1. A method for combined service similarity analysis, comprising:

acquiring a first combined service and a second combined service, wherein the first combined service comprises a plurality of first services, and the second combined service comprises a plurality of second services;

performing service coding on each first service and each second service based on service attributes;

calculating a first similarity between each two of the first services and each two of the second services based on the service codes;

and calculating second similarity of the first combined service and the second combined service based on first similarity between each two first services and each two second services.

2. The method of claim 1, wherein said calculating a first similarity between each of the first services and each of the second services pairwise based on the service code comprises:

and calculating the distance between every two service codes of each first service and each second service, and recording the distance as the first similarity between the corresponding first service and the corresponding second service.

3. The method of claim 2, wherein each of the first services and each of the second services includes a plurality of traffic attributes, and wherein service encoding each of the first services and each of the second services based on the traffic attributes comprises:

performing attribute coding on each service attribute of the first service and the second service according to a preset rule;

and combining the attribute codes of the first service and the second service according to a preset sequence to form the service codes of the first service and the second service.

4. The method of claim 3, wherein said calculating a first similarity between each of the first services and each of the second services pairwise based on the service code comprises:

sequentially comparing attribute codes of corresponding service attributes in the first service and the second service, and counting the same number of attribute codes in the first service and the second service;

and calculating the ratio of the same number of the attribute codes to the total number of the service attributes to obtain the first similarity.

5. The method of claim 1, wherein calculating the second similarity for the first combined service and the second combined service based on the first similarity between each of the first services and each of the second services comprises:

for each first service, comparing the magnitude of a first similarity between the first service and each second service, and recording the maximum similarity as a contribution value of the first service to the second similarity;

and calculating the average value of the contribution values corresponding to the first services to obtain the second similarity.

6. A combination service similarity analysis apparatus, comprising:

the service acquisition module is used for acquiring a first combined service and a second combined service, wherein the first combined service comprises a plurality of first services, and the second combined service comprises a plurality of second services;

a service coding module, configured to perform service coding on each of the first services and each of the second services based on a service attribute;

the first similarity calculation module is used for calculating a first similarity between each two first services and each two second services based on the service codes;

and the second similarity calculation module is used for calculating the second similarity of the first combined service and the second combined service based on the first similarity between each two first services and each two second services.

7. The apparatus of claim 6, wherein the first similarity calculation module comprises:

and the distance calculation unit is used for calculating the distance between every two service codes of each first service and each second service, and recording the distance as the first similarity between the corresponding first service and the corresponding second service.

8. The apparatus of claim 7, each of the first services and each of the second services comprising a plurality of service attributes, the service encoding module comprising:

the attribute coding unit is used for performing attribute coding on each service attribute of the first service and the second service according to a preset rule;

and the service coding unit is used for combining the attribute codes of the first service and the second service according to a preset sequence to form the service codes of the first service and the second service.

9. The apparatus of claim 8, the distance calculation unit comprising:

the same service attribute counting unit is used for sequentially comparing the attribute codes of the corresponding service attributes in the first service and the second service and counting the same number of the attribute codes in the first service and the second service;

and the calculating unit is used for calculating the ratio of the same number of the attribute codes to the total number of the service attributes to obtain the first similarity.

10. The apparatus of claim 6, the second similarity calculation module comprising:

a service contribution calculating unit, configured to compare, for each of the first services, a magnitude of a first similarity between the first service and each of the second services, and record a maximum similarity as a contribution value of the first service to the second similarity;

and the similarity calculation unit is used for calculating the mean value of the contribution values corresponding to the first services to obtain the second similarity.

11. A computer system, comprising:

one or more processors;

a memory for storing one or more programs,

wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of any of claims 1-5.

12. A computer readable storage medium having stored thereon executable instructions which, when executed by a processor, cause the processor to carry out the method of any one of claims 1 to 5.

Background

In a bank service system, many combined services are developed, and often related interfaces are called according to business requirements to meet different requirements, so that different combined services have similar functions, the problem of repeated development is caused, and the problem that the service system is not easy to maintain is also caused. If two services call the same interfaces, the two services can be considered to be similar in some functions, and based on the similarity, the two services can be integrated to remove redundant services and improve the utilization efficiency of a service system. How to quickly evaluate whether two services are similar is a technical problem worthy of study.

Disclosure of Invention

In view of the above, the present disclosure provides a method, an apparatus, a computer system, and a storage medium for analyzing similarity of composite services.

One aspect of the present disclosure provides a method for analyzing a combined service similarity, including: acquiring a first combined service and a second combined service, wherein the first combined service comprises a plurality of first services, and the second combined service comprises a plurality of second services; performing service coding on each first service and each second service based on service attributes; calculating a first similarity between each two of the first services and each two of the second services based on the service codes; and calculating second similarity of the first combined service and the second combined service based on first similarity between each two first services and each two second services.

According to an embodiment of the present disclosure, the calculating a first similarity between each of the first services and each of the second services based on the service code includes: and calculating the distance between every two service codes of each first service and each second service, and recording the distance as the first similarity between the corresponding first service and the corresponding second service.

According to an embodiment of the present disclosure, each of the first services and each of the second services includes a plurality of service attributes, and the service encoding each of the first services and each of the second services based on the service attributes includes: performing attribute coding on each service attribute of the first service and the second service according to a preset rule; and combining the attribute codes of the first service and the second service according to a preset sequence to form the service codes of the first service and the second service.

According to an embodiment of the present disclosure, the calculating a first similarity between each of the first services and each of the second services based on the service code includes: sequentially comparing attribute codes of corresponding service attributes in the first service and the second service, and counting the same number of attribute codes in the first service and the second service; and calculating the ratio of the same number of the attribute codes to the total number of the service attributes to obtain the first similarity.

According to an embodiment of the present disclosure, the calculating a second similarity between the first combined service and the second combined service based on a first similarity between each of the first services and each of the second services includes: for each first service, comparing the magnitude of a first similarity between the first service and each second service, and recording the maximum similarity as a contribution value of the first service to the second similarity; and calculating the average value of the contribution values corresponding to the first services to obtain the second similarity.

Another aspect of the present disclosure provides a combination service similarity analysis apparatus, including: the service acquisition module is used for acquiring a first combined service and a second combined service, wherein the first combined service comprises a plurality of first services, and the second combined service comprises a plurality of second services; a service coding module, configured to perform service coding on each of the first services and each of the second services based on a service attribute; the first similarity calculation module is used for calculating a first similarity between each two first services and each two second services based on the service codes; and the second similarity calculation module is used for calculating the second similarity of the first combined service and the second combined service based on the first similarity between each two first services and each two second services.

According to an embodiment of the present disclosure, the first similarity calculation module includes: and the distance calculation unit is used for calculating the distance between every two service codes of each first service and each second service, and recording the distance as the first similarity between the corresponding first service and the corresponding second service.

According to an embodiment of the present disclosure, each of the first services and each of the second services includes a plurality of service attributes, and the service encoding module includes: the attribute coding unit is used for performing attribute coding on each service attribute of the first service and the second service according to a preset rule; and the service coding unit is used for combining the attribute codes of the first service and the second service according to a preset sequence to form the service codes of the first service and the second service.

According to an embodiment of the present disclosure, the distance calculation unit includes: the same service attribute counting unit is used for sequentially comparing the attribute codes of the corresponding service attributes in the first service and the second service and counting the same number of the attribute codes in the first service and the second service; and the calculating unit is used for calculating the ratio of the same number of the attribute codes to the total number of the service attributes to obtain the first similarity.

According to an embodiment of the present disclosure, the second similarity calculation module includes: a service contribution calculating unit, configured to compare, for each of the first services, a magnitude of a first similarity between the first service and each of the second services, and record a maximum similarity as a contribution value of the first service to the second similarity; and the similarity calculation unit is used for calculating the mean value of the contribution values corresponding to the first services to obtain the second similarity.

Another aspect of the present disclosure provides a computer system, including: one or more processors; memory for storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of any of the first aspects.

Another aspect of the disclosure provides a computer-readable storage medium having stored thereon executable instructions that, when executed by a processor, cause the processor to implement the method of any one of the first aspects.

According to the embodiment of the disclosure, the similarity among the combined services is evaluated based on the comparison of the similarity of the business attributes among the services in the combined services, so that the method can be applied to a service system, help developers to find similar combined services, help subsequent service integration and remove redundant services, and further improve the overall efficiency of the service system.

Drawings

The above and other objects, features and advantages of the present disclosure will become more apparent from the following description of embodiments of the present disclosure with reference to the accompanying drawings, in which:

FIG. 1 schematically illustrates an exemplary system architecture to which the composite service similarity analysis method and apparatus of the present disclosure may be applied;

fig. 2 schematically illustrates an application scenario of the composite service similarity analysis method and apparatus according to an embodiment of the present disclosure;

FIG. 3 schematically illustrates a flow diagram of a composite service similarity analysis method according to an embodiment of the present disclosure;

fig. 4 schematically shows a block diagram of a composite service similarity analysis apparatus according to an embodiment of the present disclosure; and

fig. 5 schematically illustrates a block diagram of a computer system 500 suitable for implementing a robot in accordance with an embodiment of the present disclosure.

Detailed Description

Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood that the description is illustrative only and is not intended to limit the scope of the present disclosure. In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present disclosure.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The terms "comprises," "comprising," and the like, as used herein, specify the presence of stated features, steps, operations, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, or components.

All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art unless otherwise defined. It is noted that the terms used herein should be interpreted as having a meaning that is consistent with the context of this specification and should not be interpreted in an idealized or overly formal sense.

Where a convention analogous to "at least one of A, B and C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B and C" would include but not be limited to systems that have a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.). Where a convention analogous to "A, B or at least one of C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B or C" would include but not be limited to systems that have a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.).

The embodiment of the disclosure provides a method and a device for analyzing the similarity of combined services. The method includes an encoding process and a similarity calculation process. And in the encoding process, performing service encoding on each server based on the service attribute of each server. And after the server codes, entering a similarity calculation process, calculating a first similarity between every two services in the two combined services based on the service codes of the server, and obtaining a second similarity for evaluating the first combined service and the second combined copy according to the first similarity.

Fig. 1 schematically illustrates an exemplary system architecture 100 to which the composite service similarity analysis method, apparatus, according to an embodiment of the disclosure, may be applied. It should be noted that fig. 1 is only an example of a system architecture to which the embodiments of the present disclosure may be applied to help those skilled in the art understand the technical content of the present disclosure, and does not mean that the embodiments of the present disclosure may not be applied to other devices, systems, environments or scenarios.

As shown in fig. 1, the system architecture 100 according to this embodiment may include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 serves as a medium for providing communication links between the terminal devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired and/or wireless communication links, and so forth.

The user may use the terminal devices 101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. The terminal devices 101, 102, 103 may have installed thereon various communication client applications, such as a shopping-like application, a web browser application, a search-like application, an instant messaging tool, a mailbox client, and/or social platform software, etc. (by way of example only).

The terminal devices 101, 102, 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.

The server 105 may be a server providing various services, such as a background management server (for example only) providing support for websites browsed by users using the terminal devices 101, 102, 103. The background management server may analyze and perform other processing on the received data such as the user request, and feed back a processing result (e.g., a webpage, information, or data obtained or generated according to the user request) to the terminal device.

It should be noted that the method for analyzing the similarity of a composite service provided by the embodiments of the present disclosure may be generally performed by the server 105. Accordingly, the combined service similarity analysis apparatus provided by the embodiments of the present disclosure may be generally disposed in the server 105. The combined service similarity analysis method provided by the embodiment of the present disclosure may also be executed by a server or a server cluster that is different from the server 105 and is capable of communicating with the terminal devices 101, 102, 103 and/or the server 105. Accordingly, the combined service similarity analysis apparatus provided by the embodiment of the present disclosure may be disposed in a server or a server cluster different from the server 105 and capable of communicating with the terminal devices 101, 102, 103 and/or the server 105. Alternatively, the combined service similarity analysis method provided by the embodiment of the present disclosure may also be executed by the terminal device 101, 102, or 103, or may also be executed by another terminal device different from the terminal device 101, 102, or 103. Accordingly, the combined service similarity analysis apparatus provided by the embodiment of the present disclosure may also be disposed in the terminal device 101, 102, or 103, or in another terminal device different from the terminal device 101, 102, or 103.

For example, the information of each combination server may be originally stored in any one of the terminal apparatuses 101, 102, or 103 (for example, the terminal apparatus 101, but not limited thereto), or stored on an external storage apparatus and may be imported into the terminal apparatus 101. Then, the terminal device 101 may locally perform the combined service similarity analysis method provided by the embodiment of the present disclosure, or transmit information of each combined server to another terminal device, server, or server cluster, and perform the combined service similarity analysis method provided by the embodiment of the present disclosure by another terminal device, server, or server cluster that receives the information of the combined server.

It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.

Fig. 2 schematically illustrates an application scenario of the method and apparatus for combined service similarity analysis according to an embodiment of the present disclosure.

As shown in fig. 2, in the service system, a plurality of downstream services a, b, C, d, e, f, etc. are included, in order to implement some functions, there are often a large number of composite services A, B, C, D, etc. which are composed of a plurality of downstream services, and as development progresses, the number of composite services will gradually increase, but different composite services will have similar functions, for example, composite services a and C, both include downstream services a, b, C, which causes a problem of repeated development, and also causes a problem that the service system is not easy to maintain, and in this case, the same or similar composite services may be merged, so as to reduce redundant services, and improve utilization efficiency of the service system.

Fig. 3 schematically shows a flowchart of a composite service similarity analysis method according to an embodiment of the present disclosure.

As shown in fig. 3, the method includes operations S310 to S340.

S310, acquiring a first combined service and a second combined service, wherein the first combined service comprises a plurality of first services, and the second combined service comprises a plurality of second services.

S320, performing service coding on each of the first services and each of the second services based on the service attribute.

S330, calculating a first similarity between each two first services and each two second services based on the service codes.

S340, calculating a second similarity between the first combined service and the second combined service based on a first similarity between each two of the first service and the second service.

In the embodiment of the disclosure, a first similarity of services included in a composite service is calculated through service attributes of the services, and then a second similarity of the composite service is calculated based on the first similarity.

According to S310, the basic information of the first combined service a and the second combined service B with similarity to be evaluated may be obtained from the preset services, including which services the first combined service a and the second combined service B respectively include, and which service attributes each service has. For example, a first composite service a calls a downstream service a, B, c (i.e., a first service), a composite service B calls a downstream service a, B, d (i.e., a second service), and each downstream service has some business attributes.

According to S320, the service encoding of each of the first services and each of the second services based on the service attribute includes S321 to S322.

S321, performing attribute coding on each service attribute of the first service and the second service according to a preset rule.

According to the embodiment of the present disclosure, a one-hot coding may be performed on each service attribute, for example, assuming that the service attribute has three types, including a type, a function, an application belonging to the type, and a version belonging to the type, where the type includes a product application, a technical support, and a channel application, if the type of the service is the product application, the one-hot coding is preset to be [1, 0, 0], if the type of the service is the technical support, the one-hot coding is preset to be [0, 1, 0], and if the type of the service is the channel application, the one-hot coding is preset to be [0, 0, 1 ].

S322, combining the attribute codes of the first service and the second service according to a preset sequence to form a service code of each of the first service and the second service.

In this embodiment of the present disclosure, each of the first services and each of the second services include a plurality of service attributes, and each service attribute includes a service type, a service function, an application to which the service belongs, a version to which the service belongs, and the like. Suppose a service includes four service attributes of service type, service function, application and version, the specific attribute code of each attribute is [1, 0, 0], [0, 0, 1], [0, 1, 0], [0, 0, 1], and the combination of these codes in sequence, the corresponding service code is [1, 0, 0, 0, 0, 0, 1, 0, 1 ].

Optionally, according to operation S330, the calculating a first similarity between each two of the first service and each second service based on the service code may specifically include S331.

S331, calculating a distance between each two service codes of each of the first services and each of the second services, and recording the distance as a first similarity between the corresponding first service and the corresponding second service.

According to S331, the service code may be used as a vector, and the degree of similarity between the first service and the second service may be represented by calculating a euclidean distance between vector representations of the first service and the second service.

Optionally, operation S330 may further include S332 to S333.

S332, sequentially comparing the attribute codes of the corresponding service attributes in the first service and the second service, and counting the number of the attribute codes in the first service and the second service which are the same.

S333, calculating the ratio of the same number of the attribute codes to the total number of the service attributes to obtain the first similarity.

Unlike step S331, S332 evaluates the degree of similarity between the first service and the second service by counting the number of the same service attributes therebetween. For example, the composite service a calls a downstream service a, B, c (i.e. a first service), the composite service B calls a downstream service a, B, d (i.e. a second service), and the downstream services a, B, c, d all have some attributes, and assuming that the attribute codes of the service type, the service function, the belonging application, and the belonging version of the first service a are [1, 0, 0], [0, 0, 1], [0, 1, 0], [0, 0, 1], respectively, and the attribute codes of the service type, the service function, the belonging application, and the belonging version of the second service d are [0, 1, 0], [0, 0, 1], [1, 0], [0, 1, 0], respectively, and the same service attribute between the first service a and the second service d is 1, and the total number of service attributes is 4, sim ad) is (1/4 ═ 0.25; for another example, if the service type, service function, belonging application, and belonging version of the first service b are [0, 0, 1], [1, 0, 0], [0, 1, 0], and the service type, service function, belonging application, and belonging version of the second service a are [0, 0, 1], [0, 1, 0], and the total number of service attributes is 4, then sim (ba) is 3/4, 0.75.

According to S340, calculating the second similarity of the first combined service and the second combined service based on the first similarity between each pair of the first service and each pair of the second service includes operations S341 to S342.

S341, for each of the first services, comparing the first similarity between the first service and each of the second services, and recording the maximum similarity as a contribution value of the first service to the second similarity.

For example, the first combined service a includes first services a, B, and c, the second combined service B includes second services a, B, and d, the first service a is first compared with the second services a, B, and d, and if sim (aa) is 1, sim (ab) is 0.3, and sim (ad) is 0.5, the maximum value 1 is taken as the final contribution value of the first service a to the second similarity, and similarly, the first service B is compared with the second services a, B, and d, and the second service c and the second services a, B, and d are then obtained corresponding contribution values, respectively.

S342, calculating an average of the contribution values corresponding to the first services to obtain the second similarity.

Assuming that the contribution values of the first services a, B, and c are 1, and 0.6, respectively, the second similarity between the first composite service a and the second composite service B is (1+1+0.6)/3 ═ 0.87.

According to the combined service similarity analysis method provided by the disclosure, the similarity between the combined services is evaluated based on the comparison of the similarity of the business attributes between the services in the combined services, and the combined service similarity analysis method can be applied to a service system, helps developers to find similar combined services, helps subsequent service integration, removes redundant services, and accordingly improves the overall efficiency of the service system.

Fig. 4 schematically shows a block diagram of a composite service similarity analysis apparatus according to an embodiment of the present disclosure.

As shown in fig. 4, a combined service similarity analysis apparatus 400 provided in an embodiment of the present disclosure includes: the system comprises a service acquisition module 410, a service coding module 420, a first similarity calculation module 430 and a second similarity calculation module 440.

The service obtaining module 410 is configured to obtain a first combined service and a second combined service, where the first combined service includes a plurality of first services, and the second combined service includes a plurality of second services.

A service coding module 420, configured to perform service coding on each of the first services and each of the second services based on a service attribute.

A first similarity calculation module 430, configured to calculate a first similarity between each pair of the first service and each pair of the second service based on the service code.

A second similarity calculation module 440, configured to calculate a second similarity of the first combined service and the second combined service based on a first similarity between each pair of the first service and each pair of the second service.

Wherein the first similarity calculation module 430 includes: a distance calculation unit 431.

The distance calculating unit 431 is configured to calculate a distance between each two service codes of each of the first services and each of the second services, where the distance is a first similarity between the corresponding first service and the corresponding second service.

Each of the first services and each of the second services include a plurality of service attributes, and the service encoding module 420 includes: attribute encoding unit 421 and service encoding unit 422.

An attribute encoding unit 421, configured to perform attribute encoding on each service attribute of the first service and the second service according to a preset rule.

A service encoding unit 422, configured to combine the attribute codes of the first service and the second service according to a preset order, respectively, to form a service code of each of the first service and the second service.

The distance calculation unit 431 may include: a same service attribute counting unit 432 and a calculating unit 433.

A same service attribute counting unit 432, configured to compare attribute codes of corresponding service attributes in the first service and the second service in sequence, and count the number of attribute codes in the first service and the second service that are the same.

A calculating unit 433, configured to calculate a ratio between the same number of the attribute codes and a total number of the service attributes, so as to obtain the first similarity.

The second similarity calculation module 440 includes: a service contribution calculating unit 441 and a similarity calculating unit 442.

The service contribution calculating unit 441 is configured to, for each of the first services, compare magnitudes of first similarities between the first service and the second services, and record a maximum similarity as a contribution value of the first service to the second similarities.

The similarity calculation unit 442 is configured to calculate an average of the contribution values corresponding to the first services, so as to obtain the second similarity.

Any number of modules, sub-modules, units, sub-units, or at least part of the functionality of any number thereof according to embodiments of the present disclosure may be implemented in one module. Any one or more of the modules, sub-modules, units, and sub-units according to the embodiments of the present disclosure may be implemented by being split into a plurality of modules. Any one or more of the modules, sub-modules, units, sub-units according to embodiments of the present disclosure may be implemented at least in part as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented in any other reasonable manner of hardware or firmware by integrating or packaging a circuit, or in any one of or a suitable combination of software, hardware, and firmware implementations. Alternatively, one or more of the modules, sub-modules, units, sub-units according to embodiments of the disclosure may be at least partially implemented as a computer program module, which when executed may perform the corresponding functions.

For example, any plurality of the service acquiring module 410, the service encoding module 420, the first similarity calculating module 430, and the second similarity calculating module 440 may be combined and implemented in one module/unit/sub-unit, or any one of the modules/units/sub-units may be split into a plurality of modules/units/sub-units. Alternatively, at least part of the functionality of one or more of these modules/units/sub-units may be combined with at least part of the functionality of other modules/units/sub-units and implemented in one module/unit/sub-unit. According to an embodiment of the present disclosure, at least one of the service obtaining module 410, the service encoding module 420, the first similarity calculation module 430, and the second similarity calculation module 440 may be implemented at least partially as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented in hardware or firmware in any other reasonable manner of integrating or packaging a circuit, or implemented in any one of three manners of software, hardware, and firmware, or in a suitable combination of any several of them. Alternatively, at least one of the service acquisition module 410, the service encoding module 420, the first similarity calculation module 430, and the second similarity calculation module 440 may be at least partially implemented as a computer program module, which, when executed, may perform a corresponding function.

It should be noted that, in the embodiment of the present disclosure, the combined service similarity analysis device portion corresponds to the combined service similarity analysis method portion in the embodiment of the present disclosure, and the description of the combined service similarity analysis device portion specifically refers to the combined service similarity analysis method portion, which is not described herein again.

Fig. 5 schematically illustrates a block diagram of a computer system suitable for implementing the above-described method according to an embodiment of the present disclosure. The computer system illustrated in FIG. 5 is only one example and should not impose any limitations on the scope of use or functionality of embodiments of the disclosure.

As shown in fig. 5, a computer system 500 according to an embodiment of the present disclosure includes a processor 501, which can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)502 or a program loaded from a storage section 508 into a Random Access Memory (RAM) 503. The processor 501 may comprise, for example, a general purpose microprocessor (e.g., a CPU), an instruction set processor and/or associated chipset, and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), among others. The processor 501 may also include onboard memory for caching purposes. Processor 501 may include a single processing unit or multiple processing units for performing different actions of a method flow according to embodiments of the disclosure.

In the RAM 503, various programs and data necessary for the operation of the system 500 are stored. The processor 501, the ROM 502, and the RAM 503 are connected to each other by a bus 504. The processor 501 performs various operations of the method flows according to the embodiments of the present disclosure by executing programs in the ROM 502 and/or the RAM 503. Note that the programs may also be stored in one or more memories other than the ROM 502 and the RAM 503. The processor 501 may also perform various operations of method flows according to embodiments of the present disclosure by executing programs stored in the one or more memories.

According to an embodiment of the present disclosure, system 500 may also include an input/output (I/O) interface 505, input/output (I/O) interface 505 also being connected to bus 504. The system 500 may also include one or more of the following components connected to the I/O interface 505: an input portion 506 including a keyboard, a mouse, and the like; an output portion 507 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 508 including a hard disk and the like; and a communication section 509 including a network interface card such as a LAN card, a modem, or the like. The communication section 509 performs communication processing via a network such as the internet. The driver 510 is also connected to the I/O interface 505 as necessary. A removable medium 511 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 510 as necessary, so that a computer program read out therefrom is mounted into the storage section 508 as necessary.

According to embodiments of the present disclosure, method flows according to embodiments of the present disclosure may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable storage medium, the computer program containing program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 509, and/or installed from the removable medium 511. The computer program, when executed by the processor 501, performs the above-described functions defined in the system of the embodiments of the present disclosure. The systems, devices, apparatuses, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the present disclosure.

The present disclosure also provides a computer-readable storage medium, which may be contained in the apparatus/device/system described in the above embodiments; or may exist separately and not be assembled into the device/apparatus/system. The computer-readable storage medium carries one or more programs which, when executed, implement the method according to an embodiment of the disclosure.

According to an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium. Examples may include, but are not limited to: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

For example, according to embodiments of the present disclosure, a computer-readable storage medium may include ROM 502 and/or RAM 503 and/or one or more memories other than ROM 502 and RAM 503 described above.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

Those skilled in the art will appreciate that various combinations and/or combinations of features recited in the various embodiments and/or claims of the present disclosure can be made, even if such combinations or combinations are not expressly recited in the present disclosure. In particular, various combinations and/or combinations of the features recited in the various embodiments and/or claims of the present disclosure may be made without departing from the spirit or teaching of the present disclosure. All such combinations and/or associations are within the scope of the present disclosure.

The embodiments of the present disclosure have been described above. However, these examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments are described separately above, this does not mean that the measures in the embodiments cannot be used in advantageous combination. The scope of the disclosure is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be devised by those skilled in the art without departing from the scope of the present disclosure, and such alternatives and modifications are intended to be within the scope of the present disclosure.