CN111191088A - Method, system and readable medium for analyzing cross-boundary service demand - Google Patents
Method, system and readable medium for analyzing cross-boundary service demand Download PDFInfo
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Abstract
The invention relates to a method, a system and a readable medium for analyzing a cross-boundary service demand. The modeling method realizes the mapping from the user target to the service, and can guide a developer to quickly develop the cross-boundary service meeting the user requirement. The invention has the beneficial effects that: 1) the reuse of the historical model is realized, a new model can be quickly constructed based on the existing model, and the demand analysis efficiency is improved; 2) modeling analysis is comprehensively carried out on the cross-boundary service requirements from multiple angles such as value, target, service and the like, and the method has good practicability; 3) subsequent cross-boundary service design and development work can be effectively guided.
Description
Technical Field
The invention belongs to the technical field of service calculation, and particularly relates to a cross-boundary service demand analysis method and system.
Background
The cross-border service is a novel service mode and is a product of the development of the modern service industry to the advanced stage. The business field of cross-border services is not limited to a single field, but is expanded to multiple fields, thereby realizing the extension of a value chain and the improvement of core competitiveness [1 ]. Dynamic market demand and globalization trends have placed a tremendous competitive pressure on cross-border service providers, and to remain competitive in an uncertain market environment, it has become especially important to develop new cross-border services while considering both technical and business values [2 ]. However, due to the lack of a clear definition of value, service providers have not considered the value expectations of the masses, resulting in some cross-border services failing in intense market competition. The cross-boundary service relates to the fusion of heterogeneous resources of different organizations, different value chains and different fields, the operating environment is open and dynamic, the potential needs and the real intentions of users are difficult to grasp, and the cross-boundary service brings huge challenges to the demand analysis. Therefore, a complete analysis method is necessary to support the requirement analysis of a complex cross-boundary scenario, so as to provide guidance for the subsequent cross-boundary service design.
The existing value-based demand analysis methods [3,4,5] provide a mechanism for modeling the crowd-involved value demand. However, the method is mainly used for describing how the value objects are exchanged among people, and does not indicate how to guide the analysis and design of the cross-border service based on the value appeal of the people. And a target-based demand analysis method [6,7,8] mainly focuses on modeling of user intentions, but cannot effectively support the fusion modeling of values, targets and services in a cross-boundary service scene. In a word, the existing demand analysis method cannot well support the characteristics of cross organization, cross value chain, cross flow and cross field of the cross boundary service.
The references referred to herein are as follows:
[1]Wu,Z.et al.Modern Service Industry and Crossover Services:Development and Trends in China,IEEE Transactions on Services Computing,2011,9(5),pp.664–671.
[2]Aurum,A.and Wohlin,C.A Value-Based Approach in RequirementsEngineering:Explaining Some of the Fundamental Concepts,International WorkingConference on Requirements Engineering:Foundation for Software Quality,2007,pp.109–115.
[3]Thew,S.and Sutcliffe,A.Value-based requirements engineering:methodand experience,Requirements Engineering.Springer London,2018,23(4),pp.443–464.
[4]Bukhsh,F.A.and Silva,P.D.A.Modeling E-Business Customization withe3value Modeling,Proceedings-14th International Conference on Frontiers ofInformation Technology,FIT 2016.IEEE,pp.187–192.
[5]Azam,F.,Li,Z.,Ahmad and R.Integrating Value-based RequirementEngineering Models to WebML using VIP Business Modeling Framework,2007International World Wide Web Conference,WWW 2007,pp.933-942.
[6]Horkoff,J.,Maiden,N.A.and Asboth,D.Creative goal modeling forinnovative requirements,Information and Software Technology.Elsevier B.V.,2019,106,pp.85–100.
[7]Horkoff,J.and Yu,E.Interactive goal model analysis for earlyrequirements engineering,Requirements Engineering.Springer London,2016,21(1),pp.29–61.
[8]Pimentel,J.and Castro,J.piStar Tool–A Pluggable Online Tool forGoal Modeling,2018IEEE 26th International Requirements Engineering Conference(RE).IEEE,pp.498–499.
disclosure of Invention
The invention mainly solves the problems in the prior art, provides a method and a system for analyzing a cross-boundary service demand, supports cross-boundary service demand analysis in a complex scene, can search a demand model similar to the current demand scene from a historical database to realize rapid model reuse, improves the demand analysis efficiency, and has good practicability.
The technical problem of the invention is mainly solved by the following technical scheme: a cross-boundary service demand analysis method comprises the following steps:
step 1, defining core elements and relations among the core elements according to a specific business requirement scene, wherein the relations include participants, value objects, value activities and targets, inputting a core element set of a current scene into a value network model database, and searching for similar models; if the matched model can be inquired, reusing the model; otherwise, establishing a value network model by the demand analyst according to the exchange path of the value object among the participants, and storing the constructed new model into a value network model database;
step 2, extracting the large-granularity target in the step 1, inputting the large-granularity target into a target network model database to query a similar target network model, and if the similar target network model can be queried, reusing the model; otherwise, turning to the step 3;
the target network model is used for defining an operability target, a functional target and a non-functional target and determining a constraint relation and a decomposition relation among the targets;
step 3, decomposing the root target in a layer-by-layer decomposition mode to obtain a functional target, a non-functional target and an operable target with fine granularity until the operable target is obtained, and determining the relation between a lower-layer target and an upper-layer target, wherein the operable target refers to a target realized by a person or a software agent;
and 4, analyzing value activities required to achieve the operability targets obtained in the steps 2 and 3, mapping the activities to flow nodes, and establishing an execution mode of the flow. If the flow at least comprises an execution mode, the flow is a combined flow, otherwise, the flow is an atomic flow; and finally, binding specific Web services for the process to form a service network model and guiding the rapid development of the cross-border service.
Further, the step 1 specifically includes the following substeps:
step 1.1, defining a value network model related to a user demand scene as a quintuple Nv＝{L,R,Vo,Va,GvWhere L denotes the domain, R denotes a set of roles, where the roles are played by different participants, VoRepresenting a collection of value objects, VaRepresenting sets of value activities, GvRepresenting a set of targets;
step 1.2 according to the quintuple NvSearching a value network model similar to the current demand scene from a value network model database, if the value network model similar to the current field L can be searched, returning a query result and sequencing according to the similarity, otherwise, turning toStep 1.3, wherein the similarity calculation method comprises the following steps:
wherein N isvRepresenting the set of value network model elements, D, involved in the current user demand scenarioiRepresenting the ith set of model elements, M (N), in a value network model databasev,Di) Represents DiAnd NvThe similarity of (2);
step 1.3, extract NvThe method comprises the steps that four core modeling elements, namely roles, value objects, value activities and targets, are analyzed, the value objects are exchanged among the roles, a value exchange relation among the roles is established, the value activities needed in the process of exchanging the value objects are further analyzed, a value activity list is obtained, which roles are needed by the value activities to bear are determined, finally, the role targets are determined, and a value network model is obtained after semantic relations among the roles, the value objects, the value activities and the targets are obtained;
and step 1.4, storing the newly-built value network model into a value network model database for subsequent reuse.
Furthermore, the specific implementation manner of the step 2 is as follows,
extracting the target G defined in step 1vConverting the current target into a vector by using a Word2Vec tool, and calculating G by using a semantic similarity calculation technologyvRoot target G of target network model in target network databasemThe root target refers to an initial functional target to be decomposed; if the similar target network models can be searched, returning query results and sorting according to the similarity, and returning the target network models where top-k similar root targets are located to the modeler, otherwise, turning to the step 3, wherein the semantic similarity calculation method comprises the following steps:
wherein G ismRepresenting the root target of the mth target network model in the target model database, and i represents the dimension of the vector.
Further, the step 3 specifically includes the following substeps:
step 3.1, for large-granularity functional target GvDecomposing layer by layer to obtain a more specific operability target, and decomposing the upper layer target in a parallel mode in the decomposition process;
step 3.2, analyzing and defining the relationship between the lower layer target and the upper layer target, wherein the definition of the relationship is divided into two types: AND OR, wherein the judgment method of the AND relation is that the lower layer target must be completed AND the upper layer target can be achieved; the judgment method of the OR relation is that at least one lower layer target is achieved, and an upper layer target can be achieved;
and 3.3, storing the newly constructed target network model into a target network model database so as to be capable of being rapidly reused in subsequent modeling.
Further, the step 4 of constructing the given service network model specifically includes the following sub-steps:
step 4.1, mixing VaThe value activity in the process is mapped to a specific process node, and the execution mode of the process is determined according to the execution mode of the value activity, wherein the execution mode comprises a sequence mode, a selection mode, a concurrency mode and a circulation mode;
step 4.2, analyzing which Web services are needed to realize the functions defined by the flow nodes to obtain a service list, and further determining the input and output of the services and the related specific service operation;
and 4.3, storing the newly constructed service network model into a service network model database.
The invention also provides a cross-boundary service demand analysis system, which comprises the following modules:
the value network modeling module is used for modeling the relation between the audience-involved core elements and the core elements related to the cross-border service scene, wherein the core elements comprise participants, value objects, value activities and targets;
the target network modeling module is used for further defining targets related in the value network model into an operability target, a functional target and a non-functional target and determining a constraint relation and a decomposition relation among the targets;
and the service network modeling module is used for modeling the process and the service, definitely completing the service required by the function defined by the process and definitely determining the relation between the services.
The present invention also provides a computer readable storage medium having instructions stored thereon which, when executed by a processor, implement the steps of a cross-border service requirement analysis method.
Compared with the prior art, the method provided by the invention supports modeling of the requirements of the cross-boundary service from multiple perspectives such as value, target, process, service and the like, realizes cross-boundary service design under the guidance of value, and ensures that the service and the value are aligned. The modeling method realizes the mapping from the user target to the service, and can guide a developer to quickly develop the cross-boundary service meeting the user requirement. In addition, the modeling method also supports the reuse of the historical model, is beneficial to the rapid construction of the demand model, and improves the efficiency of demand analysis.
Drawings
FIG. 1 is a block diagram of a cross-boundary service requirement analysis method and system according to the present invention;
FIG. 2 is a queried value network model similar to a current demand scenario;
FIG. 3 is an initial model of a target network without semantic relationships for a Mei Tuan taxi-taking cross-border service;
FIG. 4 is a target network model for the Mei Tuo taxi-taking cross-border service;
fig. 5 is a service network model of the beauty team taxi-taking cross-border service.
Detailed Description
As shown in fig. 1, an embodiment of the present invention provides a cross-boundary service requirement analysis method, including the following steps:
step 1, according to a specific service demand scene, defining core elements such as participants, roles, value objects, value activities, targets and the like, defining the relationship among the core elements, inputting the core element set of the current scene into a value network model database, and searching for similar models. If the matched model can be inquired, reusing the model; otherwise, establishing a value network model by the demand analyst according to the exchange path of the value object among the participants, and storing the constructed new model into a value network model database.
Step 2, extracting the large-granularity functional target in the step 1, inputting the large-granularity functional target into a target network model database to query a similar target network model, and if the similar target network model can be queried, reusing the model; otherwise, go to step 3.
And 3, decomposing the root target in a layer-by-layer decomposition mode until an operability target is obtained, wherein the operability target refers to a target which can be realized by a person or a software agent, and then determining the relationship between a lower-layer target and an upper-layer target.
Step 4, analyzing which value activities need to be involved to achieve the operability targets obtained in the steps 2 and 3, mapping the activities to flow nodes, then establishing an execution mode of the flow, wherein if the flow at least comprises one execution mode, the flow is a combined flow, and otherwise, the flow is an atomic flow; and finally, binding specific Web services for the process to form a service network model and guiding the rapid development of the cross-border service.
The method for analyzing the cross-boundary service requirement includes the following specific steps in step 1:
step 1.1, defining a value network model related to a user demand scene as a quintuple Nv＝{L,R,Vo,Va,GvWhere L denotes the domain, R denotes a set of roles, where the roles are played by different participants, VoRepresenting a collection of value objects, VaRepresenting sets of value activities, GvRepresenting a set of targets.
Step 1.2 according to the quintuple NvSearching a value network model similar to the current demand scene from a value network model database, and if the value network model can be searchedAnd returning the query results and sequencing according to the similarity if the value network models in the previous field L are similar, otherwise, turning to the step 1.3. The similarity calculation method comprises the following steps:
wherein N isvRepresenting the set of value network model elements, D, involved in the current user demand scenarioiRepresenting the ith set of model elements, M (N), in a value network model databasev,Di) Represents DiAnd NvThe similarity of (c).
Step 1.3, extract NvThe method comprises the steps of analyzing roles, value objects, value activities and targets of the four core modeling elements, analyzing roles in which the value objects are exchanged, establishing a value exchange relation between the roles, further analyzing the value activities needed in the process of exchanging the value objects, obtaining a value activity list, determining which roles are needed by the value activities to bear, finally determining each role target, and obtaining a value network model after clarifying semantic relations among the roles, the value objects, the value activities and the targets.
And step 1.4, storing the newly-built value network model into a value network model database for subsequent reuse.
In the above method for analyzing a cross-boundary service requirement, the step 2 specifically includes:
extracting the target G defined in step 1vConverting the current target into a vector by using a Word2Vec tool, and calculating G by using a semantic similarity calculation technologyvRoot target G of target network model in target network databasemThe root target here refers to the initial functional target to be decomposed. If the similar target network models can be searched, returning the query results, sequencing according to the similarity, and returning the target network models where top-k similar root targets are located to the modeler, otherwise, turning to the step 3. The semantic similarity calculation method comprises the following steps:
wherein G ismRepresenting the root target of the mth target network model in the target model database, and i represents the dimension of the vector.
In the above method for analyzing a cross-boundary service requirement, the step 3 specifically includes the following substeps:
step 3.1, for large-granularity functional target GvLayer-by-layer decomposition is performed to obtain a more specific operability objective. And the decomposition process is used for decomposing the upper-layer target in a parallel mode respectively to obtain a corresponding target network model.
And 3.2, analyzing and determining the relation between the lower-layer target and the upper-layer target. The main definitions of the relationship here are two: AND OR. The judgment method of the AND relation is that the lower layer target is required to be completed AND the upper layer target can be achieved; the OR relationship is determined by achieving at least one lower level objective and only achieving an upper level objective.
And 3.3, storing the newly constructed target network model into a target network model database so as to be capable of being rapidly reused in subsequent modeling.
After the target model is constructed, the step 4 of constructing the given service network model specifically includes the following substeps:
step 4.1, mixing VaThe value activity in the process is mapped to a specific process node, and the execution mode of the process is determined according to the execution mode of the value activity, wherein the execution mode comprises modes such as sequence, selection, concurrency, circulation and the like;
and 4.2, analyzing which services are needed to realize the functions defined by the flow nodes to obtain a service list, and further determining the input/output of the services and the related specific service operation.
And 4.3, storing the newly constructed service network model into a service network model database.
The following is a specific embodiment of applying the method of the present invention to perform cross-boundary service requirement analysis: the cross-border service of the invention is taken as an embodiment, and the specific implementation process is explained in detail by combining the attached drawings.
As a lifestyle service provider, the consortium mainly offers hotel reservations, ticket reservations, and other lifestyle services. In order to meet the travel requirements of users and complement the short boards of the value chain, the American group expands the business field to the traffic travel field, and provides a cross-border service, namely the American group taxi taking. The following describes the specific implementation process of the method of the present invention by taking a Mei Tuo vehicle as a case.
And (3) executing the step (1) to construct a value network model, and determining value complaints of various people and a value exchange mechanism among the people.
Step 1.1 is executed, and the participant set R ═ driver, passenger } and the target set G of the taxi taking scene are determinedvValue object set V, value object set { convenient trip, earn profit }oTime, currency, value activity set VaThe method comprises the steps of { order submission, itinerary planning, itinerary support, driving service, order support }, so that a set N of elements of the value network to be modeled currently can be obtainedv{ ' R ': passenger ', ' driver '],'Gv'convenient trip', 'earning profit'],'Vo'time', 'currency'],'Va'submit order', 'trip plan', 'trip support', 'drive service', 'order payment']}。
Step 1.2 is executed to find a similar value network model from the value network model database. Here with some value network D already in the database1The specific method of use is illustrated by way of example. Value network model D1Is { 'R' [ 'passenger', 'driver'],'Gv'convenient trip', 'earn profit'],'Vo'time', 'money'],'Va'submit order', 'route planning', 'trip support', 'drive service', 'pay fare']}, calculate N belowvAnd D1The set similarity of (c). Here, the similarity of elements in two sets is calculated by using the open source Chinese natural language processing tool package synnyms, and the similarity of partial elements is as follows:
R
passenger 1.0
Passenger driver 0.299
Driver passenger 0.299
Driver 1.0
Gv
Convenient 0.522 of going out of convenient trip
Profit earning of convenient trip is 0.097
0.097 making profit and facilitating travel
Earning profit 1.0
Vo
Time period 1.0
Time money 0.072
Currency time 0.032
Monetary money 0.123
If the similarity of the two elements exceeds 0.5, the two elements are considered to be similar, and N can be obtained through calculationvAnd D1The intersection of (1) and (13) is 10, the similarity of the two models is 76.92%, and the value network model D1As shown in fig. 2.
Finally, because similar models are found from the value network model database, step 1.3 is skipped, step 1.4 is switched, and the demand analyst can reuse model D1And quickly constructing a new model on the basis of the model and storing the new model in a model database.
Step 2, searching for a similar target network model;
first, step 2.1 is executed to extract the existing root target set of target network model, denoted as G, from the target network model databasem. Firstly, G is divided by a jieba word segmentation toolvAnd GmSplitting into words and removing common words, then converting each Word into a vector by using Word2Vec, and finally calculating the current target G by using a formula (2)vAnd GmThe semantic similarity of each root object in the set of root objects is shown below. And (4) turning to step 3 because a similar target model is not found.
Convenient trip for realizing electronic commerce transaction 0.386
Convenient trip realizes that two-way circulation of uplink and downlink is 0.459
Convenient trip high-resolution remote sensing intelligent agricultural field application 0.297
0.253 commodity production of convenient trip enterprise
Convenient travel construction full-risk insurance service platform 0.334
Convenient trip constructs wisdom community 0.426
Travel business 0.412 is managed in convenient trip
Application of convenient trip high-resolution remote sensing in agricultural field 0.24
Step 3 is executed, a target network model is built, wherein the target network model comprises core elements such as functional targets, non-functional targets, constraint relations and decomposition relations among the targets, the user targets can be further refined through building the target model to obtain operability targets, and the operability targets can be realized manually or through specific services;
step 3.1 is executed, the target 'convenient trip' is decomposed into 5 sub-targets, which are respectively: the operability sub-targets "generate itinerary preferences" and "itinerary assessment", the functional sub-target "itinerary support" and "generate itinerary plan", and the non-functional sub-target "convenience payments". The functional target "trip support" is further decomposed into 4 sub-targets, respectively: operability goals "shortest path", "guide passenger", and "notify passenger", functional goals "locate vehicle position". The functional objective "locate vehicle position" is broken down into 2 operability sub-objectives "locate by GPS" and "locate by manual dispatch". The upper-level target 'generating a travel plan' is further decomposed into functional sub-targets 'scheduling a travel' and 'displaying a travel route'. The functional object "Schedule" is broken down into 2 non-functional sub-objects "least time consuming" and "least expensive". The upper level target "display route" is divided into 2 operability sub-targets "display by text" and "display by audio and video". FIG. 3 is a target network initial model which is constructed by the aid of the tools and does not have semantic relations given to the Mei Tuo taxi crossing service.
Step 3.2 is performed to establish the semantic relationship between the objects. The relationship between the lower-layer sub-target "generate travel preference", "travel evaluation", "travel support", "generate travel plan", "convenient payment" AND the upper-layer target "convenient travel" is "AND". The relationship between the lower level sub-target "shortest path", "guide passenger", "notify passenger", "locate vehicle position", AND the upper level target "trip support" is "AND". The relationship between the lower sub-target "positioning by GPS" and "positioning by manual scheduling" and the upper target "positioning vehicle position" is "OR". The relationship between the lower-layer sub-target "schedule a trip" AND "display a trip route" AND the upper-layer target "generate a trip plan" is "AND". The relation between the lower sub-target "least time consuming" and "least cost" and the upper sub-target "schedule" is "OR". The relationship between the lower sub-target "display through text" and "display through audio and video" and the upper target "display route" is "OR". FIG. 4 is a target network model of a midget taxi-taking cross-border service demand analysis constructed by the tool.
And 3.3, storing the newly constructed target network model into a target network model database.
Finally, step 4 is executed, a service network model is built, wherein the service network model comprises elements such as processes, resources, services, service operations, input/output messages of the services and the like, and the service required by the user target can be definitely realized by building the service network model so as to guide the subsequent service development;
step 4.1 is performed to map the value activity involved in the value network to a process node. The process related to the cross-border scene of the united taxi taking specifically comprises the following steps: the atomic process comprises the steps of ordering by a user, paying by the user and managing comments, and the combined process comprises the steps of generating a travel plan and supporting travel. The combined flow "generating a travel plan" is formed by combining 3 atomic flows, which are respectively as follows: "evaluate traffic environment", "generate travel route", and "display travel route"; the combined flow "travel support" is formed by combining 3 atomic flows, which are respectively: "collect traffic data", "GPS track" and "update real time location".
Step 4.2 is executed to serve the flow binding. Wherein, the function defined by the atomic flow 'user order' is completed by the atomic service 'order management'; the function defined by the combined process of generating the travel plan is completed by the combined service of generating the travel plan, wherein the combined service is formed by combining 3 atomic services, and the combined service specifically comprises the following steps: "weather data", "traffic condition information", and "trip route planning"; the function defined by the combined process of 'travel support' is completed by the combined service of 'travel support', and the combined process comprises 2 atomic services which are 'real-time traffic data' and 'GPS tracking' respectively; the function defined by the atomic process "user payment" is completed by the composite service "user payment", and the composite service comprises 2 atomic services, which are respectively: "generate order information" and "payment service"; and the function defined by the atomic flow 'comment management' is completed by the atomic service 'comment management'.
And 4.3, storing the newly constructed service network model into a service network model database so as to be quickly reused in subsequent modeling.
Fig. 5 is a service network model of the midget taxi-taking cross-border service demand analysis constructed by using the tool system.
The invention also provides a cross-boundary service demand analysis system, which comprises the following modules:
the value network modeling module is used for modeling the relation between the audience-involved core elements and the core elements related to the cross-border service scene, wherein the core elements comprise participants, value objects, value activities and targets;
the target network modeling module is used for further defining targets related in the value network model into an operability target, a functional target and a non-functional target and determining a constraint relation and a decomposition relation among the targets;
and the service network modeling module is used for modeling the process and the service, definitely completing the service required by the function defined by the process and definitely determining the relation between the services.
The present invention also provides a computer readable storage medium having instructions stored thereon which, when executed by a processor, implement the steps of a cross-border service requirement analysis method.
The specific embodiments described herein are merely illustrative of the spirit of the invention. Various modifications or additions may be made to the described embodiments or alternatives may be employed by those skilled in the art without departing from the spirit or ambit of the invention as defined in the appended claims.
Claims (7)
1. A cross-boundary service demand analysis method is characterized by comprising the following steps:
step 1, defining core elements and relations among the core elements according to a specific business requirement scene, wherein the relations include participants, value objects, value activities and targets, inputting a core element set of a current scene into a value network model database, and searching for similar models; if the matched model can be inquired, reusing the model; otherwise, establishing a value network model by the demand analyst according to the exchange path of the value object among the participants, and storing the constructed new model into a value network model database;
step 2, extracting the large-granularity target in the step 1, inputting the large-granularity target into a target network model database to query a similar target network model, and if the similar target network model can be queried, reusing the model; otherwise, turning to the step 3;
the target network model is used for defining an operability target, a functional target and a non-functional target and determining a constraint relation and a decomposition relation among the targets;
step 3, decomposing the root target in a layer-by-layer decomposition mode to obtain a functional target, a non-functional target and an operable target with fine granularity until the operable target is obtained, and determining the relation between a lower-layer target and an upper-layer target, wherein the operable target refers to a target realized by a person or a software agent;
step 4, analyzing the value activities needed to reach the operability targets obtained in the steps 2 and 3, mapping the activities to the process nodes, then establishing the execution mode of the process, if the process at least comprises one execution mode, the process is a combined process, otherwise, the process is an atomic process; and finally, binding specific Web services for the process to form a service network model and guiding the rapid development of the cross-border service.
2. The method for analyzing cross-border service requirements of claim 1, wherein: the step 1 specifically comprises the following substeps:
step 1.1, defining a value network model related to a user demand scene as a quintuple Nv＝{L,R,Vo,Va,GvWhere L denotes the domain, R denotes a set of roles, where the roles are played by different participants, VoRepresenting a collection of value objects, VaRepresenting sets of value activities, GvRepresenting a set of targets;
step 1.2 according to the quintuple NvSearching a value network model similar to the current demand scene from a value network model database, if the value network model similar to the current field L can be searched, returning a query result and sequencing according to similarity, otherwise, turning to the step 1.3, wherein the similarity calculation method comprises the following steps:
wherein N isvRepresenting the set of value network model elements, D, involved in the current user demand scenarioiRepresenting the ith set of model elements, M (N), in a value network model databasev,Di) Represents DiAnd NvThe similarity of (2);
step 1.3, extract NvThe four core modeling elements in the system comprise roles, value objects, value activities and targets, the value objects are analyzed to be exchanged among the roles, the value exchange relation among the roles is established, the value activities needed in the process of exchanging the value objects are further analyzed, and a value activity list is obtained to show thatDetermining which roles are required for the value activities to bear, finally determining each role target, and obtaining a value network model after obtaining the semantic relations among the roles, the value objects, the value activities and the targets;
and step 1.4, storing the newly-built value network model into a value network model database for subsequent reuse.
3. The method of claim 2, wherein the method comprises: the specific implementation of step 2 is as follows,
extracting the target G defined in step 1vConverting the current target into a vector by using a Word2Vec tool, and calculating G by using a semantic similarity calculation technologyvRoot target G of target network model in target network databasemThe root target refers to an initial functional target to be decomposed; if the similar target network models can be searched, returning query results and sorting according to the similarity, and returning the target network models where top-k similar root targets are located to the modeler, otherwise, turning to the step 3, wherein the semantic similarity calculation method comprises the following steps:
wherein G ismRepresenting the root target of the mth target network model in the target model database, and i represents the dimension of the vector.
4. The method of claim 2, wherein the method comprises: the step 3 specifically comprises the following substeps:
step 3.1, for large-granularity functional target GvDecomposing layer by layer to obtain a more specific operability target, and decomposing the upper layer target in a parallel mode in the decomposition process;
step 3.2, analyzing and defining the relationship between the lower layer target and the upper layer target, wherein the definition of the relationship is divided into two types: AND OR, wherein the judgment method of the AND relation is that the lower layer target must be completed AND the upper layer target can be achieved; the judgment method of the OR relation is that at least one lower layer target is achieved, and an upper layer target can be achieved;
and 3.3, storing the newly constructed target network model into a target network model database so as to be capable of being rapidly reused in subsequent modeling.
5. The method of claim 2, wherein the method comprises: the step 4 of constructing the given service network model specifically includes the following substeps:
step 4.1, mixing VaThe value activity in the process is mapped to a specific process node, and the execution mode of the process is determined according to the execution mode of the value activity, wherein the execution mode comprises a sequence mode, a selection mode, a concurrency mode and a circulation mode;
step 4.2, analyzing which Web services are needed to realize the functions defined by the flow nodes to obtain a service list, and further determining the input and output of the services and the related specific service operation;
and 4.3, storing the newly constructed service network model into a service network model database.
6. A cross-border service demand analysis system is characterized by comprising the following modules:
the value network modeling module is used for modeling the relation between the audience-involved core elements and the core elements related to the cross-border service scene, wherein the core elements comprise participants, value objects, value activities and targets;
the target network modeling module is used for further defining targets related in the value network model into an operability target, a functional target and a non-functional target and determining a constraint relation and a decomposition relation among the targets;
and the service network modeling module is used for modeling the process and the service, definitely completing the service required by the function defined by the process and definitely determining the relation between the services.
7. A computer-readable storage medium having instructions stored thereon, characterized in that:
the instructions, when executed by a processor, implement the steps of any of the methods of claims 1-5.
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