CN115525365A - Method, device and equipment for determining target data entity and storage medium - Google Patents

Abstract

The disclosure provides a method, a device, equipment and a storage medium for determining a target data entity, which can be applied to the technical field of big data. The method comprises the following steps: determining a target business component related to the target task from the plurality of business components according to the target task; determining a data entity corresponding to a target service component in the multiple data entities as a first data entity to obtain a first set; and determining a target data entity matched with the target task according to the first set.

Description

Method, device and equipment for determining target data entity and storage medium

Technical Field

The present disclosure relates to the field of big data, and in particular, to a method for determining a target data entity, an apparatus for determining a target data entity, an electronic device, a computer-readable storage medium, and a computer program product.

Background

In the process of executing the task, the processing procedures of a plurality of data entities are involved, and the task has a matching relationship with the plurality of data entities. For example, the task of "collecting counterfeit money" involves processing a plurality of data entities such as "counterfeit money collection register", "counterfeit money identification information", "participant name information", "participant identification information", and "banknote serial number information", and thus it is necessary to establish a matching relationship between the task of "collecting counterfeit money" and the plurality of data entities in advance.

In the process of flow modeling, when a task is modeled, a data entity having a matching relationship with the task needs to be determined from a plurality of data entities, so that the task is ensured to be normally executed.

Disclosure of Invention

In view of the above, the present disclosure provides a method of determining a target data entity, an apparatus for determining a target data entity, an electronic device, a computer readable storage medium and a computer program product.

According to a first aspect of the present disclosure, there is provided a method of determining a target data entity, comprising: according to a target task, determining a target business component related to the target task from a plurality of business components; determining a data entity corresponding to the target service component in the plurality of data entities as a first data entity to obtain a first set; and determining a target data entity matched with the target task according to the first set.

According to another embodiment of the present disclosure, the determining, according to the first set, a target data entity matching the target task comprises: for each first data entity in the first set, determining a data entity which satisfies a predetermined relationship with the first data entity in the plurality of data entities as a second data entity, and obtaining a second set corresponding to the first set; and determining a target data entity matched with the target task according to the first set and the second set.

According to another embodiment of the present disclosure, the predetermined relationship includes: the second data entity is an ancestor entity of the first data entity; or the second data entity is a descendant entity of the first data entity.

According to another embodiment of the present disclosure, the name of the target task includes a task noun, and the names of the plurality of data entities each include an entity noun; the method further comprises the following steps: determining the data entities in the current preset set, wherein the entity nouns are matched with the task nouns, and determining the data entities as third data entities to obtain a third set; wherein the determining, according to the first set and the second set, a target data entity matching the target task comprises: determining the target set of data entities from the first set, the second set, and the third set.

According to another embodiment of the disclosure, the determining the target set of data entities from the first set, the second set, and the third set comprises: showing the first set, the second set, and the third set; and in response to receiving a selection instruction, determining the data entity indicated by the selection instruction as the target data entity.

According to another embodiment of the present disclosure, the name of the target task includes a task noun, and the names of the plurality of data entities each include an entity noun; the method further comprises the following steps: determining the data entities in the current preset set, wherein the entity nouns are matched with the task nouns, and determining the data entities as third data entities to obtain a third set; wherein the determining, according to the first set, a target data entity that matches the target task comprises: and determining a target data entity matched with the target task according to the first set and the third set.

According to another embodiment of the present disclosure, further comprising: adding the target data entity to the current predetermined set to update the current predetermined set.

A second aspect of the present disclosure provides an apparatus for determining a target data entity, comprising: the task processing device comprises a first determining module, a second determining module and a third determining module, wherein the first determining module is used for determining a target business component related to a target task from a plurality of business components according to the target task. The second determining module is configured to determine, as the first data entity, a data entity corresponding to the target service component from among the multiple data entities, so as to obtain a first set. And the third determining module is used for determining a target data entity matched with the target task according to the first set.

A third aspect of the present disclosure provides an electronic device, comprising: 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 perform the above-described method.

A fourth aspect of the present disclosure also provides a computer-readable storage medium having stored thereon executable instructions that, when executed by a processor, cause the processor to perform the above-described method.

A fifth aspect of the disclosure also provides a computer program product comprising a computer program which, when executed by a processor, implements the above method.

According to the method, the device, the equipment, the medium and the program product for determining the target data entity, the target business component related to the target task is determined firstly, and then the target data entity is determined based on the data entity corresponding to the target business component, so that the selection range of the data entity can be narrowed by utilizing the business component, the efficiency of establishing the matching relationship between the target task and the target data entity is improved, and the effect of improving the task modeling efficiency is realized.

Drawings

The foregoing and other objects, features and advantages of the disclosure will be apparent from the following description of embodiments of the disclosure, which proceeds with reference to the accompanying drawings, in which:

fig. 1 schematically illustrates an application scenario diagram of determining a target data entity according to an embodiment of the present disclosure;

FIG. 2 schematically illustrates a flow chart of a method of determining a target data entity according to an embodiment of the present disclosure;

FIG. 3 schematically illustrates a flow chart of a method of determining a target data entity according to another embodiment of the present disclosure;

FIG. 4 schematically illustrates a flow chart of a method of determining a target data entity according to another embodiment of the present disclosure;

FIG. 5 schematically illustrates a flow chart of a method of determining a target data entity according to another embodiment of the present disclosure;

FIG. 6 schematically illustrates a schematic diagram of a method of determining a target data entity, in accordance with an embodiment of the present disclosure;

FIG. 7 is a block diagram schematically illustrating an apparatus for determining a target data entity according to an embodiment of the present disclosure; and

fig. 8 schematically shows a block diagram of an electronic device adapted to implement a method of determining a target data entity according to 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 to which this invention belongs, 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.

In those instances 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, and C together, etc.).

In the technical scheme of the disclosure, the collection, storage, use, processing, transmission, provision, disclosure, application and other processing of the personal information of the related user are all in accordance with the regulations of related laws and regulations, necessary confidentiality measures are taken, and the customs of the public order is not violated.

In the technical scheme of the disclosure, the processing of data acquisition, collection, storage, use, processing, transmission, provision, disclosure, application and the like all conform to the regulations of relevant laws and regulations, necessary security measures are taken, and the customs of public sequences is not violated.

To facilitate understanding of the technical solutions provided in the present disclosure, the technical terms involved are explained.

Moving: and a certain flow with definite purpose and creative value is completed from the enterprise level. For example, "apply for credit card" may be an activity and "deposit" may be an activity.

Task: an activity may include multiple tasks for the purpose of completing task items with clear business goals for the activity, for example, an "apply for credit card" activity may include "submit a request form", "review information", "approve card", and the like. For another example, a "deposit" activity may include a plurality of tasks such as "collect counterfeit money", "record a large deposit register", "check deposit data", "notify of counterfeit money finding", "register large deposit information", and the like.

And (4) service components: in the process model, all activities are subjected to cluster analysis, the activity business process sequence, the created entities and the relationship between the activities and the entities are fully considered, and the activities or refined tasks are further clustered and combined to form a business component. Each business component may be a functional module, and if at least one business component can execute a task, the at least one business component corresponds to the task. For example, the "submit application form" task described above may be performed by one business component, and the "audit information" task may be performed by another component.

The head responsibility service component: for a data entity, the business component used to create and maintain the data entity is called the incumbent business component, and other non-incumbent business components may multiplex the data entity. For example, the chief business component of the "counterfeit money collection registry" data entity is the operations distribution component, and the chief business component of the "participant" data entity is the customer information management component.

A data entity: and (4) carrying out structured expression on the service logic and the meaning thereof extracted from the entity according to the service essence. In a database, a data entity may represent a collection of something, such as a structural table including the name of a person and the age of the person in the database, and the two structural tables may be abstracted as one "basic information of person" data entity. A task corresponds to a plurality of data entities if the task involves processing the data entities during execution.

And (3) data model: is a uniform data view within the enterprise, is a series of specifications and related icons reflecting data requirements and design.

In some technical solutions, candidate data entities may be presented to a worker, the worker manually selects a matching data entity from the candidate data entities, and an association relationship is established between the manually selected data entity and a task.

It should be noted that the manual selection method can achieve better results under the condition of a small number of data entities. However, the number of data entities has reached thousands at present, and the number is still growing.

It can be understood that, due to the large number of data entities, on one hand, the work of establishing the association relationship between the tasks and the data entities has high requirements on the professional performance of the workers, and the workers need to be trained by related businesses to complete the work. On the other hand, the manual processing efficiency is low, when the number of tasks is large, multiple users need to be arranged for processing, each task needs to inquire all data entities, and if the names of the data entities are similar, the detailed information of the data entities needs to be checked to determine whether the data entities are matched with the tasks.

The embodiment of the disclosure aims to provide a method for determining a target data entity, which can define a mapping range of a target task, wherein the mapping range comprises a plurality of data entities which are possibly matched with the target task, and the number of the number entities in the mapping range is far less than that of the existing data entities, so that the task is quickly matched with the data entities.

Fig. 1 schematically shows an application scenario diagram of determining a target data entity according to an embodiment of the present disclosure.

As shown in fig. 1, the application scenario 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, wireless communication links, or fiber optic cables, to name a few.

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 shopping-like applications, web browser applications, search-like applications, instant messaging tools, mailbox clients, 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 determining the target data entity provided by the embodiments of the present disclosure may be generally performed by the server 105. Accordingly, the apparatus for determining a target data entity provided by the embodiments of the present disclosure may be generally disposed in the server 105. The method of determining a target data entity provided by the embodiments of the present disclosure may also be performed by a server or a cluster of servers different from the server 105 and capable of communicating with the terminal devices 101, 102, 103 and/or the server 105. Accordingly, the apparatus for determining the target data entity provided by the embodiment of the present disclosure may also 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.

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.

The method for determining a target data entity of the disclosed embodiment will be described in detail below with fig. 2 to 6 based on the scenario described in fig. 1.

Fig. 2 schematically shows a flow chart of a method of determining a target data entity according to an embodiment of the present disclosure.

As shown in fig. 2, the method 200 of determining a target data entity of this embodiment includes operations S210 to S230.

In operation S210, a target business component related to a target task is determined from among a plurality of business components according to the target task.

For example, an activity may include multiple tasks. For example, an "apply for credit card" activity may include tasks such as "submit a request form", "audit information", "approve card", and the like. For another example, a "deposit" activity may include a plurality of tasks such as "collect counterfeit money", "record a large deposit register", "review deposit material", "notify of counterfeit money finding", "record large deposit information", and the like. The target task may represent any task that needs to be performed.

For example, each business component can be a functional module for performing a predetermined function, at least one business component collectively performing a task, the at least one business component being associated with the task.

For example, a correspondence between a task and a business component may be established in advance, and then the business component corresponding to the target task is determined as the target business component based on the correspondence.

For another example, the plurality of business components may be displayed through a human-computer interaction interface, so that a worker may select a target business component according to a requirement, the selection operation may trigger a first instruction, and the target business component may be determined from the plurality of business components according to the first instruction.

In operation S220, a data entity corresponding to the target service component among the plurality of data entities is determined as a first data entity, so as to obtain a first set.

For example, each business component may correspond to a plurality of data entities, where the correspondence indicates that the business component creates, maintains, uses, etc. the data entities in the process of implementing the predetermined function. For example, the "customer information management" business component may correspond to a data entity such as "participant information", "participant name information", "participant identification information", and the like.

For example, a corresponding relationship between a business component and a data entity may be predetermined, and then a data entity corresponding to a target business component is determined from a plurality of data entities based on the corresponding relationship.

In operation S230, a target data entity matching the target task is determined according to the first set.

For example, a first data entity in the first set may be presented through a human-computer interaction interface, so that a worker may select a target data entity according to a requirement, the selection operation may trigger a second instruction, and the target data entity may be determined from the first set according to the second instruction.

According to the technical scheme provided by the embodiment of the disclosure, the target business component related to the target task is determined, and then the target data entity is determined based on the data entity corresponding to the target business component. It should be noted that the number of data entities is much larger than the number of business components, for example, 5000 data entities may correspond to 150 business components.

Therefore, compared with a mode of displaying all data entities to a worker and then selecting a target data entity from the data entities, the method and the system for establishing the matching relationship between the target task and the target data entity can reduce the selection range of the data entities by using the service component, so that the efficiency of establishing the matching relationship between the target task and the target data entity is improved, and the effect of improving the task modeling efficiency is achieved.

Fig. 3 schematically shows a flow chart of a method of determining a target data entity according to another embodiment of the present disclosure.

As shown in fig. 3, the method 300 for determining a target data entity of this embodiment includes operations S310 to S320, and further includes operations S331 to S332, where the operations S310 and S320 may refer to the operations S210 and S220, which are not described herein again.

In operation S331, for each first data entity in the first set, a data entity that satisfies a predetermined relationship with the first data entity in the plurality of data entities is determined as a second data entity, and a second set corresponding to the first set is obtained.

For example, the predetermined relationship may be an ancestral descendant relationship, e.g., the second data entity is an ancestral entity of the first data entity, e.g., the second data entity is a descendant entity of the first data entity. Preferably the second data entity is a parent entity of the first data entity.

For example, the sub-entities of the "participant information" data entity may include "participant identification information," which may represent an individual user or a corporate user receiving the services provided by a banking site, a "participant contract and participant correspondence," which may include a name, organization code, etc., a "correspondence between a participant and a participant role," and so on.

The second data entity and the first data entity meet the ancestor descendant relationship, and the first data entity can be effectively expanded through the ancestor descendant relationship, so that the second data entity with higher association probability with the target task is obtained.

In operation S332, a target data entity matching the target task is determined according to the first set and the second set.

For example, the data entities in the first set and the second set may be displayed through a human-computer interaction interface, that is, all the first data entities and all the second data entities are displayed, so that a worker may select a target data entity according to a requirement, the selection operation may trigger a third instruction, and the target data entity may be determined from the first set and the second set according to the third instruction.

According to the technical scheme provided by the embodiment of the disclosure, the first data entity is expanded to obtain the second data entity, and the target data entity is determined based on the first data entity and the second data entity, so that the selection range of the target data entity can be increased in a targeted manner, and the influence on the accuracy of the data entity caused by the over-small limitation of the selection range of the target data entity is avoided.

Fig. 4 schematically shows a flow chart of a method of determining a target data entity according to another embodiment of the present disclosure.

As shown in fig. 4, the method 400 of determining a target data entity of this embodiment includes operation S410, operation S420, operation S433, and operation S440.

It should be noted that, reference may be made to the above operations S210 and S220 in the operations S410 and S420, and details are not described herein again. Operation S433 is used instead of operation S331 to operation S332 in the above-described embodiment. The sequence of the operations S440, S410, and S420 is not limited in the embodiment of the present disclosure, and the operations S440 may be executed before the operation S433.

In operation S440, the data entities in the current predetermined set, of which the entity nouns match the task nouns, are determined as third data entities, so as to obtain a third set.

For example, the predetermined set may comprise several data entities, which may be a subset of the set of all data entities.

In one example, some data entities may be screened from all data entities in advance to form the predetermined set.

In another example, the predetermined set may be an empty set when the flow is first executed, and then the target data entity is added to the predetermined set to effect the updating and expanding of the predetermined set. For example, the target data entity may be added to the predetermined set after the flow is executed for the first time and the target data entity is obtained, and then, when the flow is executed for the second time, the updated predetermined set may be expanded for the last time to determine the third data entity.

For example, the task name may include a verb and a noun, the data entity name includes a noun, and for convenience of distinction, the noun in the task name is referred to as including a task noun, and the noun in the data entity name is referred to as an entity noun.

For example, verbs in a task name may include buy, build, develop, extract, rent, receive, reclaim, subscribe, authorize, enable, execute, build, generate, implement, collect, and the like. Nouns in the name of the target task may include participants, coupons, business values, regulatory information, and the like. The combination of verbs and names can obtain the name of the task, for example, the name of the task may include "collect counterfeit money", "record large deposit register", "review deposit data", "notify of counterfeit money finding", "record large deposit information", "build deposit data", and the like.

For example, the names of data entities may include participants, participant roles, participant contracts, participant and resource item ownership relationships, participant roles and conditional relationships, and so forth.

For example, it may be determined that a noun matches a task noun where the noun is the same as or similar to the task noun. For example, the text similarity and/or semantic similarity between entity nouns and task nouns may be calculated, and the entity nouns and task nouns may be determined to match in the case that the text similarity and/or semantic similarity each reach a corresponding threshold.

In operation S433, a target data entity matching the target task is determined according to the first set and the third set.

For example, the data entities in the first set and the third set, that is, all the first data entities and all the third data entities, may be presented through a human-computer interaction interface, so that a worker may select a target data entity according to a requirement, and the selecting operation may trigger a fourth instruction, according to which the target data entity may be determined from the first set and the third set.

According to the technical scheme provided by the embodiment of the disclosure, as the third data entity is obtained by expanding the nouns in the nouns of the target task and the target data entity is determined based on the first data entity and the third data entity, the selection range of the target data entity can be increased in a targeted manner, and the influence on the accuracy of the data entity caused by the over-small limitation of the selection range of the target data entity is avoided.

Fig. 5 schematically shows a flow chart of a method of determining a target data entity according to another embodiment of the present disclosure.

It should be noted that, in the above embodiments, the embodiment shown in fig. 2 may determine the target data entity by using the first data entity, the embodiment shown in fig. 3 may determine the target data entity by using the first data entity and the second data entity, and the embodiment shown in fig. 4 may determine the target data entity by using the first data entity and the third data entity. In this embodiment, the embodiments shown in fig. 3 and fig. 4 may be combined and improved, so as to determine the target data entity by using the first data entity, the second data entity and the third data entity.

As shown in fig. 5, the method 500 of determining a target data entity of this embodiment includes operation S510, operation S520, operation S534, operation S535, and operation S540.

It should be noted that, the operations S510, S520, and S540 may refer to the operations S410, S420, and S440, respectively, which are not described herein again. Operations S534 through S535 may be used instead of operations S331 through S332 in the above-described embodiment, or may be used instead of S433 in the above-described embodiment.

In operation S534, for each first data entity in the first set, a data entity that satisfies a predetermined relationship with the first data entity in the plurality of data entities is determined as a second data entity, resulting in a second set corresponding to the first set.

For example, refer to the operation S331 mentioned above in this embodiment, which is not described herein.

In operation S535, a target set of data entities is determined according to the first set, the second set, and the third set.

For example, the data entities in the first set, the second set and the third set may be displayed through a human-computer interaction interface, that is, all the first data entities, all the second data entities and all the third data entities are displayed, so that a worker may select a target data entity according to a requirement, the selection operation may trigger a selection instruction, and the target data entity may be determined from the first set, the second set and the third set according to the data entity indicated by the selection instruction.

According to the technical scheme provided by the embodiment of the disclosure, because the first data entity is used for expanding to obtain the second data entity, the noun in the noun of the target task is also used for expanding to obtain the third data entity, and the target data entity is determined based on the first data entity, the second data entity and the third data entity, the selection range of the target data entity can be increased in a targeted manner, and the influence on the accuracy of the data entity caused by the fact that the selection range of the target data entity is too small is avoided.

According to another embodiment of the present disclosure, it is considered that in practical applications, tasks may be adjusted according to practical requirements, for example, functions of the tasks are extended, and thus data entities corresponding to the tasks may also be changed accordingly. To accommodate this, the target data entity may also be added to the current predefined set after the target data entity is determined as described above to update the current predefined set.

FIG. 6 schematically illustrates a schematic diagram of a method of determining a target data entity according to an embodiment of the present disclosure.

As shown in fig. 6, in this embodiment, a worker may edit a target task 601, and the edited content may include information of fields such as a number, a task name, an activity to which the task belongs, a responsible person, a purpose, a definition, and a scope in basic information.

Then, a target business component 603 corresponding to the target task 601 is selected from the business components 602, then, the association relationship between the business component and the data entity is read from the database, and based on the association relationship, a plurality of first data entities A1 corresponding to the target business component 603 are determined from the data entities 604, so as to obtain a first set.

Then for each first data entity A1 605, the parent entity of the first data entity A1 605 is determined to be the second data entity A2 606, resulting in a second set.

Next, considering that the task name includes a verb and a task noun, and the data entity name includes a entity noun, the data entity whose entity noun matches the task noun in the predetermined set 607 may also be determined as a third data entity A3 608, resulting in a third set. The initial predetermined set 607 may be an empty set.

Through the above operations, three sets, i.e., a first set, a second set, and a third set, may be obtained, and then the target data entity may be determined based on the three sets. For example, data entities in three sets may be presented for a worker to select matching data entities from the three sets, and the selected matching data entities are determined as target data entities.

Furthermore, data entities that match the selection may also be added to the predefined set 607, thereby enabling an expansion of the predefined set 607.

It should be noted that, in some cases, for example, in the case that the data entities in the three sets do not match the target task 601 or in other cases, the fourth data entity A4 609 may also be manually added, and the fourth data entity A4 609 is added to the predetermined set 607, so as to implement the expansion of the predetermined set 607.

By adopting the technical scheme, when the matching relation between the tasks and the data entities is processed, a layer of service components is added between the tasks and the data entities, and the range of the data entities is narrowed down by utilizing the service components, so that the processing efficiency is improved. In addition, the predetermined set 607 can be expanded by using the target data entity, so that the application to the change task is realized, and the application range of the scheme is enlarged.

Based on the method for determining the target data entity, the disclosure also provides a device for determining the target data entity. The apparatus will be described in detail below with reference to fig. 7.

Fig. 7 schematically shows a block diagram of the apparatus for determining a target data entity according to an embodiment of the present disclosure.

As shown in fig. 7, the apparatus 700 for determining a target data entity of this embodiment includes a first determining module 710, a second determining module 720 and a third determining module 730.

The first determining module 710 is configured to determine a target business component related to a target task from a plurality of business components according to the target task. In an embodiment, the first determining module 710 may be configured to perform the operation S210 described above, which is not described herein again.

The second determining module 720 is configured to determine, as the first data entity, a data entity corresponding to the target service component from the multiple data entities, so as to obtain a first set. In an embodiment, the second determining module 720 may be configured to perform the operation S220 described above, which is not described herein again.

The third determining module 730 is configured to determine a target data entity matching the target task according to the first set. In an embodiment, the third determining module 730 may be configured to perform the operation S230 described above, which is not described herein again.

According to another embodiment of the present disclosure, the third determining module includes: a first determination submodule and a second determination submodule. The first determining submodule is used for determining a data entity meeting a preset relation with the first data entity in the plurality of data entities as a second data entity aiming at each first data entity in the first set to obtain a second set corresponding to the first set; and the second determining submodule is used for determining the target data entity matched with the target task according to the first set and the second set.

According to another embodiment of the present disclosure, the predetermined relationship includes: the second data entity is an ancestor entity of the first data entity; or the second data entity is a descendant entity of the first data entity.

According to another embodiment of the present disclosure, the name of the target task includes a task noun, and the names of the plurality of data entities each include an entity noun; the device still includes: a fourth determining module, configured to determine, as a third data entity, a data entity in the current predetermined set, where the entity noun matches the task noun, to obtain a third set; wherein the second determination submodule includes: and the determining unit is used for determining the target data entity set according to the first set, the second set and the third set.

According to another embodiment of the present disclosure, the determining unit includes: a presentation subunit and a determination subunit. The display subunit is used for displaying the first set, the second set and the third set; the determining subunit is configured to determine, in response to receiving the selection instruction, the data entity indicated by the selection instruction as the target data entity.

According to another embodiment of the present disclosure, the name of the target task includes a task noun, and the names of the plurality of data entities each include an entity noun; the device still includes: a fifth determining module, configured to determine, as a third data entity, a data entity whose entity nouns match the task nouns in the current predetermined set, so as to obtain a third set; wherein the third determining module comprises: and the third determining submodule is used for determining the target data entity matched with the target task according to the first set and the third set.

According to another embodiment of the present disclosure, the above apparatus further comprises: and the adding module is used for adding the target data entity into the current preset set so as to update the current preset set.

According to an embodiment of the present disclosure, any plurality of the first determining module 710, the second determining module 720, and the third determining module 730 may be combined into one module to be implemented, or any one of the modules may be split into a plurality of modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of the other modules and implemented in one module. According to an embodiment of the present disclosure, at least one of the first determining module 710, the second determining module 720, and the third determining module 730 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 in any one of three implementations of software, hardware, and firmware, or in any suitable combination of any of them. Alternatively, at least one of the first determining module 710, the second determining module 720 and the third determining module 730 may be at least partially implemented as a computer program module, which when executed, may perform a corresponding function.

Fig. 8 schematically shows a block diagram of an electronic device adapted to implement a method of determining a target data entity according to an embodiment of the present disclosure.

As shown in fig. 8, an electronic device 800 according to an embodiment of the present disclosure includes a processor 801 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 802 or a program loaded from a storage section 808 into a Random Access Memory (RAM) 803. The processor 801 may include, for example, a general purpose microprocessor (e.g., CPU), an instruction set processor and/or associated chipset, and/or a special purpose microprocessor (e.g., application Specific Integrated Circuit (ASIC)), among others. The processor 801 may also include onboard memory for caching purposes. The processor 801 may include a single processing unit or multiple processing units for performing different actions of the method flows according to embodiments of the present disclosure.

In the RAM 803, various programs and data necessary for the operation of the electronic apparatus 800 are stored. The processor 801, the ROM 802, and the RAM 803 are connected to each other by a bus 804. The processor 801 performs various operations of the method flow according to the embodiments of the present disclosure by executing programs in the ROM 802 and/or the RAM 803. Note that the programs may also be stored in one or more memories other than the ROM 802 and the RAM 803. The processor 801 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.

Electronic device 800 may also include input/output (I/O) interface 805, input/output (I/O) interface 805 also connected to bus 804, according to an embodiment of the present disclosure. Electronic device 800 may also include one or more of the following components connected to I/O interface 805: an input portion 806 including a keyboard, a mouse, and the like; an output section 807 including a signal such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 808 including a hard disk and the like; and a communication section 809 including a network interface card such as a LAN card, a modem, or the like. The communication section 809 performs communication processing via a network such as the internet. A drive 810 is also connected to the I/O interface 805 as necessary. A removable medium 811 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 810 as necessary, so that a computer program read out therefrom is mounted on the storage section 808 as necessary.

The present disclosure also provides a computer-readable storage medium, which may be embodied in the device/apparatus/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 a method according to an embodiment of the disclosure.

According to embodiments of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, which may include, for example but is 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 the ROM 802 and/or RAM 803 described above and/or one or more memories other than the ROM 802 and RAM 803.

Embodiments of the present disclosure also include a computer program product comprising a computer program containing program code for performing the method illustrated by the flow chart. When the computer program product runs in a computer system, the program code is used for causing the computer system to realize the item recommendation method provided by the embodiment of the disclosure.

The computer program performs the above-described functions defined in the system/apparatus of the embodiments of the present disclosure when executed by the processor 801. The systems, apparatuses, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the present disclosure.

In one embodiment, the computer program may be hosted on a tangible storage medium such as an optical storage device, a magnetic storage device, and the like. In another embodiment, the computer program may also be transmitted in the form of a signal on a network medium, distributed, downloaded and installed via communication section 809, and/or installed from removable media 811. The computer program containing program code may be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.

In such an embodiment, the computer program can be downloaded and installed from a network through the communication section 809 and/or installed from the removable medium 811. The computer program, when executed by the processor 801, 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.

In accordance with embodiments of the present disclosure, program code for executing computer programs provided by embodiments of the present disclosure may be written in any combination of one or more programming languages, and in particular, these computer programs may be implemented using high level procedural and/or object oriented programming languages, and/or assembly/machine languages. The programming language includes, but is not limited to, programming languages such as Java, C + +, python, the "C" language, or the like. The program code may execute entirely on the user's computing device, partly on the user's device, partly on a remote computing device, or entirely on the remote computing device or server. In situations involving remote computing devices, the remote computing devices may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to external computing devices (e.g., through the internet using an internet service provider).

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 that 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 advantageously in 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 disclosure, and these alternatives and modifications are intended to fall within the scope of the disclosure.

Claims (11)

1. A method of determining a target data entity, comprising:

according to a target task, determining a target business component related to the target task from a plurality of business components;

determining a data entity corresponding to the target service component in the multiple data entities as a first data entity to obtain a first set; and

and determining a target data entity matched with the target task according to the first set.

2. The method of claim 1, wherein said determining, from the first set, a target data entity that matches the target task comprises:

for each first data entity in the first set, determining a data entity which satisfies a predetermined relationship with the first data entity in the plurality of data entities as a second data entity, and obtaining a second set corresponding to the first set; and

and determining a target data entity matched with the target task according to the first set and the second set.

3. The method of claim 2, wherein the predetermined relationship comprises:

the second data entity is an ancestor entity of the first data entity; or

The second data entity is a descendant entity of the first data entity.

4. The method of claim 2, wherein the names of the target tasks include task nouns, the names of the plurality of data entities each including an entity noun; the method further comprises the following steps:

determining the data entities in the current preset set, wherein the entity nouns are matched with the task nouns, and determining the data entities as third data entities to obtain a third set;

wherein the determining, according to the first set and the second set, a target data entity matching the target task comprises:

determining the target set of data entities from the first set, the second set, and the third set.

5. The method of claim 4, wherein the determining the target set of data entities from the first set, the second set, and the third set comprises:

showing the first set, the second set, and the third set; and

in response to receiving a selection instruction, determining the data entity indicated by the selection instruction as the target data entity.

6. The method of claim 1, wherein the name of the target task comprises a task noun, the names of the plurality of data entities each comprising an entity noun; the method further comprises the following steps:

determining the data entities in the current preset set, wherein the entity nouns are matched with the task nouns, and determining the data entities as third data entities to obtain a third set;

wherein the determining, according to the first set, a target data entity that matches the target task comprises:

and determining a target data entity matched with the target task according to the first set and the third set.

7. The method of claim 4 or 6, further comprising:

adding the target data entity to the current predetermined set to update the current predetermined set.

8. An apparatus for determining a target data entity, comprising:

the first determining module is used for determining a target business component related to a target task from a plurality of business components according to the target task;

a second determining module, configured to determine, as a first data entity, a data entity corresponding to the target service component from among the multiple data entities, to obtain a first set; and

and the third determining module is used for determining the target data entity matched with the target task according to the first set.

9. An electronic device, comprising:

one or more processors;

a storage device to store 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 perform the method recited in any of claims 1-7.

10. A computer readable storage medium having stored thereon executable instructions which, when executed by a processor, cause the processor to perform the method according to any one of claims 1 to 7.

11. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 7.

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