CN117874167A - Method, system, equipment and storage medium for searching object - Google Patents
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Abstract
The invention relates to the field of low-code modeling, in particular to a method, a system, equipment and a storage medium for searching objects, wherein the method comprises the following steps: in response to receiving a natural language, part-of-speech tagging is performed on the natural language to select words of a preset part-of-speech; searching corresponding entity indexes according to the words of the preset parts of speech to determine the entities corresponding to the natural language; analyzing the natural language according to the words with the preset parts of speech and the corresponding entities to generate search conditions; and performing object inquiry according to the search condition. The invention realizes coding-free and intelligent search support by integrating natural language identification technology and business entity model structure.
Description
Technical Field
The present invention relates to the field of low-code modeling, and more particularly, to a method, system, apparatus, and storage medium for searching for objects.
Background
In the field of low codes, modeling abstraction of business documents provides the capability of supporting rapid development of business applications, and development efficiency is greatly improved. However, the existing applications developed by the low-code platform only support formatted search conditions, and cannot meet the requirements of intelligent and natural language search.
Disclosure of Invention
In view of this, an object of an embodiment of the present invention is to provide a method, a system, an electronic device, and a computer readable storage medium for searching objects.
Based on the above object, an aspect of the embodiments of the present invention provides a method for searching an object, including the steps of: in response to receiving a natural language, part-of-speech tagging is performed on the natural language to select words of a preset part-of-speech; searching corresponding entity indexes according to the words of the preset parts of speech to determine the entities corresponding to the natural language; analyzing the natural language according to the words with the preset parts of speech and the corresponding entities to generate search conditions; and performing object inquiry according to the search condition.
In some embodiments, the step of searching the corresponding entity index according to the word of the preset part of speech to determine the entity corresponding to the natural language includes: and constructing an index structure of the entity index through the entity index main key, the entity data, the field type entity, the business entity model to which the entity data belongs and the field to which the field type belongs, and determining corresponding data in the index structure of the entity index through the words with preset parts of speech.
In some embodiments, the step of parsing the natural language according to the word of the preset part of speech and the corresponding entity to generate the search condition includes: and constructing an index structure of the service data index through the data index main key, the data main key, the affiliated service entity model and the entity index main key, and determining corresponding data in the index structure of the service data index through the entity index main key.
In some embodiments, the step of searching the corresponding entity index according to the word of the preset part of speech to determine the entity corresponding to the natural language includes: and searching the corresponding entity index in the entity index storage according to the attribute of the entity field.
In some embodiments, the step of searching the corresponding entity index according to the word of the preset part of speech to determine the entity corresponding to the natural language includes: and maintaining the entity index corresponding to the entity field through enumeration list maintenance, reference dictionary maintenance and data dictionary dynamic maintenance.
In some embodiments, the step of maintaining the entity index corresponding to the entity field through enumeration list maintenance, reference dictionary maintenance and data dictionary dynamic maintenance includes: and determining entity data in the entity index through the enumeration list or the referenced dictionary, or dynamically maintaining the entity data in the entity index according to the data of the current business application.
In some embodiments, the step of performing the object query according to the search condition includes: responding to the global search mode, and matching from the business entity index data corresponding to all the business entity models corresponding to the entity index structure; and matching from the business entity model specified by the entity index structure in response to the particular business application search pattern.
In another aspect of an embodiment of the present invention, there is provided a system for searching an object, including: the marking module is configured to mark parts of speech of natural language to select words with preset parts of speech in response to receiving the natural language; the searching module is configured to search corresponding entity indexes according to the words of the preset parts of speech to determine the entities corresponding to the natural language; the analysis module is configured to analyze the natural language according to the words with the preset parts of speech and the corresponding entities so as to generate search conditions; and the execution module is configured to perform object query according to the search condition.
In still another aspect of the embodiment of the present invention, there is also provided an electronic device, including: at least one processor; and a memory storing computer instructions executable on the processor, which when executed by the processor, perform the steps of the method as above.
In yet another aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium storing a computer program which, when executed by a processor, implements the method steps as described above.
The invention has the following beneficial technical effects: by integrating natural language identification technology and business entity model structure, intelligent search technology for intelligent and rapid configuration business application is formed.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are necessary for the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention and that other embodiments may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of an embodiment of a method for searching objects provided by the present invention;
FIG. 2 is a flow chart of an embodiment of a method of searching for objects provided by the present invention;
FIG. 3 is a schematic diagram of an embodiment of a system for searching objects provided by the present invention;
fig. 4 is a schematic hardware structure of an embodiment of an electronic device for searching an object according to the present invention;
fig. 5 is a schematic diagram of an embodiment of a computer storage medium for searching objects provided by the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the following embodiments of the present invention will be described in further detail with reference to the accompanying drawings.
It should be noted that, in the embodiments of the present invention, all the expressions "first" and "second" are used to distinguish two entities with the same name but different entities or different parameters, and it is noted that the "first" and "second" are only used for convenience of expression, and should not be construed as limiting the embodiments of the present invention, and the following embodiments are not described one by one.
In a first aspect of the embodiment of the present invention, an embodiment of a method for searching an object is provided. Fig. 1 is a schematic diagram of an embodiment of a method for searching an object provided by the present invention. As shown in fig. 1, the embodiment of the present invention includes the following steps:
s1, responding to received natural language, marking the part of speech of the natural language to select words with preset part of speech;
s2, searching corresponding entity indexes according to the words of the preset parts of speech to determine the entities corresponding to the natural language;
s3, analyzing the natural language according to the words with the preset parts of speech and the corresponding entities to generate search conditions; and
s4, carrying out object query according to the search conditions.
The embodiment of the invention provides the search condition matching capability based on natural language processing, and supports the conversion of natural language conditions into structured search conditions.
The embodiment of the invention is realized based on a business entity model, the business entity model is used for describing business logic, and the entity model abstracted by adopting field driving design; the business entity model comprises an entity data structure and a business logic layer; the business entity operation module is used for providing a basic framework for business logic operation and comprises the most basic content of a business logic layer and an expansion mechanism for packaging public business logic; the buffer module comprises a session level buffer layer, a transaction level buffer layer and an action level buffer layer, wherein the session level buffer layer corresponds to the original data, the transaction level buffer corresponds to the current transaction level data, the action and buffer corresponds to the current operation level data, the access frequency of the database is reduced on meeting the access requirement of the service function to the data in different states, and the overall efficiency is improved; the incremental mechanism module is used for defining that the data returned by the front-end caller, the data submitted by the front-end modification and the data submitted to the database during storage are all incremental data; the business logic layer comprises an entity logic layer and a service logic layer, wherein the entity logic layer is the business logic splitting layer with the finest granularity, and the service logic layer is used for arranging and processing the entity logic layer; the business entity designer is used for carrying out business development through a business entity modeling tool and modeling an entity data structure and business logic; a JIT generator for generating a modeled business entity model into business codes that run on the basis of a business entity running framework; the JIT generator generates a corresponding Api, entity, core and Persistence four packages from one business entity model according to the business entity model generation runtime code.
In response to receiving a natural language, part-of-speech tagging is performed on the natural language to select words of a preset part-of-speech. Part of speech tagging may be performed using part of speech tagging service components commonly used in the industry, for example: the black computer can recognize that the black is noun, the word is auxiliary word and the computer is noun through part-of-speech tagging.
Searching corresponding entity indexes according to the words with the preset parts of speech to determine the entities corresponding to the natural language. Based on the nouns marked by parts of speech, searching corresponding entity indexes in entity index storage, and identifying the entities in the natural language. For example, according to "black" and "computer", two entities of "material color" and "material type" in the "material dictionary" model can be identified.
In some embodiments, the step of searching the corresponding entity index according to the word of the preset part of speech to determine the entity corresponding to the natural language includes: and constructing an index structure of the entity index through the entity index main key, the entity data, the field type entity, the business entity model to which the entity data belongs and the field to which the field type belongs, and determining corresponding data in the index structure of the entity index through the words with preset parts of speech.
The entity index is used for indicating the index structure of the entity of the field in the service application, and supports the storage of the field type entity corresponding to the corresponding field data value in a specific service application. The main structure comprises: the method comprises a main key, entity data, a business entity model corresponding to the business application and a field type entity. For example, in a materials dictionary, its business entity model is a materials model, in which there are two fields: the material type is dictionary type, the material type dictionary stores material type data comprising data of a computer, a mouse, a computer desk and the like, and the material color comprises data of black, white, yellow, blue and the like. Taking a computer as a material type and a black color as an example, the following table is an index structure of an entity index:
in some embodiments, the step of searching the corresponding entity index according to the word of the preset part of speech to determine the entity corresponding to the natural language includes: and searching the corresponding entity index in the entity index storage according to the attribute of the entity field.
In some embodiments, the step of searching the corresponding entity index according to the word of the preset part of speech to determine the entity corresponding to the natural language includes: and maintaining the entity index corresponding to the entity field through enumeration list maintenance, reference dictionary maintenance and data dictionary dynamic maintenance.
In some embodiments, the step of maintaining the entity index corresponding to the entity field through enumeration list maintenance, reference dictionary maintenance and data dictionary dynamic maintenance includes: and determining entity data in the entity index through the enumeration list or the referenced dictionary, or dynamically maintaining the entity data in the entity index according to the data of the current business application.
The enumeration type table maintenance indicates that entity data in the entity index is derived from a preferential enumeration list, such as gender, and the entity data comprises three items of male, female and unknown; the reference dictionary maintains a representation that entity data in the entity index originates from a dictionary of references, such as the "department to department" field, and entity data originates from an "organization" table; the dynamic maintenance of the data dictionary indicates that the entity data in the entity index is dynamically maintained according to the data of the current business application, namely: and when the business data corresponding to the current business entity model changes (is newly added, modified and deleted), automatically maintaining the entity index.
And analyzing the natural language according to the words with the preset parts of speech and the corresponding entities to generate search conditions.
In some embodiments, the step of parsing the natural language according to the word of the preset part of speech and the corresponding entity to generate the search condition includes: and constructing an index structure of the service data index through the data index main key, the data main key, the affiliated service entity model and the entity index main key, and determining corresponding data in the index structure of the service data index through the entity index main key.
The service data index is used for representing an index structure of service data and supports service data retrieval aiming at query conditions in one service application. The main structure comprises: data index main key, data main key, affiliated business entity model, entity index main key, etc. For example, in a materials dictionary, there is a piece of materials data: black computer, the following table is the index structure of the business data index:
query semantic parsing, parsing natural language into machine-recognizable semantic representations. For example, based on the identified parts of speech and entities, the semantic parsing may parse "black computers" into "materials with black color and materials with computer types".
Based on the semantics identified by the steps and the business entity model, changing the condition package into ' material color= ' black ' and material type= ' computer ' ";
and carrying out object inquiry according to the search condition. In the embodiment of the invention, the material is taken as an object for illustration.
In some embodiments, the step of performing the object query according to the search condition includes: responding to the global search mode, and matching from the business entity index data corresponding to all the business entity models corresponding to the entity index structure; and matching from the business entity model specified by the entity index structure in response to the particular business application search pattern.
If the global search mode is adopted, the search service matches the business entity index data corresponding to all the business entity models from the entity index structure, and the matching is returned; if the search is in a specific business application, a user is required to transmit a specific business application-business entity model, and when the search service is matched from the entity index structure, the search is limited in the range of the designated business entity model.
Taking a material dictionary as an example, the steps of starting intelligent search are introduced in support of searching according to material types and material colors:
1. opening a business entity model designer, selecting a 'material type' field, and in a right attribute frame: setting the "business entity search setting" attribute to "yes"; clicking a button behind the entity index maintenance strategy, selecting a reference dictionary in a pop-up maintenance strategy list, clicking a dictionary model selecting button, and selecting a material type model;
2. repeating 1, and setting a search setting of a field of 'material color';
3. storing and releasing business entities;
4. the "update index function" in the click service entity designer performs the update.
5. And finishing the searching setting of the material dictionary.
It should be noted that, in the embodiments of the method for searching objects, the steps may be intersected, replaced, added and subtracted, so that the method for searching objects by reasonable permutation and combination should also belong to the protection scope of the present invention, and the protection scope of the present invention should not be limited to the embodiments.
With the above object in mind, in a second aspect of embodiments of the present invention, a system 200 for searching for objects is presented. As shown in fig. 3, the system 200 includes the following modules: the marking module is configured to mark parts of speech of natural language to select words with preset parts of speech in response to receiving the natural language; the searching module is configured to search corresponding entity indexes according to the words of the preset parts of speech to determine the entities corresponding to the natural language; the analysis module is configured to analyze the natural language according to the words with the preset parts of speech and the corresponding entities so as to generate search conditions; and the execution module is configured to perform object query according to the search condition.
In some embodiments, the lookup module is further configured to: and constructing an index structure of the entity index through the entity index main key, the entity data, the field type entity, the business entity model to which the entity data belongs and the field to which the field type belongs, and determining corresponding data in the index structure of the entity index through the words with preset parts of speech.
In some embodiments, the parsing module is further configured to: and constructing an index structure of the service data index through the data index main key, the data main key, the affiliated service entity model and the entity index main key, and determining corresponding data in the index structure of the service data index through the entity index main key.
In some embodiments, the lookup module is further configured to: and searching the corresponding entity index in the entity index storage according to the attribute of the entity field.
In some embodiments, the lookup module is further configured to: and maintaining the entity index corresponding to the entity field through enumeration list maintenance, reference dictionary maintenance and data dictionary dynamic maintenance.
In some embodiments, the lookup module is further configured to: and determining entity data in the entity index through the enumeration list or the referenced dictionary, or dynamically maintaining the entity data in the entity index according to the data of the current business application.
In some embodiments, the execution module is further configured to: responding to the global search mode, and matching from the business entity index data corresponding to all the business entity models corresponding to the entity index structure; and matching from the business entity model specified by the entity index structure in response to the particular business application search pattern.
In view of the above object, a third aspect of an embodiment of the present invention provides an electronic device, including: at least one processor; and a memory storing computer instructions executable on the processor, the instructions being executable by the processor to perform the steps of: s1, responding to received natural language, marking the part of speech of the natural language to select words with preset part of speech; s2, searching corresponding entity indexes according to the words of the preset parts of speech to determine the entities corresponding to the natural language; s3, analyzing the natural language according to the words with the preset parts of speech and the corresponding entities to generate search conditions; and S4, carrying out object inquiry according to the search condition.
In some embodiments, the step of searching the corresponding entity index according to the word of the preset part of speech to determine the entity corresponding to the natural language includes: and constructing an index structure of the entity index through the entity index main key, the entity data, the field type entity, the business entity model to which the entity data belongs and the field to which the field type belongs, and determining corresponding data in the index structure of the entity index through the words with preset parts of speech.
In some embodiments, the step of parsing the natural language according to the word of the preset part of speech and the corresponding entity to generate the search condition includes: and constructing an index structure of the service data index through the data index main key, the data main key, the affiliated service entity model and the entity index main key, and determining corresponding data in the index structure of the service data index through the entity index main key.
In some embodiments, the step of searching the corresponding entity index according to the word of the preset part of speech to determine the entity corresponding to the natural language includes: and searching the corresponding entity index in the entity index storage according to the attribute of the entity field.
In some embodiments, the step of searching the corresponding entity index according to the word of the preset part of speech to determine the entity corresponding to the natural language includes: and maintaining the entity index corresponding to the entity field through enumeration list maintenance, reference dictionary maintenance and data dictionary dynamic maintenance.
In some embodiments, the step of maintaining the entity index corresponding to the entity field through enumeration list maintenance, reference dictionary maintenance and data dictionary dynamic maintenance includes: and determining entity data in the entity index through the enumeration list or the referenced dictionary, or dynamically maintaining the entity data in the entity index according to the data of the current business application.
In some embodiments, the step of performing the object query according to the search condition includes: responding to the global search mode, and matching from the business entity index data corresponding to all the business entity models corresponding to the entity index structure; and matching from the business entity model specified by the entity index structure in response to the particular business application search pattern.
Fig. 4 is a schematic hardware structure of an embodiment of the electronic device for searching objects according to the present invention.
Taking the example of the apparatus shown in fig. 4, a processor 301 and a memory 302 are included in the apparatus.
The processor 301 and the memory 302 may be connected by a bus or otherwise, for example in fig. 4.
The memory 302 is used as a non-volatile computer readable storage medium for storing non-volatile software programs, non-volatile computer executable programs, and modules, such as program instructions/modules corresponding to the method of searching for objects in the embodiments of the present application. The processor 301 executes various functional applications of the server and data processing, i.e., a method of realizing a search object, by running nonvolatile software programs, instructions, and modules stored in the memory 302.
Memory 302 may include a storage program area that may store an operating system, at least one application program required for functionality, and a storage data area; the storage data area may store data created according to the use of the method of searching for the object, and the like. In addition, memory 302 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, memory 302 may optionally include memory located remotely from processor 301, which may be connected to the local module via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
Computer instructions 303 corresponding to one or more methods of searching for objects are stored in memory 302, which when executed by processor 301, perform the methods of searching for objects in any of the method embodiments described above.
Any one embodiment of the electronic device that performs the method for searching for an object described above may achieve the same or similar effects as any one of the method embodiments described above that corresponds to the embodiment.
The present invention also provides a computer readable storage medium storing a computer program which when executed by a processor performs a method of searching for objects.
Fig. 5 is a schematic diagram of an embodiment of the computer storage medium of the search object according to the present invention. Taking a computer storage medium as shown in fig. 5 as an example, the computer readable storage medium 401 stores a computer program 402 that when executed by a processor performs the above method.
Finally, it should be noted that, as will be understood by those skilled in the art, implementing all or part of the above-described embodiments of the method may be implemented by a computer program to instruct related hardware, and the program of the method for searching the object may be stored in a computer readable storage medium, where the program may include the steps of the embodiments of the methods described above when executed. The storage medium of the program may be a magnetic disk, an optical disk, a read-only memory (ROM), a random-access memory (RAM), or the like. The computer program embodiments described above may achieve the same or similar effects as any of the method embodiments described above.
The foregoing is an exemplary embodiment of the present disclosure, but it should be noted that various changes and modifications could be made herein without departing from the scope of the disclosure as defined by the appended claims. The functions, steps and/or actions of the method claims in accordance with the disclosed embodiments described herein need not be performed in any particular order. Furthermore, although elements of the disclosed embodiments may be described or claimed in the singular, the plural is contemplated unless limitation to the singular is explicitly stated.
It should be understood that as used herein, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly supports the exception. It should also be understood that "and/or" as used herein is meant to include any and all possible combinations of one or more of the associated listed items.
The foregoing embodiment of the present invention has been disclosed with reference to the number of embodiments for the purpose of description only, and does not represent the advantages or disadvantages of the embodiments.
It will be understood by those skilled in the art that all or part of the steps for implementing the above embodiments may be implemented by hardware, or may be implemented by a program for instructing relevant hardware, and the program may be stored in a computer readable storage medium, where the storage medium may be a read-only memory, a magnetic disk or an optical disk, etc.
Those of ordinary skill in the art will appreciate that: the above discussion of any embodiment is merely exemplary and is not intended to imply that the scope of the disclosure of embodiments of the invention, including the claims, is limited to such examples; combinations of features of the above embodiments or in different embodiments are also possible within the idea of an embodiment of the invention, and many other variations of the different aspects of the embodiments of the invention as described above exist, which are not provided in detail for the sake of brevity. Therefore, any omission, modification, equivalent replacement, improvement, etc. of the embodiments should be included in the protection scope of the embodiments of the present invention.
Claims (10)
1. A method of searching for objects, comprising the steps of:
in response to receiving a natural language, part-of-speech tagging is performed on the natural language to select words of a preset part-of-speech;
searching corresponding entity indexes according to the words of the preset parts of speech to determine the entities corresponding to the natural language;
analyzing the natural language according to the words with the preset parts of speech and the corresponding entities to generate search conditions; and
and carrying out object inquiry according to the search condition.
2. The method of searching for objects according to claim 1, wherein the step of searching for the corresponding entity index according to the words of the preset part of speech to determine the entity corresponding to the natural language includes:
and constructing an index structure of the entity index through the entity index main key, the entity data, the field type entity, the business entity model to which the entity data belongs and the field to which the field type belongs, and determining corresponding data in the index structure of the entity index through the words with preset parts of speech.
3. The method of searching for objects according to claim 2, wherein the step of parsing the natural language according to the words of the preset part of speech and the corresponding entities to generate search conditions comprises:
and constructing an index structure of the service data index through the data index main key, the data main key, the affiliated service entity model and the entity index main key, and determining corresponding data in the index structure of the service data index through the entity index main key.
4. The method of searching for objects according to claim 1, wherein the step of searching for the corresponding entity index according to the words of the preset part of speech to determine the entity corresponding to the natural language includes:
and searching the corresponding entity index in the entity index storage according to the attribute of the entity field.
5. The method of searching for objects according to claim 4, wherein the step of searching for the corresponding entity index according to the words of the preset part of speech to determine the entity corresponding to the natural language comprises:
and maintaining the entity index corresponding to the entity field through enumeration list maintenance, reference dictionary maintenance and data dictionary dynamic maintenance.
6. The method for searching for an object according to claim 5, wherein the maintaining the entity index corresponding to the entity field through enumeration list maintenance, reference dictionary maintenance, data dictionary dynamic maintenance comprises:
and determining entity data in the entity index through the enumeration list or the referenced dictionary, or dynamically maintaining the entity data in the entity index according to the data of the current business application.
7. The method of searching for objects according to claim 1, wherein the step of performing an object query according to the search condition comprises:
responding to the global search mode, and matching from the business entity index data corresponding to all the business entity models corresponding to the entity index structure; and
in response to a particular business application search pattern, a match is made from a business entity model specified by the entity index structure.
8. A system for searching for objects, comprising:
the marking module is configured to mark parts of speech of natural language to select words with preset parts of speech in response to receiving the natural language;
the searching module is configured to search corresponding entity indexes according to the words of the preset parts of speech to determine the entities corresponding to the natural language;
the analysis module is configured to analyze the natural language according to the words with the preset parts of speech and the corresponding entities so as to generate search conditions; and
and the execution module is configured to perform object query according to the search condition.
9. An electronic device, comprising:
at least one processor; and
a memory storing computer instructions executable on the processor, which when executed by the processor, perform the steps of the method of any one of claims 1-7.
10. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method of any one of claims 1-7.
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