CN103365975B - Data provenance considered Web service matching method and model based on SP tree - Google Patents
Data provenance considered Web service matching method and model based on SP tree Download PDFInfo
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Abstract
The invention discloses a data provenance considered Web service matching method and model based on an SP tree. According to the method, data provenance is regarded as one constraint attribute of the Web service matching, and the matching calculation is carried out with inputting data provenance information; the method comprises the following steps: (1) designing the Web service matching method with consideration to the data provenance and on the basis of the SP tree, and comprehensively considering function matching and data provenance matching, so as to improve accuracy rate of Web service matching; (2) establishing the Web service matching model by considering the data provenance, adopting a matcher module to realize matching requests of the Web service, and returning the matching requests of the Web service to a result set; (3) emphatically designing a data How provenance matching method based on the SP tree, and obtaining How provenance matching degree according to SP tree converted by the How provenance. According to the data provenance considered Web service matching method and the model based on the SP tree, the inputting data provenance information is considered fully, the quality of the inputting data is guaranteed, and precision ratio of the Web service matching is improved effectively.
Description
Technical field
The present invention relates to a kind of Web service matching process based on SP tree considering data origin and model, by Web
Semantic constraint is added in service, and the matching degree playing source information of input data calculates, and considers data origin and function two
Aspect, to improve the precision ratio of Service Matching, belongs to Web service technology field, more specifically, is related to data origin, work
The technical fields such as stream, Service Matching.
Background technology
With the increase of Web service number, species in Internet, how in many services, to find satisfactory clothes
Business, has become as the problem that must solve in Web service application.
At present, it has been matched as the prevailing mechanism of Web service coupling based on semantic Web service, but, based on semantic
Web service matching mechanisms mainly consider service performance, lack the quality for being related to data in service and consider.
Developing rapidly with Web, data volume greatly increases, and some data develop continuous, and this is accomplished by passing through
The source-information investigating data it is ensured that the reliability of data, thus improving the precision ratio of Service Matching.For example, water conservancy is led
The waterlevel data in domain, data is identical in itself, but to the waterlevel data from different time, different location, because river breaks
The difference in face, they need the computational methods using is also different, when carrying out Service Matching calculating, needs to fully take into account
These differences of data.
Content of the invention
Goal of the invention：In order to solve the problems, such as the quality of data in Web service coupling, it is an object of the invention to proposing a kind of
Consider the Web service matching process based on SP tree of data origin, by the generation time of data（When）, produce main body（Who）、
Produce place (Where) and differentiation flow process (How) this four classes data origin information is added in Web service matching primitives,
A source information of data, as one of Service Matching process constraints, considers clothes from function data two angles of origin
Business coupling, thus improve the precision ratio of Web service coupling.
Technical scheme：A kind of Web service matching process based on SP tree considering data origin, is to needing to carry out data
The Web service of origin matching primitives, the constraint specification of interpolation data origin, and on the basis of function match, based on SP tree, right
The |input paramete of Web service carries out data origin matching primitives, draws the matching degree of data origin, thus improving Service Matching
Precision.
Algorithm synthesis consider function data two aspects of origin, the coupling of two aspects that originate from according to function data
Degree, carries out Web service coupling：
（1）Functionally, according to the function match degree obtaining Web service based on the concept similarity algorithm of body, enter
And find the Web service meeting user function demand；
（2）In terms of data origin, to the Web service collection meeting functional requirement, to the When of its input data, Who,
Tetra- constrained attributes of Where, How carry out matching degree calculating respectively, and then, by the total coupling angle value of weight calculation, as Web takes
The data origin matching degree of business.
Consider the Web service Matching Model of data origin：
According to Web service matching process proposed by the present invention, devise corresponding Web service Matching Model, by registration
The heart, OWL-S storehouse, OWL-S, field ontology library, Jena inference machine, this six most of composition of adaptation.Wherein, adaptation is model
Core, be Web service matching primitives device, be also in itself one be used for matching primitives Web service, including following functions mould
Block：
（1）Provenance resolver：Mainly it is responsible for data origin information is parsed, complete two functions：Counting
Extract the function match demand being serviced by lookup according to rising in source information；The data origin information of |input paramete is extracted, and
It is converted into serial-to-parallel (Series-Parallel, SP) tree；
（2）Function match device：It is responsible for the service of locating function coupling in service library, matching principle is to Web service
IO in OWL-S carries out matching degree calculating.It is the main algorithm of function match based on the concept similarity matching algorithm of body.Work(
The set of service meeting functional requirement is given data origin module and is carried out data origin matching primitives by energy matching module；
（3）Data origin adaptation：Mainly it is responsible for carrying out data origin matching degree meter to the services set meeting functional requirement
Calculate and function match angle value is calculated further.The thought that data origin matching degree calculates is to When, Who, Where, How
After four constrained attributes carry out matching degree calculating respectively, by the total coupling angle value of weight calculation；
（4）Sorting unit：It is responsible for being ranked up matching result, and return final result collection.
The Web service matching process based on SP tree considering data origin proposed by the present invention, needs data How is originated from
Carry out matching primitives, originate from for data How and mate this difficult point, the present invention is divided into following two steps：
（1）Data How origin coupling based on SP tree judges：Judge flow process（I.e. How）Whether meet constraint requirements；
（2）Data How origin matching degree based on SP tree calculates：In flow process（I.e. How）On the basis of meeting constraint, according to
The coupling angle value of single process calculates total coupling angle value of whole flow process.
The technical solution used in the present invention comprises the following steps：
（1）The request submitted to according to user, parses and extracts data origin information and function information；
（2）The data How origin SP tree that source information generates user's request is played according to data How of request；
（3）It is met the Web clothes of functional requirement according to function solicited message and based on the concept similarity method of body
Business collection, and obtain its function match degree；
（4）To the Web service collection meeting demand, the input data How origin constraint life to each Web service
Become data How origin SP tree；
（5）SP tree is originated from and the input data How origin SP tree asked to input data How of Web service, using this
The data How origin matching algorithm based on SP tree of bright proposition tries to achieve Web service How origin matching degree；
（6）Using When, Who, the Where and the Web service that obtain asking based on the concept similarity algorithm of body
The coupling angle value of When, Who, Where；
（7）According to the thought of weight, it is met the data origin coupling angle value of the Web service collection of functional requirement；
（8）It is ranked up according to function match angle value data origin coupling angle value, and Web service collection is returned to use
Family.
The present invention adopts technique scheme, has the advantages that：By semantic constraint is added to Web service, with
And the matching degree playing source information of input data calculates, consider data origin and function two aspect to improve Service Matching
Precision ratio.
Brief description
Fig. 1 is the Web service Matching Model considering data origin；
Fig. 2 is the data How origin constraint specification of a Web service；
Fig. 3 is the data How origin constraint flow process of a Web service and specific execution flow process；
Fig. 4 is the SP tree of flow process A and flow process B in Fig. 3；
Fig. 5 is the SP tree conversion process that in Fig. 3, Web service flow process constrains flow process；
Fig. 6 is a simple body with regard to water conservancy forecast；
The function data origin list of matches that Fig. 7 obtains for Web service matching process of the present invention；
Fig. 8 is the matching precision comparison diagram of service matching method of the present invention and additive method under different service numbers；
Fig. 9 is the matching precision comparison diagram of service matching method of the present invention and additive method under similar service number；
Figure 10 is the flow chart of the origin matching process of data How based on SP tree proposed by the present invention；
Figure 11 parses example for Water_flow2 data origin；
Figure 12 is that the parameter flood data origin of service SedimentFlood develops flow path match process instance.
Specific embodiment
With reference to specific embodiment, it is further elucidated with the present invention it should be understood that these embodiments are merely to illustrate the present invention
Rather than restriction the scope of the present invention, after having read the present invention, the various equivalences to the present invention for the those skilled in the art
The modification of form all falls within the application claims limited range.
Fig. 1 is the Web service Matching Model considering data origin proposed by the present invention.By registration center, OWL-S storehouse,
This six most of composition of OWL-S, field ontology library, Jena inference machine, adaptation.Wherein, adaptation is the core of model, is
Web service matching primitives device, is also a Web service being used for matching primitives, including following functions module in itself：
（1）Provenance resolver：Mainly it is responsible for data origin information is parsed, complete two functions：Counting
Extract the function match demand being serviced by lookup according to rising in source information；The data origin information of |input paramete is extracted, and
It is converted into serial-to-parallel (Series-Parallel, SP) tree；
（2）Function match device：It is responsible for the service of locating function coupling in service library, matching principle is to Web service
IO in OWL-S carries out matching degree calculating.It is the main algorithm of function match based on the concept similarity matching algorithm of body.Work(
The set of service meeting functional requirement is given data origin module and is carried out data origin matching primitives by energy matching module；
（3）Data origin adaptation：Mainly it is responsible for carrying out data origin matching degree meter to the services set meeting functional requirement
Calculate and function match angle value is calculated further.The thought that data origin matching degree calculates is to When, Who, Where, How
After four constrained attributes carry out matching degree calculating respectively, by the total coupling angle value of weight calculation；
（4）Sorting unit：It is responsible for being ranked up matching result, and return final result collection.
1st, premise
Add the constraint specification to data origin in Web service, specific as follows：
When：The generation time of Web service |input paramete；
Who：The generation main body of Web service |input paramete；
Where：The generation place of Web service |input paramete or field；
How：The differentiation flow process of Web service |input paramete.
Fig. 2 is the data How origin constraint specification of a Web service, specifically describes process as follows：
2nd, method and step
（1）Parsing user's request, extracts this four classes data origin information of When, Who, Where, How, and user is to defeated
Enter the function solicited message of output：
When：The generation time of the |input paramete of service request；
Who：The generation main body of the |input paramete of service request；
Where：The generation place of the |input paramete of service request or field；
How：The differentiation flow process of the |input paramete of service request.
（2）Data How of user's request is played source information and is converted into SP tree.
Fig. 3 is the data How origin constraint of a Web service and specific execution flow process.
Fig. 4 is the SP tree of flow process A and flow process B in Fig. 3.
Taking flow process A in Fig. 3 as a example, SP tree conversion process is specially：
First, flow process A is a sequence flow on the whole, so the root node of SP tree is S, child node is respectively a base
This SP schemes Q（1a, 2a）, a parallel SP scheme P and basic SP figure Q（6a, 7a）；
Then, travel through non-Q node, that is, child node P, P has three child nodes, is all sequential organization, so, its sub- knot
Point is S, S, S；
Again, travel through the child node of P from left to right, after travel through two Q nodes of Far Left child node, travel through the successively
Two child nodes, after having traveled through, then are the 3rd child nodes；
Finally, do not need the non-Q node traveling through, traversal terminates.
（3）The IO of the OWL-S to Web service for the concept similarity based on body carries out Web service matching degree calculating, obtains
The function match degree of Web service；
（4）Meet the Web service of each of the Web service collection of function to try to achieve in step 3, its data How is risen
Source constraint is converted into SP tree.
Fig. 5 is the conversion process of the SP tree of Web service flow process constraint in Fig. 3.
The same step of its conversion process（2）Conversion process.
（5）Based on SP tree, calculate the data How origin matching degree trying to achieve Web service.
If Sim (x) represents the matching degree of SP tree interior joint or subtree x and constraint flow process.Total matching degree of so SP tree, can
Combined by following three kinds of computational methods and obtain：
● parallel, bifurcated：To parallel and bifurcation structure, its total matching degree is equal to the minimum of a value of all branches.In SP tree
In, it is presented as that the similarity of P type node is equal to the minimum of a value of all subtrees (child node).
● circulation：What loop structure produced is serial, and its matching degree is equal to the minimum of a value of all cycle-indexes of this circulation.
In SP tree, due to circulating in S type node, so when calculating the matching degree of S type node, needing first to be circulated place
Reason.
● serial：For serial, its matching degree is equal to the product of its similarity of all subtrees, if wherein included
Circulation, then only take one matching degree of minimum of circulation.In SP tree, (circulation takes to be equivalent to the product of all subtrees of S node
Little).
（6）To the Web service collection obtaining in step 3 using the concept similarity method based on body, it is calculated respectively
Data Who, When of Web service, the matching value of Where.
（7）Data When, Who of each of Web service collection Web service, Where, How origin matching value are carried out
Weight is sued for peace, the as data origin matching degree of Web service.
（8）According to the function match degree data origin matching degree obtaining, Web service is ranked up, and result is returned
Back to user.
Fig. 6 is a simple body with regard to water conservancy forecast.This body is made up of two parts：The data of monitoring is pre- with needs
The content of report.In the setting by attribute for the body, the derivation relationship between the content of forecast and monitor value can be set.
According to the domain body of Fig. 6, and Web service matching process proposed by the present invention, calculate function data and rise
Source matching degree, Fig. 7 is its function data origin list of matches.
3rd, method analysis
The present invention adopts Prot é g é 3.4 as Domain Ontology Modeling instrument, is used as inference machine by Jena2.6.0, at random
Generate 1000 services, using artificial mark to 500 services in service library in the face of matching effect is verified.
Under Random Service collection, by coupling that interpolation data is originated from, mate with without data origin and carry out contrast and test
Card, Fig. 8 is different Service Matching accuracy comparison figure.
Meanwhile, if made a look up to special services, with the raising of proportion in total services set for the type service,
Can be further discovered that it is considered to the Web service coupling based on SP tree of data origin is more smart based on semantic Service Matching than simple
What degree improved becomes apparent from, and Fig. 9 is similar service matching precision comparison diagram.
Data How origin matching process based on SP tree
1st, flow chart
The data How origin matching process based on SP tree of present invention design, mainly includes two parts：
（1）Data How origin coupling based on SP tree judges：Judge flow process（I.e. How）Whether meet constraint requirements；
（2）Data How origin matching degree based on SP tree calculates：In flow process（I.e. How）On the basis of meeting constraint, according to
The coupling angle value of single process calculates total coupling angle value of whole flow process.
It is necessary first to whether n node determination flow of traversal meets the requirements during data How origin matching primitives,
Complexity is O（n2）；Then, then travel through n node and calculate How origin matching degree, its complexity is O（n2）.However, due to
Family is indifferent to whether flow process mates, and is only concerned final matching degree.So when flow process mismatches it is believed that matching degree is 0,
Think that data origin mismatches completely.So, method can be optimized.
Figure 10 is the flow chart of the data How origin matching process based on SP tree after optimizing.
From the beginning of the root node of SP tree, using the thought of traversal, it concretely comprises the following steps the method：
（1）The type of predicate node（Q or S, P）；
（2）If Q type, press（3）Process, if S or p-type, press（4）Process；
（3）Whether Q flow process mates：
（3.1）If it does, calculating matching degree, travel through next node, jump to（1）；
（3.2）Otherwise, matching degree is 0, returns matching degree, and algorithm terminates；
（4）Whether SP mates：
（4.1）If it does, obtaining its child node, beginning stepping through from child node, jumping to（1）；
（4.2）If mismatched, matching degree is 0, returns matching degree, and algorithm terminates.
2nd, the data How origin coupling based on SP tree judges
Data How origin coupling based on SP tree judges it is for judging whether the evolution process of input data meets Web
The constraint requirements to data origin information for the service.
Due to without the coupling considering concrete node, so core is to carry out legitimacy meter to each node in SP tree
Calculate.According to SP tree feature, invention defines five basic matching relationships：
In Web service constraint, if process is atom process, then it with SP tree in Q node matching；
Web service constraint in, if N number of process node be order model, then it with S as root node, with N number of mistake
Journey is the SP tree coupling of child nodes；
In Web service constraint, if N number of process node is parallel model, then it arrives N with P as root node, with one
Individual process is the SP tree coupling of child nodes；
In Web service constraint, if process node is Bifurcation Model, then it with P as root node, with one
Or the SP tree coupling that multiple processes are child nodes；
In Web service constraint, if process node is circulation model, then it with S as root node, with one
Or the SP tree coupling that multiple processes are child nodes.
In SP tree individual node Web service constraint in carry out matching primitives false code as follows：
Input：The node node of SP tree
Output：Boolean the match is successful return true, mismatch then return false
Explanation：Node is the data structure of a preservation nodal information
Algorithm：SPSingleNodeMatch
Step：
Based on individual node flow path match algorithm, can be by the recursive traversal to SP tree, to each S, P section in SP tree
Point carries out matching primitives, thus obtaining whether whole flow process mates.
Judge that false code is as follows based on the flow path match of SP tree traversal：
Input：The root node root of origin SP tree
Output：Boolean true represents flow path match false and represents mismatch
Explanation：Node is the data structure of a preservation nodal information, and this algorithm adopts recursive calculation
Algorithm：SPProcessMatch
Step：
3rd, the data How origin matching degree based on SP tree calculates
The coupling angle value of data How origin on the basis of flow path match, is calculated based on SP tree.Main thought is to pass through
Calculating to the matching degree of Q type node in SP tree, then in SP tree S, P type node to coupling angle value process, from
And obtain total coupling angle value of whole flow process.
If Sim (x) represents the matching degree of SP tree interior joint or subtree x and constraint flow process.Total matching degree of so SP tree, can
Combined by following three kinds of computational methods and obtain：
Parallel, bifurcated：Total matching degree is equal to the minimum of a value of all branches.In SP tree, it is presented as the similar of P type node
Degree is equal to the minimum of a value of all subtrees (child node)；
Circulation：What loop structure produced is serial, and its matching degree is equal to the minimum of a value of all cycle-indexes of this circulation.?
In SP tree, due to circulating in S type node, so when calculating the matching degree of S type node, needing first to be circulated place
Reason；
Serial：Matching degree is equal to the product of its similarity of all subtrees, if wherein including circulation, then only take and follow
One matching degree of the minimum of ring.In SP tree, be equivalent to the product (circulation takes little) of all subtrees of S node.
In Fig. 3, total coupling angle value of flow process A is：
Sim(A)=Q(1a,2a)*min(Q(2a,3a)*Q(3a,6a),Q(2a,3b)*Q(3b,6a),Q(2a,4a)*Q
(4a,6a))*Q(6a,7a)
The false code that How origin matching degree based on SP tree calculates is as follows：
Input：The root node root of origin SP tree
Output：Double matching degree
Explanation：Node is the data structure of a preservation nodal information, and this algorithm adopts recursive calculation
Algorithm：matchMakingDegree
Step：
4th, method analysis
The flow chart on Figure 11 left side, is that in a water conservancy, the data calculating silt content according to monitoring point collection and flood are pre-
Alert flow process (example).Collection_data is the raw data set of collection, comprises silt content, precipitation, water level information.
Sediment_con, rainfall, water_lev represent the silt content extracted from initial data, precipitation and water level respectively
These data are carried out finishing analysis by data respectively, by water level can with calculated flow rate (flow_rate), by precipitation event and
Traffic conditions calculate flood (flood).
The service that matchMaker representative will be searched, its input is the silt content after finishing analysis
(consodidated_sed) with the flood (flood) being computed, its function is exactly to silt content and flood according to input
The carrying out of the impact that water is likely to result in calculates, finally output silt content and flood possible impact result (sed_flood).
In the generating process of SP tree, multiple inputs may be comprised by lookup service.Each |input paramete must be given birth to
Become corresponding SP tree.It is necessary first to extract to the flow process producing each input data before generating SP tree.In Figure 11, right
For the evolution process of parameter flood, parameter silt content (sediment_con) does not play work in its evolution process
With.So in the SP tree generating process of flood, not needing including silt content, and only need to develop flow process phase including with it
Collection_data, rainfall, water_lev, consodidated_rai, the consodidated_lev closing,
The parameters such as flow_rate.In Figure 11, the SP tree on right side is the SP tree of parameter flood.
The parameter flood data origin that Figure 12 demonstrates service SedimentFlood develops flow path match process.Far Left
It is the service constraint specification to parameter flood for the SedimentFlood.In playing source information Water_flow2, will originate from Figure 11
Rainfall in Water_flow has made the SP figure for its flood parameter for the SP tree in the middle of ice, Figure 12 into.According to based on SP
The flow path match algorithm of tree, can calculate both flow processs is coupling, and its finally total matching degree is on the right of 0.36, Figure 12
Calculating tree be its calculating process.
Thus, the data How origin matching algorithm based on SP tree proposed by the present invention is feasible, effectively.
Claims (1)
1. a kind of Web service matching process based on SP tree considering data origin is it is characterised in that comprise the following steps：
Step 1), to needing to carry out the Web service of data origin matching primitives, the constraint specification of interpolation data origin；
Step 2), on the basis of function match, based on SP tree, data origin coupling meter is carried out to the |input paramete of Web service
Calculate, draw the matching degree of data origin；
Step 3), according to function match angle value data origin coupling angle value, the Web service meeting user function demand is carried out
Sequence, and the Web service collection after sequence is returned to user；
Step 1) in needing to carry out the Web service of data origin matching primitives, the constraint specification of interpolation data origin, comprehensively examine
Consider function data two aspects of origin, comprise the steps of further：
11) functionally, obtain the function match degree of Web service based on the concept similarity of body, and then find satisfaction using
The Web service of family functional requirement；
12) in terms of data origin, to the Web service collection meeting functional requirement, to the When of its input data, Who, Where,
Tetra- constrained attributes of How carry out matching degree calculating respectively, then, by the total coupling angle value of weight calculation, the as number of Web service
According to origin matching degree；
Matching degree calculating is carried out to data How origin, is divided into following two steps：
121) the data How origin coupling based on SP tree judges：Judge whether How constrained attributes meet constraint requirements；
122) the data How origin matching degree based on SP tree calculates：On the basis of meeting constraint, according to the coupling of single process
Angle value calculates total coupling angle value of whole flow process.
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Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102368215A (en) * | 2011-10-07 | 2012-03-07 | 彭志平 | Single Web service matching method |
-
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Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102368215A (en) * | 2011-10-07 | 2012-03-07 | 彭志平 | Single Web service matching method |
Non-Patent Citations (2)
| Title |
|---|
| 信息提供类Web服务与RDF数据源的集成;赵文峰 等;《北京邮电大学学报》;20081231;第31卷(第6期);109-112,124 * |
| 基于语义Web服务的发布/订阅模型研究;许国艳 等;《微电子学与计算机》;20090930;第26卷(第9期);23-25 * |
Cited By (2)
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| CN107895595A (en) * | 2017-11-14 | 2018-04-10 | 重庆大学 | The planning selection scheme of the software quick definition intelligent environment of Users ' Need-oriented recommends method |
| CN107895595B (en) * | 2017-11-14 | 2020-06-19 | 重庆大学 | User-demand-oriented planning selection scheme recommendation method for software rapid definition intelligent environment |
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