CN114218949A - Method and device for extracting service object - Google Patents

Abstract

The application provides a method and a device for extracting a service object, which are used for carrying out word segmentation on the obtained description information of a target service scene to obtain a plurality of nouns and verbs; analyzing the nouns and the verbs, and screening out a plurality of service source objects, a plurality of object attributes and a plurality of object behaviors from the nouns and the verbs; for each service source object, determining a target object attribute and a target object behavior belonging to the service source object from the plurality of object attributes and the plurality of object behaviors, and generating a target service source object corresponding to the service source object according to the service source object, the target object attribute and the target object behavior; and for each target service source object, performing abstract processing on the target service source object to obtain a service object corresponding to the target service source object. Based on the method and the device, the accuracy of extracting the business object can be improved, and the labor cost and the data cost can be reduced.

Description

Method and device for extracting service object

Technical Field

The present invention relates to the field of computer computing, and in particular, to a method and an apparatus for extracting a business object.

Background

Object-oriented means that the problem-forming transaction is broken down into individual business objects, and the purpose of creating a business object is not to complete one step, but to describe the behavior of something throughout the problem-solving step. How to identify and extract business objects, business object attributes, business object relationships, business object behaviors and the like is a key and a basis for constructing the electric power marketing information system, and therefore, how to extract the business objects from business scene description information related to the electric power marketing information system is a problem which needs to be solved urgently at present.

In the prior art, after the service source object extraction is carried out based on the current historical conditions of the electric power marketing information system, namely based on the service model design specification, the service object can be extracted from the service source object extracted in the front by the object extractor. However, the business model design specification book itself contains a large amount of information of the system operation level, which results in identifying a large amount of useless business objects and business attributes, and manually extracting the business objects requires a large amount of effort to discriminate, which results in a large amount of workload and a large amount of labor cost and data cost.

Disclosure of Invention

The invention provides a method and a device for extracting a business object, which are used for improving the accuracy of extracting the business object and reducing the labor cost and the data cost.

The first aspect of the present invention discloses a method for extracting a business object, wherein the method comprises:

performing word segmentation on the acquired target service scene description information to obtain a plurality of nouns and a plurality of verbs;

analyzing the nouns and the verbs, and screening out a plurality of service source objects, a plurality of object attributes and a plurality of object behaviors from the nouns and the verbs;

for each service source object, determining a target object attribute and a target object behavior belonging to the service source object from the plurality of object attributes and the plurality of object behaviors, and generating a target service source object corresponding to the service source object according to the service source object, the target object attribute and the target object behavior;

and for each target service source object, performing abstract processing on the target service source object to obtain a service object corresponding to the target service source object.

Optionally, the word segmentation processing is performed on the obtained target service scene description information to obtain a plurality of nouns and a plurality of verbs, and the word segmentation processing includes:

utilizing a noun-verb method to carry out word segmentation on the target service scene description information to obtain a plurality of noun information and a plurality of verb information;

combing the noun information to obtain a noun with noun terms aiming at each noun information; the noun carries a corresponding noun tag, and the noun tag is a candidate service object tag or a candidate object attribute tag; nouns of which the noun tags are candidate business object tags are candidate business objects, and nouns of which the noun tags are candidate object attribute tags are candidate object attributes;

combing the verb information aiming at each verb information to obtain a verb with a verb term; the verb carries a verb label corresponding to the verb, and the verb label is a candidate object behavior label.

Optionally, the nouns include candidate business objects and candidate object attributes, the verbs include candidate object behaviors, the analyzing the nouns and verbs screens out business source objects, object attributes, and object behaviors, including:

determining each candidate business object which meets preset attribute rules in the plurality of candidate business objects as an object attribute;

selecting a target candidate business object as a business source object from all target candidate business objects which meet preset redundancy rules in the candidate business objects;

selecting candidate business objects which do not meet a plurality of preset business object identification rules from the rest of candidate business objects, and determining the candidate business objects as the business source objects;

determining each candidate object attribute meeting a preset target business object identification rule in the plurality of candidate object attributes as a business source object;

selecting candidate object attributes which do not meet a plurality of preset object attribute identification rules from the rest candidate object attributes, and determining the candidate object attributes as object attributes;

and selecting the candidate object behaviors meeting any one of a plurality of preset object behavior identification rules from the plurality of candidate object behaviors, and determining the candidate object behaviors as the object behaviors.

Optionally, the method further includes:

configuring corresponding association tags for the object attributes meeting preset association attribute rules in the object attributes;

and configuring corresponding Boolean values for the object attributes meeting preset Boolean attribute rules in the object attributes.

Optionally, for each target service object, performing abstraction processing on the target service source object to obtain a service object corresponding to the target service source object, including:

for each target original business object, performing source pasting processing on the target business source object;

separating the target service source object subjected to source attaching processing to obtain an initial service object;

and purifying the initial service object, and simplifying the purified initial service object to obtain the service object of the target service source object.

The second aspect of the present invention discloses a device for extracting a business object, wherein the device comprises:

the word segmentation processing unit is used for carrying out word segmentation processing on the acquired target service scene description information to obtain a plurality of nouns and a plurality of verbs;

the analysis unit is used for analyzing the nouns and the verbs and screening out a plurality of service source objects, a plurality of object attributes and a plurality of object behaviors from the nouns and the verbs;

a generating unit, configured to determine, for each service source object, a target object attribute and a target object behavior that belong to the service source object from the multiple object attributes and the multiple object behaviors, and generate a target service source object corresponding to the service source object according to the service source object, the target object attribute, and the target object behavior;

and the abstract processing unit is used for abstracting the target service source object aiming at each target service source object to obtain a service object corresponding to the target service source object.

Optionally, the word segmentation processing unit includes:

the word segmentation processing subunit is used for segmenting words of the target service scene description information by using a noun-verb method to obtain a plurality of noun information and a plurality of verb information;

the first combing unit is used for combing the noun information to obtain a noun with noun terms aiming at each noun information; the noun carries a corresponding noun tag, and the noun tag is a candidate service object tag or a candidate object attribute tag; nouns of which the noun tags are candidate business object tags are candidate business objects, and nouns of which the noun tags are candidate object attribute tags are candidate object attributes;

the second combing unit is used for combing the verb information aiming at each verb information to obtain a verb with a verb term; the verb carries a verb label corresponding to the verb, and the verb label is a candidate object behavior label.

Optionally, the nouns include candidate business objects and candidate object attributes, the verbs include candidate object behaviors, and the analysis unit includes:

a first determining unit, configured to determine, as an object attribute, each candidate service object that satisfies a preset attribute rule among the plurality of candidate service objects;

a selecting unit, configured to select one target candidate service object as a service source object from target candidate service objects that satisfy a preset redundancy rule among the plurality of candidate service objects;

a second determining unit, configured to select, from the remaining multiple candidate service objects, a candidate service object that does not satisfy multiple preset service object identification rules, and determine the candidate service object as the service source object;

a third determining unit, configured to determine, as a service source object, each candidate object attribute that satisfies a preset target service object identification rule among the plurality of candidate object attributes;

a fourth determining unit, configured to select, from the remaining multiple candidate object attributes, a candidate object attribute that does not satisfy multiple preset object attribute identification rules, and determine the candidate object attribute as an object attribute;

a fifth determining unit, configured to select, from the plurality of candidate object behaviors, a candidate object behavior that satisfies any one of a plurality of preset object behavior recognition rules, and determine the candidate object behavior as an object behavior.

Optionally, the apparatus further comprises:

the first configuration unit is used for configuring corresponding association tags for the object attributes meeting preset association attribute rules in the object attributes;

and the second configuration unit is used for configuring corresponding Boolean values for the object attributes which meet preset Boolean attribute rules in the object attributes.

Optionally, the abstraction processing unit includes:

a source pasting processing unit, configured to perform source pasting processing on the target service source object for each target original service object;

the separation processing unit is used for separating the target service source object subjected to source pasting processing to obtain an initial service object;

and the purification and reduction processing unit is used for purifying the initial service object and reducing the purified initial service object to obtain the service object of the target service source object.

The invention provides a method and a device for extracting a service object, which are characterized in that a plurality of nouns and verbs are obtained by acquiring target service scene description information to be subjected to service object extraction and performing word segmentation processing on the target service scene description information; further, analyzing each noun and each verb, and screening out a plurality of service source objects, a plurality of object attributes and a plurality of object behaviors from the nouns and the verbs; and for each service source object, determining the target object property and the target object behavior belonging to the service source object from the plurality of object properties and the plurality of object behaviors, generating a target service source object of the service source object according to the service source object, the target object property and the target object behavior, and finally, abstracting the target service source object to obtain the service object of the target service source object. The technical scheme provided by the invention can improve the accuracy of the extracted business object and reduce the labor cost and the data cost.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.

Fig. 1 is a schematic flowchart of a method for extracting a business object according to an embodiment of the present invention;

fig. 2 is a schematic structural diagram of an apparatus for extracting a business object according to an embodiment of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The term "include" and variations thereof as used herein are open-ended, i.e., "including but not limited to". The term "based on" is "based, at least in part, on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions for other terms will be given in the following description.

It should be noted that the terms "first", "second", and the like in the present disclosure are only used for distinguishing different devices, modules, or units, and are not used for limiting the order or interdependence of the functions performed by the devices, modules, or units.

It is noted that references to "a", "an", and "the" modifications in the disclosure are exemplary rather than limiting, and that those skilled in the art will understand that "one or more" unless the context clearly dictates otherwise.

The business object is as follows: the semantic object is a business concept expressed in a high-level view, expresses a person, a place, a thing or a concept from a business domain, and is a reusable object consisting of names, attributes, behaviors and relationships. Compared with the traditional object, the business object is a special object, focuses on expressing the business concept, can be abstracted from nouns and dynamic nouns related to the business scene description, such as clients, metering points, internet of things points and transformers, and has no relation with the details of computing facilities and technical implementation.

Object attributes: refers to the property that the object itself has. Since an object can be regarded as an object, the color, shape, size, name, position, etc. of the object itself can be regarded as the attribute of the object. The properties of an object may be changeable or may not be changeable (read-only properties). For example, if I throw a book from a desk to the ground, the location attribute of the book is changed, but the material from which the book is made and the contents of the book are not changed (read-only attribute).

The object state: an object has a state, which is a description of one or more attributes of the object (e.g., a light "light is on-this is its state").

Object behavior: an object has behaviors, which are actions and reactions of the object to change its state (e.g., a light "turns off the light" is its behavior). Briefly, object behavior is an action that an object has based on object properties.

Object relationship: a relationship between one object and another object or between one object and itself is called a relationship between objects when there is a business relationship. Mainly comprises the relationships of succession, association, aggregation, combination, dependency and the like.

The service source object: the service source object refers to an unmodified and abstract initial service entity or service data existing in service reality, and is derived from a service (mainly derived from a service model) and used for expressing basic service information.

6 To: class 6 customers (6To), ToB (Enterprise), ToC (Individual), ToS (employee), ToM (management), ToP (ecological partner), ToG (government), respectively; ToB (enterprise user), enterprise (organization) with unified social credit code as unique identification, such as enterprise, institution, organization group, etc.; ToC (personal client) refers to a natural person with personal identification cards such as personal identification cards, military/official cards, Taiwan cards, house books and the like as unique identification. Such as residential homes, personal electric vehicle customers, and personal distributed photovoltaic power generation customers; ToS (internal staff): staff of each post in the company (staff develops a post activity view); ToM (enterprise manager): enterprise managers and management (management and management view) in general; ToP (ecological partner): refer to ecological partners (ecological collaboration class services); ToG (government department): refers to government regulatory agencies (regulatory, municipal services).

As can be seen from the above background art, in the conventional business object extraction method, since the business model design specification book contains a large amount of information of the system operation layer, a large amount of useless business objects and business attributes are identified, and the manual extraction of the business objects requires a large amount of effort to discriminate, which results in a large amount of workload and requires a large amount of labor cost and data cost.

In the prior art, the extraction of the service object can be realized by an unsupervised keyword extraction method, but the service source object extracted by the method is not complete, so that the abstraction of the subsequent service object cannot be smoothly performed.

In the prior art, a supervised keyword extraction method can also be used for extracting the business object, but the method needs a large amount of data to train the classifier, and the cost is high.

In the prior art, the extraction of the business object can be realized by an extraction method based on a wildcard mode, but the complexity of the method is high, so that the extraction efficiency of the business object is low.

Therefore, the invention provides a method and a device for extracting a service object, which are used for obtaining target service scene description information to be subjected to service object extraction and performing word segmentation processing on the target service scene description information to obtain a plurality of nouns and a plurality of verbs; further, analyzing each noun and each verb, and screening out a plurality of service source objects, a plurality of object attributes and a plurality of object behaviors from the nouns and the verbs; and for each service source object, determining the target object property and the target object behavior belonging to the service source object from the plurality of object properties and the plurality of object behaviors, generating a target service source object of the service source object according to the service source object, the target object property and the target object behavior, and finally, abstracting the target service source object to obtain the service object of the target service source object. According to the technical scheme provided by the invention, by analyzing each noun and each verb, a comprehensive service source object can be screened out from a plurality of nouns and verbs, so that the service object can be abstracted from the service source object subsequently and smoothly. In addition, the invention does not need a large amount of data to train the classifier and does not need manual screening, thereby not only improving the precision and efficiency of the extracted business object, but also reducing the labor cost and the data cost.

Referring to fig. 1, a schematic flow diagram of a method for extracting a business object according to an embodiment of the present invention is shown, where the method for extracting a business object specifically includes the following steps:

step S101: and performing word segmentation on the acquired description information of the target service scene to obtain a plurality of nouns and a plurality of verbs.

In the embodiment of the application, the service scene description information to be subjected to service object extraction is obtained, the target service scene description information containing the main verb-object-shape complement can be identified from the target service scene description information, word segmentation processing can be further performed on the identified target service scene description information, and a plurality of nouns and a plurality of verbs are extracted from the target service scene description information.

Optionally, the noun-verb method may be used to perform word segmentation on the target service scenario description information to obtain a plurality of noun information and a plurality of verb information. For each noun message, the noun message can be combed to obtain a noun with noun terms, and the noun carries a corresponding noun tag. For each verb information, the verb information can be combed to obtain a verb with a verb term, and the verb carries a corresponding verb label.

Wherein, the noun label is a candidate business object label or a candidate object attribute label; nouns with noun tags as candidate business object tags are candidate business objects, nouns with noun tags as candidate object attribute tags are candidate object attributes; verb tags are candidate behavior tags.

It should be noted that the term is mainly used to describe the business object and the business attribute. Verb terms are used primarily for the description of the subject behavior of a business subject.

It should be noted that the service scenario description information is compiled according To the service requirement of the 6To customer.

S102: and analyzing the nouns and verbs, and screening out a plurality of service source objects, a plurality of object attributes and a plurality of object behaviors from the nouns and verbs.

In the embodiment of the application, the nouns include a plurality of candidate business objects and a plurality of candidate object attributes, and the verbs include a plurality of candidate object behaviors and at least one candidate business object.

In the embodiment of the application, for a plurality of candidate business objects, an attribute rule, a redundancy rule and a plurality of business object identification rules are preset.

Optionally, if there is a candidate service object satisfying the preset attribute rule in each candidate service object, which indicates that the candidate service object should belong to the object attribute but not the service object, the candidate service object may be declared as the attribute again, that is, the candidate service object determines the object attribute.

Each target candidate business object meeting the preset redundancy rule can be determined from the plurality of candidate business objects, the target candidate business object with the highest description capacity is selected from the plurality of target candidate business objects to be determined as a business source object, and the rest target candidate business objects are deleted. For example, a meter is a device that can describe the metering of electrical energy in terms of electricity, but an electrical energy meter has more capability of describing the metering of electrical energy than a meter.

And finally, selecting candidate business objects which do not meet the preset multiple business object identification rules from the residual multiple candidate business objects, and determining the candidate business objects as business source objects.

In this embodiment of the present application, the preset multiple service object identification rules may be: irrelevant object identification rules, mixed object identification rules, operation object identification rules, role object identification rules, implementation component object identification rules, and derived object identification rules.

It should be noted that the irrelevant object identification rule may be: and deleting the candidate service object which is irrelevant to the service indicated in the target service scene description information. For example, in a theater ticket ordering system, the profession of the ticket holder is irrelevant, but the staff of the theater is relevant.

The inclusion object identification rule may be: the boundary definition of the deleted object is fuzzy, or the scope is too wide.

The operation object identification rule may be: if the operation described for the candidate business object can be applied to the object but cannot be used independently, it is deleted.

The role object recognition team then: if the name of the object of the candidate business object should reflect not its essential characteristics, but rather the role played in the association, it is deleted.

Implementing a component object identification rule: candidate business objects that are not related to the real world are deleted.

Derived object identification rules: candidate business objects derived from other business objects are deleted.

In the embodiment of the application, for a plurality of candidate object attributes, a corresponding target business object identification rule and a plurality of object attribute identification rules are preset.

Optionally, each candidate object attribute satisfying the preset target service object identification rule in the plurality of candidate object attributes is determined as a service source object, and each candidate object attribute not satisfying the preset plurality of object attribute identification rules is selected from the remaining plurality of candidate object attributes and determined as an object attribute.

It should be noted that the preset target business object identification rule may be: if the independent existence of the element in the candidate object attribute is important, that is, the element is not only a value, it can be determined that the candidate object attribute should be a business object, and the candidate object attribute can be declared as an object again, that is, the candidate object attribute determines a business source object.

The preset multiple attribute identification rules comprise: a qualifier object attribute identification rule, a name object attribute identification rule, an identifier object attribute identification rule, an internal value object attribute identification rule, a detail object attribute identification rule, and an inconsistent object attribute identification rule.

The qualifier object property identification rule may be: if the attribute value of a candidate attribute depends on a particular context, the candidate attribute may be deleted by re-describing the candidate attribute as a qualifier.

The name object attribute identification rule may be: if a candidate object property can be better modeled as a qualifier, the candidate object property can be deleted if it is determined that the candidate object property is not a true property.

The identifier object attribute identification rule may be: the only purpose for deletion to include those present is to determine the candidate object properties of the object, since the object identifier is implicit in the class model.

The internal value object attribute identification rule can be as follows: if the candidate object attribute describes an internal state of an object that is not visible outside the object, the candidate object attribute is deleted.

The detail object attribute identification rule may be: secondary candidate attributes that are unlikely to affect most operations are deleted.

The inconsistent object attribute identification rule may be: a candidate property that appears completely different or unrelated to all other candidate properties may mean that the class should be split into two different classes and the candidate property should be deleted.

In the embodiment of the application, an associated attribute rule and a boolean attribute rule are preset. After the plurality of object attributes are screened out, the object attributes meeting preset association attribute rules are determined from all the object attributes, and corresponding association labels are configured for the object attributes. And determining object attributes meeting preset Boolean attribute rules from the object attributes, and configuring Boolean values of the objects for the object attributes.

It should be noted that the preset association attribute rule may be: if the attribute value corresponding to a certain object attribute needs the existence of the link, the object attribute is the associated object attribute.

The preset boolean property rule may be: the boolean attributes of all object attributes are reconsidered. Often the boolean property can be broadened and re-declared as an enumeration.

In the embodiment of the application, for a plurality of candidate object behaviors, a plurality of object behavior identification rules are preset.

Alternatively, candidate object behaviors that do not uniformly satisfy a plurality of preset object behavior recognition rules may be selected from the plurality of candidate object behaviors and determined as the object behaviors.

It should be noted that the preset multiple object behavior identification rules include: active receive object behavior recognition rules, query and update object behavior recognition rules, focus class object behavior recognition rules, and real world class object behavior recognition rules.

The active receiving object behavior recognition rule may be: the candidate behavior may be determined to be an object behavior when the candidate behavior indicates that one business object performs an activity and another business object may function.

The query and update object behavior recognition rules may be: candidate behavior indicates that when other business objects simply query their information, and a business object is modified by this operation, the candidate behavior can be determined to be object behavior.

The focus class object behavior identification rule may be: candidate behavior indicates finding the classes and associations involved in the operation, which class is located at the center of this class model subnet? If these classes and associations form a star around a single central class, it is the target of the operation, i.e., the candidate object behavior can be determined to be the object behavior.

The analogy object behavior identification rule with the real world can be as follows: candidate behavior indicates that if these objects are not software, but real-world objects, then some real object is pushed, moved, activated, or manipulated to initiate this action, the candidate behavior may be determined to be object behavior.

In the embodiment of the application, if there is a candidate object behavior in the plurality of candidate object behaviors, which is easy to make a decision when the operation only contains one object, the candidate object behavior is queried (or told) to perform the operation, and the candidate object behavior can be determined as a business object.

S103: and for each service source object, determining the target object attribute and the target object behavior belonging to the service source object from the plurality of object attributes and the plurality of object behaviors, and generating a target service source object corresponding to the service source object according to the service source object, the target object attribute and the target object behavior.

In the embodiment of the present application, after a plurality of service source objects, a plurality of object attributes, and a plurality of object behaviors are screened from a plurality of nouns and verbs, for each service source object, an object attribute corresponding to the service source object is determined and output from the plurality of object attributes by analyzing each object attribute (for convenience of distinction, the object attribute corresponding to the service source object is referred to as a target object attribute); and determining the object behaviors of the business source object from the plurality of object behaviors by analyzing each object behavior (for the convenience of distinguishing, the object behaviors of the business source object are called target object behaviors). And finally, generating a target service source object of the service source object according to the target object attribute and the target object behavior of the service source object.

It should be noted that a business source object may have multiple target object attributes and a target object behavior. In reality, there are many behaviors related to the service source object, and all behaviors are included in the service source object, which may cause the service source object to be overstaffed and polluted, and violate the principle of single responsibility, so that the attribution of the behaviors needs to follow some principles. For example, methods that are highly reusable or are inherent to the object and closely related to the state of the business source object are placed in the business source object. Methods that are not inherently object-specific (but dependent on the particular scenario), not germane to the state of the business source object, are placed at the business source object manager or service level.

It should be noted that the service source object may be an electric energy meter, and the target object attribute corresponding to the electric energy meter may be a manufacturer, a production date, and the like.

S104: and for each target business object, performing abstract processing on the target business source object to obtain a business object corresponding to the target business source object.

In the embodiment of the application, for each service source object, after a target service source object of the object is generated according to the target object attribute and the object behavior of the object, the target service source object can be further subjected to source attachment processing; separating the target service source object subjected to source attaching processing to obtain an initial service object; and finally, carrying out simplification processing on the initial service object after the purification processing to obtain the service object of the target service source object.

In this embodiment of the present application, a specific process of performing source pasting processing on the target service source object may be as follows: firstly, standardizing the target service source object according to a preset standardized processing rule, then carrying out duplication removal and elimination on the target service source object subjected to the standardized processing, and carrying out integration processing on the target service source object subjected to the duplication removal and elimination.

The specific process of performing separation processing on the target service source object subjected to the source pasting processing may be as follows: and classifying, sorting, separating and removing the duplicate of the target service source object subjected to the source attaching processing in sequence to obtain an initial service object.

Optionally, analyzing the target service source object subjected to source pasting processing and attribute meaning thereof, and performing sorting (classification, sorting, separation, stripping) and duplicate removal on the attributes of the non-target service source object; when one target service source object comprises a plurality of object attributes, and each object attribute has separability and is complete, the division and the separation are carried out. If only the object name can be separated and no attribute exists, the object name is not separated, and if the object name can be separated and the attribute is less than 2, the object name and the attribute are not separated.

Specifically, the target service source object subjected to source pasting processing can be classified according to the service meaning and the object property of the target service source object; secondly, according to object classification and object meaning and attribute, integrating and merging the results obtained by classification to form a uniform service object; finally, the nature of the uniform business object is analyzed, and the real treatment is carried out on the different business objects expressed in different stages or processes, so that the business objects are merged into an initial business object.

The specific process of performing the purification process on the initial service object may be as follows: and assimilating, purifying, evading and purifying the initial service object in sequence.

Specifically, the assimilation process is as follows: the industry attribute and the professional attribute of the initial business object are analyzed, the specific industry or professional attribute is abstracted (a general classification attribute expression mode), the industry or professional constraint is reduced as much as possible, and the application field of the business object is expanded.

The purification process comprises the following steps: analyzing the service attributes (professions) related to the assimilated initial service object, separating or eliminating the condition that one object expresses a plurality of professional attributes, and enabling the service object to be pure as far as possible.

The advanced process can be as follows: the parent class object (equivalent to a new added object) of a similar object of a certain class is abstracted by high-level (advanced) processing, the parent class object is the public attribute of the child class object, the child class object is the unique attribute of the child class object, and the inheritance relationship between the child class object and the parent class is expressed by { parent class object } in the child class attribute. And examining the attribute composition of the business object, searching high-order object elements for a class of similar objects, properly splitting the objects containing a plurality of object attributes, and properly recombining the similar objects.

The process of obtaining the service object of the target service source object by performing the reduction processing on the initial service object after the purification processing may be as follows: and simplifying, referencing, regulating and perfecting the initial service object after the purification treatment in sequence to obtain the service object of the target service source object.

Specifically, the transaction attributes of the initial service objects after the purification processing are analyzed, after the simplification and simplification processing is performed on the redundant attributes, the attributes which are excessively related and the attributes which are excessively extended, the attribute composition is examined, high-order object elements are searched for one kind of similar objects, the objects containing a plurality of object attributes are properly split, and the similar objects are properly recombined; the object is relieved, and unnecessary redundancy is abandoned; revising the initial service object by referring to the SAP service object and the attributes thereof; refining and perfecting the public attribute of the parent class by the object with parent-child inheritance relationship, and using the child class object to quote the parent class object as the attribute; analyzing the service meaning of the enumeration attribute of the object, finding out enumeration values as much as possible, and carrying out normalized processing on the enumeration values to avoid overlapping and crossing among the enumeration values; analyzing initial service objects and the relation thereof according to the angle of system realization, supplementing and perfecting some attributes and elements necessary for system realization, such as roles, authorities, workflows, object association, system support and the like on the system design level; for the merged business object, the method of inspecting the object, the basic method and the dynamic or derived method are analyzed, the derivation is removed, and the method (behavior) of the basic essence is reserved; and examining the relationship of the front carding to the merged object, integrating the relationship of the business objects, examining whether the name of the merged object is accurately expressed according to the business meaning and method of the merged object, and properly adjusting the name of the merged object to obtain the business object of the target business source object of the initial business object.

The invention provides a method for extracting a service object, which comprises the steps of obtaining target service scene description information to be subjected to service object extraction, and performing word segmentation processing on the target service scene description information to obtain a plurality of nouns and a plurality of verbs; further, analyzing each noun and each verb, and screening out a plurality of service source objects, a plurality of object attributes and a plurality of object behaviors from the nouns and the verbs; and for each service source object, determining the target object property and the target object behavior belonging to the service source object from the plurality of object properties and the plurality of object behaviors, generating a target service source object of the service source object according to the service source object, the target object property and the target object behavior, and finally, abstracting the target service source object to obtain the service object of the target service source object. The technical scheme provided by the invention can improve the accuracy of the extracted business object and reduce the labor cost and the data cost.

Based on the method for extracting a service object disclosed in the embodiment of the present invention, the embodiment of the present invention also discloses a device for extracting a service object, and as shown in fig. 2, the extracting of the service object includes:

the word segmentation processing unit 21 is configured to perform word segmentation processing on the obtained target service scene description information to obtain a plurality of nouns and a plurality of verbs;

the analysis unit 22 is used for analyzing the nouns and the verbs and screening out a plurality of service source objects, a plurality of object attributes and a plurality of object behaviors from the nouns and the verbs;

a generating unit 23, configured to determine, for each service source object, a target object attribute and a target object behavior belonging to the service source object from the multiple object attributes and the multiple object behaviors, and generate a target service source object corresponding to the service source object according to the service source object, the target object attribute and the target object behavior;

and the abstraction processing unit 24 is configured to, for each target service source object, perform abstraction processing on the target service source object to obtain a service object corresponding to the target service source object.

The specific principle and the execution process of each unit in the device for extracting a service object disclosed in the embodiment of the present invention are the same as those of the method for extracting a service object shown in fig. 1 disclosed in the embodiment of the present invention, and reference may be made to corresponding parts in the method for extracting a service object disclosed in the embodiment of the present invention, which are not described herein again.

The invention provides a device for extracting a service object, which is characterized in that a plurality of nouns and verbs are obtained by acquiring target service scene description information to be subjected to service object extraction and performing word segmentation processing on the target service scene description information; further, analyzing each noun and each verb, and screening out a plurality of service source objects, a plurality of object attributes and a plurality of object behaviors from the nouns and the verbs; and for each service source object, determining the target object property and the target object behavior belonging to the service source object from the plurality of object properties and the plurality of object behaviors, generating a target service source object of the service source object according to the service source object, the target object property and the target object behavior, and finally, abstracting the target service source object to obtain the service object of the target service source object. The technical scheme provided by the invention can improve the accuracy of the extracted business object and reduce the labor cost and the data cost.

Optionally, the word segmentation processing unit includes:

the word segmentation processing subunit is used for segmenting words of the target service scene description information by utilizing a noun-verb method to obtain a plurality of noun information and a plurality of verb information;

the first combing unit is used for combing the noun information according to each noun information to obtain a noun with noun terms; the noun is a candidate business object label or a candidate object attribute label; nouns with noun tags as candidate business object tags are candidate business objects, nouns with noun tags as candidate object attribute tags are candidate object attributes;

the second combing unit is used for combing the verb information aiming at each verb information to obtain a verb with verb terms; the verb tag is a candidate object behavior tag.

Optionally, the nouns include candidate business objects and candidate object attributes, the verbs include candidate object behaviors, and the analyzing unit includes:

the first determining unit is used for determining each candidate business object which meets preset attribute rules in the plurality of candidate business objects as an object attribute;

the selection unit is used for selecting one target candidate business object as a business source object from all target candidate business objects which meet preset redundancy rules in the candidate business objects;

a second determining unit, configured to select, from the remaining multiple candidate service objects, a candidate service object that does not satisfy multiple preset service object identification rules, and determine the candidate service object as a service source object;

a third determining unit, configured to determine, as a service source object, each candidate object attribute that satisfies a preset target service object identification rule among the plurality of candidate object attributes;

a fourth determining unit, configured to select, from the remaining multiple candidate object attributes, a candidate object attribute that does not satisfy multiple preset object attribute identification rules, and determine the candidate object attribute as an object attribute;

and a fifth determining unit, configured to select, from the plurality of candidate object behaviors, a candidate object behavior that satisfies any one of a plurality of preset object behavior recognition rules, and determine the candidate object behavior as the object behavior.

Further, the device for extracting a business object provided by the present invention further includes:

the first configuration unit is used for configuring corresponding association tags for object attributes meeting preset association attribute rules in the object attributes;

and the second configuration unit is used for configuring corresponding Boolean values for the object attributes which meet preset Boolean attribute rules in the object attributes.

Optionally, the abstraction processing unit includes:

the source pasting processing unit is used for carrying out source pasting processing on the target service source object aiming at each target original service object;

the separation processing unit is used for separating the target service source object subjected to the source pasting processing to obtain an initial service object;

and the purification and reduction processing unit is used for purifying the initial service object and reducing the purified initial service object to obtain the service object of the target service source object.

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, the system or system embodiments are substantially similar to the method embodiments and therefore are described in a relatively simple manner, and reference may be made to some of the descriptions of the method embodiments for related points. The above-described system and system embodiments are merely illustrative, wherein units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.

Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

The foregoing is only a preferred embodiment of the present invention, and it should be noted that it is obvious to those skilled in the art that various modifications and improvements can be made without departing from the principle of the present invention, and these modifications and improvements should also be considered as the protection scope of the present invention.

Claims (10)

1. A method for extracting a business object, the method comprising:

performing word segmentation on the acquired target service scene description information to obtain a plurality of nouns and a plurality of verbs;

analyzing the nouns and the verbs, and screening out a plurality of service source objects, a plurality of object attributes and a plurality of object behaviors from the nouns and the verbs;

for each service source object, determining a target object attribute and a target object behavior belonging to the service source object from the plurality of object attributes and the plurality of object behaviors, and generating a target service source object corresponding to the service source object according to the service source object, the target object attribute and the target object behavior;

and for each target service source object, performing abstract processing on the target service source object to obtain a service object corresponding to the target service source object.

2. The method according to claim 1, wherein the performing word segmentation processing on the obtained target service scenario description information to obtain a plurality of nouns and a plurality of verbs comprises:

utilizing a noun-verb method to carry out word segmentation on the target service scene description information to obtain a plurality of noun information and a plurality of verb information;

combing the noun information to obtain a noun with noun terms aiming at each noun information; the noun carries a corresponding noun tag, and the noun tag is a candidate service object tag or a candidate object attribute tag; nouns of which the noun tags are candidate business object tags are candidate business objects, and nouns of which the noun tags are candidate object attribute tags are candidate object attributes;

combing the verb information aiming at each verb information to obtain a verb with a verb term; the verb carries a verb label corresponding to the verb, and the verb label is a candidate object behavior label.

3. The method of claim 2, wherein the nouns comprise candidate business objects and candidate object attributes, wherein the verbs comprise at least candidate object behaviors, wherein analyzing the nouns and verbs screens out business source objects, object attributes, and object behaviors, including:

determining each candidate business object which meets preset attribute rules in the plurality of candidate business objects as an object attribute;

selecting a target candidate business object as a business source object from all target candidate business objects which meet preset redundancy rules in the candidate business objects;

selecting candidate business objects which do not meet a plurality of preset business object identification rules from the rest of candidate business objects, and determining the candidate business objects as the business source objects;

determining each candidate object attribute meeting a preset target business object identification rule in the plurality of candidate object attributes as a business source object;

selecting candidate object attributes which do not meet a plurality of preset object attribute identification rules from the rest candidate object attributes, and determining the candidate object attributes as object attributes;

and selecting the candidate object behaviors meeting any one of a plurality of preset object behavior identification rules from the plurality of candidate object behaviors, and determining the candidate object behaviors as the object behaviors.

4. The method of claim 3, further comprising:

configuring corresponding association tags for the object attributes meeting preset association attribute rules in the object attributes;

and configuring corresponding Boolean values for the object attributes meeting preset Boolean attribute rules in the object attributes.

5. The method according to claim 1, wherein, for each target service object, abstracting the target service source object to obtain a service object corresponding to the target service source object, includes:

for each target original business object, performing source pasting processing on the target business source object;

separating the target service source object subjected to source attaching processing to obtain an initial service object;

and purifying the initial service object, and simplifying the purified initial service object to obtain the service object of the target service source object.

6. An apparatus for extracting a business object, the apparatus comprising:

the word segmentation processing unit is used for carrying out word segmentation processing on the acquired target service scene description information to obtain a plurality of nouns and a plurality of verbs;

the analysis unit is used for analyzing the nouns and the verbs and screening out a plurality of service source objects, a plurality of object attributes and a plurality of object behaviors from the nouns and the verbs;

a generating unit, configured to determine, for each service source object, a target object attribute and a target object behavior that belong to the service source object from the multiple object attributes and the multiple object behaviors, and generate a target service source object corresponding to the service source object according to the service source object, the target object attribute, and the target object behavior;

and the abstract processing unit is used for abstracting the target service source object aiming at each target service source object to obtain a service object corresponding to the target service source object.

7. The apparatus of claim 6, wherein the word segmentation processing unit comprises:

the word segmentation processing subunit is used for segmenting words of the target service scene description information by using a noun-verb method to obtain a plurality of noun information and a plurality of verb information;

the first combing unit is used for combing the noun information to obtain a noun with noun terms aiming at each noun information; the noun carries a corresponding noun tag, and the noun tag is a candidate service object tag or a candidate object attribute tag; nouns of which the noun tags are candidate business object tags are candidate business objects, and nouns of which the noun tags are candidate object attribute tags are candidate object attributes;

the second combing unit is used for combing the verb information aiming at each verb information to obtain a verb with a verb term; the verb carries a verb label corresponding to the verb, and the verb label is a candidate object behavior label.

8. The apparatus of claim 7, wherein the nouns comprise candidate business objects and candidate object attributes, wherein the verbs comprise at least candidate object behaviors, and wherein the analysis unit comprises:

a first determining unit, configured to determine, as an object attribute, each candidate service object that satisfies a preset attribute rule among the plurality of candidate service objects;

a selecting unit, configured to select one target candidate service object as a service source object from target candidate service objects that satisfy a preset redundancy rule among the plurality of candidate service objects;

a second determining unit, configured to select, from the remaining multiple candidate service objects, a candidate service object that does not satisfy multiple preset service object identification rules, and determine the candidate service object as the service source object;

a third determining unit, configured to determine, as a service source object, each candidate object attribute that satisfies a preset target service object identification rule among the plurality of candidate object attributes;

a fourth determining unit, configured to select, from the remaining multiple candidate object attributes, a candidate object attribute that does not satisfy multiple preset object attribute identification rules, and determine the candidate object attribute as an object attribute;

a fifth determining unit, configured to select, from the plurality of candidate object behaviors, a candidate object behavior that satisfies any one of a plurality of preset object behavior recognition rules, and determine the candidate object behavior as an object behavior.

9. The apparatus of claim 8, further comprising:

the first configuration unit is used for configuring corresponding association tags for the object attributes meeting preset association attribute rules in the object attributes;

and the second configuration unit is used for configuring corresponding Boolean values for the object attributes which meet preset Boolean attribute rules in the object attributes.

10. The apparatus of claim 6, wherein the abstraction processing unit comprises:

a source pasting processing unit, configured to perform source pasting processing on the target service source object for each target original service object;

the separation processing unit is used for separating the target service source object subjected to source pasting processing to obtain an initial service object;

and the purification and reduction processing unit is used for purifying the initial service object and reducing the purified initial service object to obtain the service object of the target service source object.

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