considering is:
(a，minD，maxD)
(f，minD，maxD)
(h，minD，maxD)
MaxR is reduced to the minimum value of the maxD of filial generation
According to minD subarray is sorted
When subarray is not sky and min (minD of filial generation)＜maxR)
Selection has the child node of minimum minD;
(object is to the distance of object)=find near object (child node, maxR)
Return (object is to the distance of object)
Fig. 3 shows the example of the process flow diagram that exemplary search is described.
The qualification frame of the tree of Fig. 4 A exploded view 4B.Fig. 4 A shows how the qualification frame of child node is embedded in the parent node.The size of qualification frame also not in scale.
Fig. 5 A shows exemplary search to 5F.Can import to determine a some P according to the user, for example select, select or according to another input medium according to touch-screen according to cursor.Also can from GPS (GPS) or other position determination system, obtain some P.Fig. 5 A to the step shown in the 5F show the search tree structure with find a P near the mode of object.
In Fig. 5 A (corresponding to the step 302 of Fig. 3), maxR is defined as the distance in the corner farthest of qualification frame from a P to root node.Because root (node r) is not a leaf node, so in the step 304 of Fig. 3, obtain the child node (node a, f, h) of described node.
Then can obtain the minimum and maximum distance (step 306) of each qualification frame of child node.Shown in Fig. 5 A, ultimate range can be corresponding to the distance of the line from a P to the corner farthest that limits frame.Minor increment can be (if possible) from a P along latitude or longitude to the straight line of the side that limits frame, perhaps if there is no along this type of line of latitude or longitude, can be the line in the most close corner that limits frame.
If maxR, then can be set at described maxR the shortest person (this is the step 308 of Fig. 3) among the maxD of child node less than current maxR.Can get rid of the child node of its minD greater than maxR.In Fig. 5 B, can ignore node h and its filial generation.The order of the minD value of can rising progressively is arranged other node (step 310 of Fig. 3) in tabulation, make most probable contain and examined at first near the node of object.Therefore, this moment, tabulation can be { a, f}.
In Fig. 5 C, the child node of check node a.In Fig. 5 D, maxR is set at the maxD that limits frame b.Tabulation this moment is { b, f}.
In Fig. 5 E, the filial generation of check node b, and tabulation becomes { e, f}.
In Fig. 5 F, because node e is a leaf node, so the object among the check node e is to find the most close object of a P.Node e can have the pointer of the object in many point at objects storeies.Can to its test with find among the node e near object.This is corresponding to the step 320 of Fig. 3.Because the distance that arrives described object is less than current maxR, so maxR is set at the distance of described object.This moment, row showed as { f}.
Then check node f and find that it has child node g.Node g has minD〉maxR, so method finishes and the object determining in node e, to find in near object for to described position near object.Can be in map display, menu or give the user indication to this object via the user interface of a certain other type.For instance, can show road name and can on map, highlight described road to the user, or can export road name via the Text To Speech Aristogrid.
In one embodiment, tree node can be stored the indication of other search criterion.Nearest search can use described indication to implement the search of n dimension.For instance, in one embodiment, can come filtered search by classification.Described indication can comprise comprising or be not included in the indication of the classification in the qualification frame of node.
For instance, do not indicate the node that its filial generation, has the restaurant to getting rid of from search tree to the search in the most close restaurant of a position.
In one embodiment, node can be stored the POI classification and gets rid of information to simplify and to quicken search to particular category.Eliminating information can be indicated in the qualification frame of described node does not have object in described classification.
Fig. 6 shows an example.In this example, if the search of the tree fragment that this place is showed is aimed at the restaurant, so described search can stop at node 602 places, and if search be aimed at the refuelling station, search can stop at 604 places so.Indication (for example getting rid of information) to other search criterion can be implemented when creating node tree.
Technician as computer realm will understand, can use the special digital computer of programming according to teaching of the present invention or the conventional general-use of microprocessor to implement an embodiment.Technician as software field will understand that skilled programming personnel can easily prepare appropriate software coding based on teaching of the present invention.As be appreciated by those skilled in the art that, also can implement the present invention by the preparation integrated circuit or by the appropriate network of the conventional assembly circuit that interconnects.
An embodiment comprises a kind of computer program, its on it/wherein store the medium of instruction, described instruction can be used for programmed computer to carry out any one in the feature that exists herein.Medium can include but not limited to the dish of any kind, comprise floppy disk, CD, DVD, CD-ROM, microdrive and magneto-optic disk, ROM, Ram, EPROM, EEPROM, DRAM, be suitable for being stored in instruction and/or the medium of data or the flash memory of device stored on any one in the computer-readable media, the present invention includes be used to control general/specialized computer or microprocessor hardware both and be used to make computing machine or microprocessor can utilize result of the present invention and human user or other mechanism to carry out interactive software.This type of software can include, but are not limited to device driver, operating system, execution environments/containers and user application.
Previous description to the preferred embodiment of the present invention is provided for the purpose of illustration and description.Do not wish that this is detailed or limit the invention to the precise forms that disclosed.Those possessing an ordinary skill in the pertinent arts will understand many modifications and variations.For instance, can substitute order and carry out the step of in the embodiments of the invention that disclosed, carrying out, can omit some step, and can add additional step.Selecting and describing described embodiment is for best interpretations principle of the present invention and practical application thereof, and then makes others skilled in the art can understand various embodiment of the present invention and the various modifications that are suitable for desired special-purpose.Wish that scope of the present invention is defined by claims and equivalent thereof.
Claims (24)
1. computer-implemented method, it comprises:
Search system, the node of its search tree is to obtain near object, use the object keywords of encoding coordinate to construct described tree, make that the node in the described tree is organized the qualification frame of described object corresponding to limiting a son, searching algorithm finds the described near object of a position; The described qualification frame that wherein is positioned at the described tree node of root below only covers the zone that wherein has object, and wherein said search will have some node that limits frame eliminating outside considering.
2. computer-implemented method according to claim 1, wherein the degree of accuracy of encoded object keywords each node on the path from described to leaf all increases.
3. computer-implemented method according to claim 1, wherein said coordinate comprises latitude and longitude.
4. computer-readable media according to claim 1, wherein for example by means of corner location and scope, the object keywords information of node is enough to encode, and it limits frame.
5. computer-implemented method according to claim 1, wherein staggered described coordinate information.
6. computer-implemented method according to claim 5 wherein by the corner, lower-left that limits frame of determining described node through the coordinate of release of an interleave, and is determined the described scope of the described qualification frame of each coordinate from the composition of described coordinate.
7. computer-implemented method according to claim 1, wherein the node storage is to the indication of other search criterion.
8. computer-implemented method according to claim 7, wherein said indication to other search criterion comprises the indication to the classification of the object in the qualification frame that is not included in node.
9. computer-implemented method according to claim 8, wherein said indication to other search criterion comprises the indication to the classification of the object in the qualification frame that is included in node.
10. computer-implemented method according to claim 1, wherein most of leaf nodes point to a plurality of objects.
11. computer-implemented method according to claim 1, wherein said tree structure trend towards making the number of the object that is associated with described leaf node reach maximum based on given standard.
12. computer-implemented method according to claim 1, wherein said method is kept the maximum search radius value, and based on described maximum search radius some nodes is got rid of outside considering.
13. computer-implemented method according to claim 1, wherein said method are kept the minor increment to a position of node, and use described minor increment that lowest distance value is got rid of outside considering greater than the node of described maximum search radius.
14. computer-implemented method according to claim 1 wherein uses the qualification frame of described node to calculate the minimum and the ultimate range to a position of described node.
15. computer-implemented method according to claim 1, wherein said object comprises spatial object.
16. computer-implemented method according to claim 15, wherein said spatial object comprises the map geometric characteristic.
17. computer-implemented method according to claim 15, wherein said spatial object comprises focus.
18. computer-implemented method according to claim 1, wherein said computer-implemented method are the parts of mapped system.
19. a system, it comprises:
Application program, it comprises in order to obtain the interface of position; Wherein said application program is used search system, the node of described search system search tree with acquire described position near object, described tree is based on the search key with staggered coordinate, make node in the described tree corresponding to the qualification frame of giving in the position fixing, the described near object of a position found in described search, the described qualification frame that wherein is positioned at the described tree node of root below only covers the zone that wherein has object, and wherein said search will have some node that limits frame eliminating outside considering.
20. system according to claim 19, wherein said position is based on that cursor is selected and obtains.
21. system according to claim 19, wherein said position is based on that the user touches, user location, user speech input or obtain by other user interface member.
22. system according to claim 19, wherein said application program comprises map display.
23. a computer-implemented system, it comprises:
Search system, the node of its search tree is to obtain near object, use the object keywords of encoding coordinate to construct described tree, make node in the described tree corresponding to the qualification frame that limits a sub-group objects, the described near object of a position found in described search;
The overall maximum search radius value and the minor increment of wherein said some node of system held, and wherein said system uses described minor increment that minor increment is got rid of outside considering greater than the node of described maximum search radius.
24. a computer-implemented method, it comprises:
Search system, the node of its search tree is to obtain near spatial object, use the object keywords of encoding coordinate to construct described tree, make the node in the described tree organize the qualification frame of described object corresponding to limiting a son, searching algorithm finds the described near spatial object of a position, the described qualification frame that wherein is positioned at the described tree node of root below only covers the zone that wherein has spatial object, and wherein said method is kept the maximum search radius value, and based on described maximum search radius some nodes are got rid of outside considering, described search radius value reduces based on limiting frame information.
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US80636706P | 2006-06-30 | 2006-06-30 | |
| US60/806,367 | 2006-06-30 | ||
| US60/806,366 | 2006-06-30 |
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| CN101467150A true CN101467150A (en) | 2009-06-24 |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101964808A (en) * | 2010-07-09 | 2011-02-02 | 北京哈工大计算机网络与信息安全技术研究中心 | Node searching and positioning system in internet of thing |
| CN102087666A (en) * | 2011-01-30 | 2011-06-08 | 华东师范大学 | Indexes based on covering relationship between nodes and key words, constructing method and query method thereof |
| CN105955982A (en) * | 2016-04-18 | 2016-09-21 | 上海泥娃通信科技有限公司 | Method and system for information sequence feature encoding and retrieval |
-
2007
- 2007-06-28 CN CNA2007800221233A patent/CN101467150A/en active Pending
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101964808A (en) * | 2010-07-09 | 2011-02-02 | 北京哈工大计算机网络与信息安全技术研究中心 | Node searching and positioning system in internet of thing |
| CN101964808B (en) * | 2010-07-09 | 2013-03-27 | 北京哈工大计算机网络与信息安全技术研究中心 | Node searching and positioning system in internet of thing |
| CN102087666A (en) * | 2011-01-30 | 2011-06-08 | 华东师范大学 | Indexes based on covering relationship between nodes and key words, constructing method and query method thereof |
| CN102087666B (en) * | 2011-01-30 | 2012-10-31 | 华东师范大学 | Indexes based on covering relationship between nodes and key words, constructing method and query method thereof |
| CN105955982A (en) * | 2016-04-18 | 2016-09-21 | 上海泥娃通信科技有限公司 | Method and system for information sequence feature encoding and retrieval |
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