CN109408543A - A kind of intelligence relationship net sniff method - Google Patents
A kind of intelligence relationship net sniff method Download PDFInfo
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Abstract
The invention proposes a kind of intelligence relationship net sniff methods, pass through setting scoring and average index, each relation chain can be scored and is averaging index, the scoring and average index of synthetic relationship chain select between two users that path is most short, the highest path of stability；It is fast according to search index array element speed by using the form of storage of array, mass data can be stored, it is convenient according to index traversal array, can be with the relation chain between quick search user, and the record of inquiry is stored, guarantee that data are not lost；Entire method mainly passes through storage of array and loops through array, inquire all relation chains between user, fractionation storage is carried out to each user in relation chain, relationship rank between two users in marriage relation library and relationship type library inquiry, other and for relation chain the scoring of all relative degrees, the relationship scoring and average index for calculating every relation chain, search path most short, most firm between two users.
Description
Technical field
The present invention relates to field of information processing more particularly to a kind of intelligence relationship net sniff methods.
Background technique
Personal relationship has found the method for referring to automatic associated relation between finder and people in Next Generation Internet, will
Huge user and frequency of use can be brought to internet, be the important hand for embodying internet new technology and economic value
Section.The basic skills that the path between people and people is personal relationship's discovery is searched, target is to not recognize directly at two
People between find a paths, the user in the path behaves, and the two neighboring relationship artificially recognized mutually in the path passes through
The introduction of these people can connect the people that two do not recognize directly, so that two people not recognized directly can
Find a kind of mode for establishing connection.
It is the important method in this field that personal relationship is searched based on path, and target is that first community network is built
Mould becomes figure, indicates people with user, indicates the relationship between people and people with the side of connection user.In most methods, look into
The relationship looked between people and people is to reach target by searching two user paths that may be present in figure.
There are following some limitations in the personal relationship's discovery method having proposed: first, only account for " minimal path
The simple case of diameter ", that is to say, that look only for the shortest paths of length, the shortest path of this length is likely to be tool
Some least paths in side, it is also possible to be according to while weight and while the shortest path that calculates of number.Second, lack
Path scoring can remove the lower path of score when carrying out mulitpath lookup according to path appraisal result,
The efficiency of raising system, this is extremely important when applying in large-scale community network.
Summary of the invention
It is closed in view of this, the intelligence that path between two users is most short, most firm can be selected the invention proposes one kind
It is net sniff method.
The technical scheme of the present invention is realized as follows: the present invention provides a kind of intelligence relationship net sniff method, packet
Include following steps:
S101, each user are connected to form relationship library according to business datum, determine the relationship type of each user and neighboring user
And the corresponding relationship rank of relationship type, relationship type, relationship rank and the relationship between two users are illustrated into corresponding storage
In relationship type library, association user in relationship library is defined as start, associated user is defined as end；
S102, the path between two users is calculated using recursive principle, path all between two nodes will be connected to
It finds out, the array $ result of relation chain and retrieval record between definition two nodes of storage, the specific method is as follows:
S201, it defines a variable $ str and for storing the array $ T1 of user, start=$ is retrieved in relationship library
The relation chain of str end=$ str is stored in array $ T1, and an association user is defined as $ other in array $ T1, with
Its corresponding associated user is defined as $ target, and relationship type is defined as $ linktype；
S202, S203 is continued to execute if array $ T1 has value, executes S204 if $ T1 void value；
S203, array $ T1 is looped through, relation chain all between relational users and associated user is found out
Come；The specific method is as follows:
S301, associated user's value that the relation chain other end is taken out in the data of current key assignments are assigned to association user $
other；
S302, definition store the array $ n of current key assignments record, according to $ n=$ n+ ' $ other | the format of $ linktype '
Association user $ other and relationship type $ linktype are configured to the record array $ n of current key assignments；
Whether S303, another end subscriber for judging relation chain are that target is associated user target, if other=
Target then finds target, executes 304；If $ other！=$ target, then execute S301；
S304, the record array $ n of current key assignments is labeled as a completeness relation chain, and is stored in retrieval record array $
In result；
S204, the lookup for jumping out current level；
S103, the relation chain being retrieved that would cycle through path between two users are recorded in array $ result,
It scores all relation chains between two users, the method for scoring are as follows: according to the every two adjacent use in relation chain
The corresponding relationship rank of family type search, by the relation chain be defined as the pass there are two the sum of the relationship rank of neighboring user
The scoring of tethers, the specific method is as follows；
The relation chain stored under S401, the current key assignments of definition is $ r [n], and each user splits in relation chain $ r [n],
After fractionation, the user after fractionation is defined as v, the user class offset of two neighboring user is defined as v_linktype, each
V includes user's name and $ v_linktype, and $ v is stored in the record array $ n of current key assignments；
The variable $ point=0 that S402, definition storage relation chain score；
S403, the record array $ n for looping through current key assignments, the $ v_linktype in $ v is extracted, and according to
Relationship type and relationship rank corresponding relationship in relationship type library, extract relationship class value, by the relative degree in the relation chain
Not the sum of value scoring for being defined as the relation chain；
S501, the value of v is broken up by user's name and v_linktype again, obtains the relation object offset of relation chain
v_linktype；
S502, relationship grade variable val is defined, the note of linktype=v_linktype is found in relationship type library
Record value, and the relationship class value in relation chain is assigned to variable val；
S503, the scoring defined in relation chain are $ point, are added up in the relation chain according to $ point=$ point+ $ val
Scoring $ point, will scoring $ point return to array $ result；
S504, circulation execute S501~S504, and all relation chains between two users are scored, and scoring is tied
Fruit is stored in array $ result；
S104, in all search results, in the completeness relation chain of return and the record of score data, according to relation chain
Length and the height of scoring be ranked up；
S105, definition relationship chain length are count (n), and the average index for defining relation chain is value, according to formula:
$ value=$ point/count ($ n), the average index $ value of calculated relationship chain, score in marriage relation chain and relation chain
Average index $ value, select path most short, most firm between two users.
On the basis of above technical scheme, it is preferred that relationship chain length is shorter in S104, then the scoring of relation chain is got over
Height, representation relation are more intimate firm.
On the basis of above technical scheme, it is preferred that measure the firm journey of a relation chain according to average value $ value
Degree, average value is high, then the feasibility of relation chain is high.
A kind of intelligence relationship net sniff method of the invention has the advantages that compared with the existing technology
(1) by setting scoring and average index, all relation chains between two users can be found, and right
Each relation chain is scored and is asked the average index of every relation chain, the scoring and average index of synthetic relationship chain, choosing
Path is most short between two users out, the highest path of stability；
(2) fast according to search index array element speed by using the form of storage of array, mass data can be stored,
It is convenient according to index traversal array, can be with the relation chain between quick search user, and the record of inquiry is stored, guarantee data not
It loses；
(3) entire method mainly passes through the technology of storage of array and variable assignments, loops through array, and inquire user
Between all relation chains, fractionation storage, marriage relation library and relationship type library inquiry are carried out to each user in relation chain
Relationship rank between two users, other and for relation chain the scoring of all relative degrees, the relationship for calculating every relation chain are commented
Point and average index, search most short, most firm path between two users.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of invention for those of ordinary skill in the art without creative efforts, can be with
It obtains other drawings based on these drawings.
Fig. 1 is a kind of flow chart of intelligence relationship net sniff method of the invention；
Fig. 2 is that relation chain all between user in relationship library is retrieved in a kind of intelligence relationship net sniff method of the invention
Flow chart；
Fig. 3 is the flow chart that the relation chain between two users is retrieved in a kind of intelligence relationship net sniff method of the invention；
Fig. 4 is in a kind of intelligence relationship net sniff method of the invention to two in certain relation chain between two users
The flow chart of neighboring user relationship type；
Fig. 5 is in a kind of intelligence relationship net sniff method of the invention to the scoring of certain relation chain between two users
Flow chart；
Fig. 6 is the relationship library part table built in a kind of intelligence relationship net sniff method of the invention；
Fig. 7 is the part table that relationship type is built in a kind of intelligence relationship net sniff method of the invention；
Fig. 8 is that relation chain and the record to relation chain scoring are retrieved in a kind of intelligence relationship net sniff method of the invention
A part of table.
Specific embodiment
Below in conjunction with embodiment of the present invention, the technical solution in embodiment of the present invention is carried out clearly and completely
Description, it is clear that described embodiment is only some embodiments of the invention, rather than whole embodiments.Base
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts all
Other embodiments shall fall within the protection scope of the present invention.
As shown in Figure 1, a kind of intelligence relationship net sniff method of the invention comprising following steps:
S101, each user are connected to form relationship library according to business datum, determine the relationship type of each user and neighboring user
And the corresponding relationship rank of relationship type, relationship type, relationship rank and the relationship between two users are illustrated into corresponding storage
In relationship type library, association user in relationship library is defined as start, associated user is defined as end；
S102, the path between two users is calculated using recursive principle, path all between two nodes will be connected to
It finds out, the array $ result of relation chain and retrieval record between definition two nodes of storage, as shown in Fig. 2, specific method
It is as follows:
S201, it defines a variable $ str and for storing the array $ T1 of user, start=$ is retrieved in relationship library
The relation chain of str end=$ str is stored in array $ T1, and an association user is defined as $ other in array $ T1, with
Its corresponding associated user is defined as $ target, and relationship type is defined as $ linktype, by taking user A to user E as an example,
A relation chain between middle user A to user E is A-W-C-M-E, and the relation object offset between user A and user W is 4, is used
Relationship type between family W and user C is 3, and the relationship type between user C and user M is 2, between user M and user E
Relationship type is 1, then in the relation chain of user A to user E, user A is defined as $ other, and user E is defined as $
target；
S202, S203 is continued to execute if array $ T1 has value, executes S204 if $ T1 void value；
S203, array $ T1 is looped through, relation chain all between relational users and associated user is found out
Come；As shown in figure 3, the specific method is as follows:
S301, associated user's value that the relation chain other end is taken out in the data of current key assignments are assigned to association user $
other；
S302, definition store the array $ n of current key assignments record, according to $ n=$ n+ ' $ other | the format of $ linktype '
Association user $ other and relationship type $ linktype are configured to the record array $ n of current key assignments, with user A to user E
Between a relation chain for, the data assembly format of $ r [n] are as follows: A | 0-W | 4-C | 3-M | 2-E | 1；
Whether S303, another end subscriber for judging relation chain are that target is associated user target, if other=
Target then finds target, executes 304；If $ other！=$ target, then execute S301；
S304, the record array $ n of current key assignments is labeled as a completeness relation chain, and is stored in retrieval record array $
In result；
S204, the lookup for jumping out current level；
S103, the relation chain being retrieved that would cycle through path between two users are recorded in array $ result,
It scores all relation chains between two users, the method for scoring are as follows: according to the every two adjacent use in relation chain
The corresponding relationship rank of family type search, by the relation chain be defined as the pass there are two the sum of the relationship rank of neighboring user
The scoring of tethers, as shown in figure 4, the specific method is as follows:
The relation chain stored under S401, the current key assignments of definition is $ r [n], and each user splits in relation chain $ r [n],
After fractionation, the user after fractionation is defined as v, the user class offset of two neighboring user is defined as v_linktype, each
V includes user's name and $ v_linktype, $ v is stored in the record array $ n of current key assignments, between user A to user E
A relation chain for, score by [A-W] [W-C] [C-M] [M-E], r [n] relation chain broken up with '-' for unit
It is stored in array $ n, the code of realization is: $ n=explode ("-", $ r [n]), by the A after breaing up | 0, W | 4, C | 3, M | 2 and E
| in 1 deposit array $ n；
The variable $ point=0 that S402, definition storage relation chain score；
S403, the record array $ n for looping through current key assignments, the $ v_linktype in $ v is extracted, and according to
Relationship type and relationship rank corresponding relationship in relationship type library, extract relationship class value, by the relative degree in the relation chain
Not the sum of value scoring for being defined as the relation chain, methods of marking are as shown in Figure 5；
S501, the value of v is broken up by user's name and v_linktype again, obtains the relation object offset of relation chain
The value of v is broken up again with " | " for unit, is obtained by taking a relation chain between user A to user E as an example by v_linktype
The types value for obtaining relation chain, is assigned to variable $ v_linktype for types value, the method is as follows:
$ v_linktype=explode (" | ", $ v)；
$ v_linktype=$ v_linktype [1]；
I.e. by W | 4 are separated into W and 4, obtain the relation object offset v_linktype=4 between user A and user W, successively
Analogize, A | 0, C | 3, M | 2 and E | 1 with the separation of identical principle, wherein A | and what the 0 of 0 represented is the pass of user A oneself and oneself
System, i.e. user A retrieve user A oneself, and corresponding relationship rank is 0；
S502, relationship grade variable val is defined, the note of linktype=v_linktype is found in relationship type library
Record value, and the relationship class value in relation chain is assigned to variable val, a relation chain between user A to user E is A |
0-W | 4-C | 3-M | 2-E | 1, relationship type 0-4-3-2-1, corresponding relationship rank corresponds to 0-6-7-8-9；
S503, the scoring defined in relation chain are $ point, are added up in the relation chain according to $ point=$ point+ $ val
Scoring $ point, will scoring $ point return to array $ result, i.e. A between A to user E | 0-W | 4-C | 3-M | 2-E |
The scoring of 1 relation chain is 0+6+7+8+9=30；
S504, circulation execute S501~S504, and all relation chains between two users are scored, and scoring is tied
Fruit is stored in array $ result；
S104, in all search results, in the completeness relation chain of return and the record of score data, according to relation chain
Length and the height of scoring be ranked up；
S105, definition relationship chain length are count (n), and the average index for defining relation chain is value, according to formula:
$ value=$ point/count ($ n), the average index $ value of calculated relationship chain, score in marriage relation chain and relation chain
Average index $ value, select path most short, most firm between two users.
Fig. 6 and Fig. 7 is respectively relationship library and relationship type library, and relationship library and relationship type library are one-to-one relationships,
The value in relationship library and relationship class value are available data, no longer burdensome herein, wherein in Fig. 6, star association user is array
In associated user, end be associated user be in array be associated user, linktype relationship type is between two users
Relationship type, in Fig. 7, the linktype relationship type of linktype relationship type and Fig. 6 are the same, each linktype
Relationship type corresponds to a relationship rank, and relationship rank is high, and relationship explanation in the present invention is more intimate, such as relationship rank
It is lineal relative that the relative degree that value is 9, which is not mentionleted alone bright, and such as set membership, relationship illustrates and relationship description is saying to relationship
It is bright.
Fig. 8 is the scoring for traversing relation chain and relation chain that array is inquired between two users, such as the starting point of relation chain
For A, terminal B, relation chain A-W-R-M, relation chain scoring is 34.
The foregoing is merely better embodiments of the invention, are not intended to limit the invention, all of the invention
Within spirit and principle, any modification, equivalent replacement, improvement and so on be should all be included in the protection scope of the present invention.
Claims (3)
1. a kind of intelligence relationship net sniff method comprising following steps:
S101, each user are connected to form relationship library according to business datum, determine each user and neighboring user relationship type and
Relationship type, relationship rank and relationship between two users is illustrated that correspondence is stored in pass by the corresponding relationship rank of relationship type
In set type library, association user in relationship library is defined as start, associated user is defined as end；
S102, the path between two users is calculated using recursive principle, path searching all between two nodes will be connected to
Out, the array $ result of relation chain and retrieval record between two nodes of definition storage, the specific method is as follows:
S201, define a variable $ str and for storing the array $ T1 of user, retrieved in relationship library start=$ str or
The relation chain of person end=$ str is stored in array $ T1, and an association user is defined as $ other in array $ T1, corresponding
Associated user be defined as $ target, relationship type is defined as $ linktype；
S202, S203 is continued to execute if array $ T1 has value, executes S204 if $ T1 void value；
S203, array $ T1 is looped through, relation chain all between relational users and associated user is found out；Tool
Body method is as follows:
S301, associated user's value that the relation chain other end is taken out in the data of current key assignments are assigned to association user $
other；
S302, definition store the array $ n of current key assignments record, according to $ n=$ n+ ' $ other | and the format of $ linktype ' will close
Combination family $ other and relationship type $ linktype is configured to the record array $ n of current key assignments；
Whether S303, another end subscriber for judging relation chain are that target is associated user target, if other=
Target then finds target, executes 304；If $ other！=$ target, then execute S301；
S304, the record array $ n of current key assignments is labeled as a completeness relation chain, and is stored in retrieval record array $ result
In；
S204, the lookup for jumping out current level；
S103, the relation chain being retrieved that would cycle through path between two users are recorded in array $ result, to two
All relation chains between a user score, the method for scoring are as follows: according to the every two adjacent user class in relation chain
Type searches corresponding relationship rank, and the sum of the relationship rank of neighboring user there are two institutes in the relation chain is defined as the relation chain
Scoring, the specific method is as follows；
The relation chain stored under S401, the current key assignments of definition is $ r [n], and each user splits in relation chain $ r [n], splits
Afterwards, the user after fractionation is defined as v, the user class offset of two neighboring user is defined as v_linktype, and each v is equal
Including user's name and $ v_linktype, $ v is stored in the record array $ n of current key assignments；
The variable $ point=0 that S402, definition storage relation chain score；
S403, the record array $ n for looping through current key assignments, the $ v_linktype in $ v are extracted, and according to relationship
Relationship type and relationship rank corresponding relationship in typelib, extract relationship class value, by the relationship class value in the relation chain
The sum of be defined as the scoring of the relation chain；
S501, the value of v is broken up by user's name and v_linktype again, obtains the relation object offset v_ of relation chain
linktype；
S502, relationship grade variable val is defined, the record of linktype=v_linktype is found in relationship type library
Value, and the relationship class value in relation chain is assigned to variable val；
S503, the scoring defined in relation chain are $ point, are added up commenting in the relation chain according to $ point=$ point+ $ val
Divide $ point, scoring $ point is returned into array $ result；
S504, circulation execute S501~S504, all relation chains between two users are scored, and appraisal result is deposited
Storage is in array $ result；
S104, in all search results, in the completeness relation chain of return and the record of score data, according to the length of relation chain
Degree and the height of scoring are ranked up；
S105, definition relationship chain length are count (n), and the average index for defining relation chain is value, according to formula:
Value=$ point/count ($ n), the average index $ value of calculated relationship chain, scoring and relation chain in marriage relation chain
Average index $ value selects path most short, most firm between two users.
2. a kind of intelligence relationship net sniff method as described in claim 1, it is characterised in that: relationship chain length in the S104
Shorter, then the scoring of relation chain is higher, and representation relation is more intimate firm.
3. a kind of intelligence relationship net sniff method as described in claim 1, it is characterised in that: described according to average value $ value
The soundness of a relation chain is measured, average value is high, then the feasibility of relation chain is high.
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