CN117909872A - Method and device for determining classification result, storage medium and electronic device - Google Patents

Abstract

The application discloses a method and a device for determining a classification result, a storage medium and an electronic device, and relates to the field of big data, wherein the method for determining the classification result comprises the following steps: generating a tag list for the target object, wherein the tag list comprises: the system comprises a plurality of tag information, a plurality of target objects and a plurality of control units, wherein each tag information in the plurality of tag information is used for indicating regular data of execution target events of the target objects in a preset period; determining a rule tree of the target object according to a plurality of tag information included in the tag list; and determining the classification result of the target object according to the rule tree. By adopting the technical scheme, the problem that the classification mode of the target object in the prior art is poor in classification expansibility and accuracy is solved.

Description

Method and device for determining classification result, storage medium and electronic device

Technical Field

The present application relates to the field of big data, and in particular, to a method and apparatus for determining a classification result, a storage medium, and an electronic apparatus.

Background

At present, the business comparison on the aspect of user water consumption depends on crowd classification, and the existing crowd classification mode is often based on the statistics of water consumption time distribution of records of users using related water consumption equipment, and then the crowd is classified through fixed logic rules.

Aiming at the related technology, the problem that the classification mode of the target object in the prior art is poor in classification expansibility and accuracy is solved, and no effective solution is proposed at present.

Accordingly, there is a need for improvements in the related art to overcome the drawbacks of the related art.

Disclosure of Invention

The embodiment of the application provides a method and a device for determining a classification result, a storage medium and an electronic device, which are used for at least solving the problems of poor classification expansibility and accuracy of a classification mode of a target object in the prior art in the related art.

According to an embodiment of the present application, there is provided a method for determining a classification result, including: generating a tag list for the target object, wherein the tag list comprises the following components: the system comprises a plurality of tag information, a plurality of target objects and a plurality of control units, wherein each tag information in the plurality of tag information is used for indicating regular data of execution target events of the target objects in a preset period; determining a rule tree of the target object according to the plurality of tag information included in the tag list; and determining a classification result of the target object according to the rule tree.

In an exemplary embodiment, before generating the tag list for the target object, the method further comprises: determining tag types of the plurality of tag information, wherein the tag types are used for indicating unit time and the target event included in the preset period; acquiring rule sub-data of the target object for executing the target event in the unit time according to the type of the search tag; and determining rule data of the execution target event of the target object in a preset period according to the rule sub-data corresponding to all the unit time.

In an exemplary embodiment, determining the rule tree of the target object according to the plurality of tag information included in the tag list includes: obtaining a rule pool corresponding to the rule tree to be generated, wherein the rule pool comprises: for any tag information in the tag information, determining a target grammar rule matched with the any tag information from the rule pool by using a plurality of grammar rules; constructing a node of any label information in the rule tree according to the target grammar rule, wherein the value of the node is any label information; the rule tree is determined in a case where the plurality of tag information has all constructed nodes in the rule tree.

In an exemplary embodiment, obtaining a rule pool corresponding to the rule tree to be generated includes: acquiring the classification requirement of the target object, wherein the classification requirement is used for indicating the quantity to be classified, the category to be classified and the rule pattern of grammar rules of the target object; and configuring a plurality of grammar rules included in the rule pool according to the classification requirement.

In an exemplary embodiment, determining the classification result of the target object according to the rule tree includes: determining a parent node in the rule tree as a first classification result of the target object, and determining a child node of the parent node as a second classification result of the target object, wherein the classification result comprises: the first classification result and the second classification result.

In an exemplary embodiment, after determining the classification result of the target object according to the rule tree, the method further includes: receiving an acquisition request initiated by terminal equipment; responding to the acquisition request, and determining whether the terminal equipment has the acquisition authority for acquiring the classification result; and sending the classification result of the target object to the terminal equipment under the condition that the terminal equipment has the acquisition permission.

In one exemplary embodiment, generating a tag list for a target object includes: determining whether the target object opens a generation right or not, wherein the generation right is used for indicating whether the target object allows regular data of an execution target event of the target object in a preset period to be acquired or not; and generating a tag list for the target object under the condition that the target object has opened the generation permission.

According to another aspect of the embodiment of the present application, there is further provided a device for determining a classification result, a generating module, configured to generate a tag list for a target object, where the tag list includes: the system comprises a plurality of tag information, a plurality of target objects and a plurality of control units, wherein each tag information in the plurality of tag information is used for indicating regular data of execution target events of the target objects in a preset period; a first determining module, configured to determine a rule tree of the target object according to the plurality of tag information included in the tag list; and the second determining module is used for determining the classification result of the target object according to the rule tree.

In an exemplary embodiment, the generating module is further configured to: determining tag types of the plurality of tag information, wherein the tag types are used for indicating unit time and the target event included in the preset period; acquiring rule sub-data of the target object for executing the target event in the unit time according to the type of the search tag; and determining rule data of the execution target event of the target object in a preset period according to the rule sub-data corresponding to all the unit time.

In an exemplary embodiment, the first determining module further includes: an obtaining unit, configured to obtain a rule pool corresponding to the rule tree to be generated, where the rule pool includes: a plurality of grammar rules; a first determining unit, configured to determine, for any tag information in the plurality of tag information, a target grammar rule matching with the any tag information from the rule pool; the construction unit is used for constructing a node of any label information in the rule tree according to the target grammar rule, wherein the value of the node is any label information; a second determining unit configured to determine the rule tree in a case where the plurality of tag information has all constructed nodes in the rule tree.

In an exemplary embodiment, the above-mentioned acquisition unit is further configured to: acquiring the classification requirement of the target object, wherein the classification requirement is used for indicating the quantity to be classified, the category to be classified and the rule pattern of grammar rules of the target object; and configuring a plurality of grammar rules included in the rule pool according to the classification requirement.

In an exemplary embodiment, the second determining module is further configured to: determining a parent node in the rule tree as a first classification result of the target object, and determining a child node of the parent node as a second classification result of the target object, wherein the classification result comprises: the first classification result and the second classification result.

In an exemplary embodiment, the second determining module is further configured to: receiving an acquisition request initiated by terminal equipment; responding to the acquisition request, and determining whether the terminal equipment has the acquisition authority for acquiring the classification result; and sending the classification result of the target object to the terminal equipment under the condition that the terminal equipment has the acquisition permission.

In an exemplary embodiment, the generating module is further configured to: determining whether the target object opens a generation right or not, wherein the generation right is used for indicating whether the target object allows regular data of an execution target event of the target object in a preset period to be acquired or not; and generating a tag list for the target object under the condition that the target object has opened the generation permission.

According to a further aspect of embodiments of the present application, there is also provided a computer-readable storage medium having a computer program stored therein, wherein the computer program is configured to perform the above-described method of determining a classification result when run.

According to still another aspect of the embodiments of the present application, there is further provided an electronic device including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the method for determining the classification result by the computer program.

In the embodiment of the application, a tag list containing a plurality of tag information is generated for a target object based on regular data of an execution target event of the target object in a preset period, and a rule tree of the target object is generated according to the plurality of tag information contained in the tag list for determining a classification result of the target object. By adopting the technical scheme, the problem that the classification mode of the target object in the prior art is poor in classification expansibility and accuracy is solved, and the effect of flexible classification is further achieved.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.

In order to more clearly illustrate the embodiments of the application or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, and it will be obvious to a person skilled in the art that other drawings can be obtained from these drawings without inventive effort.

FIG. 1 is a schematic diagram of a hardware environment of a method for determining classification results according to an embodiment of the present application;

FIG. 2 is a flow chart of a method of determining classification results according to an embodiment of the application;

FIG. 3 is a schematic diagram (one) of a method for determining classification results according to an embodiment of the present application;

FIG. 4 is a schematic diagram (II) of a method for determining classification results according to an embodiment of the present application;

Fig. 5 is a block diagram of a determination apparatus of a classification result according to an embodiment of the present application.

Detailed Description

In order that those skilled in the art will better understand the present application, a technical solution in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present application without making any inventive effort, shall fall within the scope of the present application.

It should be noted that the terms "first," "second," and the like in the description and the claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

According to an aspect of an embodiment of the present application, a method for determining a classification result is provided. The method for determining the classification result is widely applied to full-house intelligent digital control application scenes such as intelligent Home (Smart Home), intelligent Home equipment ecology, intelligent Home (INTELLIGENCE HOUSE) ecology and the like. Alternatively, in the present embodiment, the above-described determination method of the classification result may be applied to a hardware environment constituted by the terminal device 102 and the server 104 as shown in fig. 1. As shown in fig. 1, the server 104 is connected to the terminal device 102 through a network, and may be used to provide services (such as application services and the like) for a terminal or a client installed on the terminal, a database may be set on the server or independent of the server, for providing data storage services for the server 104, and cloud computing and/or edge computing services may be configured on the server or independent of the server, for providing data computing services for the server 104.

The network may include, but is not limited to, at least one of: wired network, wireless network. The wired network may include, but is not limited to, at least one of: a wide area network, a metropolitan area network, a local area network, and the wireless network may include, but is not limited to, at least one of: WIFI (WIRELESS FIDELITY ), bluetooth. The terminal device 102 may not be limited to a PC, a mobile phone, a tablet computer, an intelligent air conditioner, an intelligent smoke machine, an intelligent refrigerator, an intelligent oven, an intelligent cooking range, an intelligent washing machine, an intelligent water heater, an intelligent washing device, an intelligent dish washer, an intelligent projection device, an intelligent television, an intelligent clothes hanger, an intelligent curtain, an intelligent video, an intelligent socket, an intelligent sound box, an intelligent fresh air device, an intelligent kitchen and toilet device, an intelligent bathroom device, an intelligent sweeping robot, an intelligent window cleaning robot, an intelligent mopping robot, an intelligent air purifying device, an intelligent steam box, an intelligent microwave oven, an intelligent kitchen appliance, an intelligent purifier, an intelligent water dispenser, an intelligent door lock, and the like.

In this embodiment, a method for determining a classification result is provided and applied to the terminal device, and fig. 2 is a flowchart of a method for determining a classification result according to an embodiment of the present application, where the flowchart includes the following steps:

Step S202, generating a tag list for the target object, where the tag list includes: the system comprises a plurality of tag information, a plurality of target objects and a plurality of control units, wherein each tag information in the plurality of tag information is used for indicating regular data of execution target events of the target objects in a preset period;

Optionally, the target event in step S202 includes, but is not limited to, water usage behavior of the target object, tv watching behavior, application software usage behavior, sports behavior, etc.

Step S204, determining a rule tree of the target object according to the plurality of tag information included in the tag list;

step S206, determining the classification result of the target object according to the rule tree.

Through the steps, a tag list is generated for the target object, wherein the tag list comprises the following components: the system comprises a plurality of tag information, a plurality of target objects and a plurality of control units, wherein each tag information in the plurality of tag information is used for indicating regular data of execution target events of the target objects in a preset period; determining a rule tree of the target object according to the plurality of tag information included in the tag list; the classification result of the target object is determined according to the rule tree, the problem that the classification mode of the target object in the prior art is poor in classification expansibility and accuracy is solved, and the effect of flexible classification is achieved.

In an exemplary embodiment, before performing the step S202 to generate the tag list for the target object, the method further includes: determining tag types of the plurality of tag information, wherein the tag types are used for indicating unit time and the target event included in the preset period; acquiring rule sub-data of the target object for executing the target event in the unit time according to the type of the search tag; and determining rule data of the execution target event of the target object in a preset period according to the rule sub-data corresponding to all the unit time.

Optionally, in the above embodiment, a plurality of tags with atomization characteristics may be determined through specific services, and the tag content may be atomized, that is, thinned as much as possible, so that it is ensured that the tag content does not need to be segmented again, taking a water service as an example, statistics is performed on water usage records in the vicinity of the user (corresponding to the target object), and the time is specifically divided into units of hours, that is, several minutes per week, and for the water usage, the water usage rule of the user obviously cannot be accurate to units of minutes, so that statistics is performed on the water usage time distribution of the user in units of hours, that is, the tag content has atomization characteristics, and the continuous segmentation has little help on the water service.

For example, it is counted that the user uses water in about four weeks at 7 points of 2 weeks, then the user is marked with a label of the water consumption law of 7 points of tuesday, a plurality of label information exist on the same user, and if the user uses water in three 8 points of every week, the user is continuously marked with a label of the water consumption law of 8 points of tuesday, that is, each user corresponds to a label list, and the label list comprises a plurality of label information. In the water service of this embodiment, there are a total of 7×24=168 tags, that is, tag information including water behavior distribution in units of time from monday to sunday, and from 0 to 23 points, and since the atomized tag information covers the entire time range, the possibility of the tag information being changed is low, and frequent modification of the tag information is not required. It should be noted that, in different services, the types and the numbers of tag information are different. Through the plurality of tags of the embodiment, the classification of the water use behavior of the user in unit time can be realized, and the classification data of all time periods can be further covered.

In an exemplary embodiment, for the implementation process of determining the rule tree of the target object according to the plurality of tag information included in the tag list in the step S204, the implementation process specifically includes: obtaining a rule pool corresponding to the rule tree to be generated, wherein the rule pool comprises: a plurality of grammar rules; for any tag information in the plurality of tag information, determining a target grammar rule matched with the any tag information from the rule pool; constructing a node of any label information in the rule tree according to the target grammar rule, wherein the value of the node is any label information; the rule tree is determined in a case where the plurality of tag information has all constructed nodes in the rule tree.

In the above embodiment, the rule tree is generated according to the tag information, and the tag information needs to be matched with the grammar rule first. Then, according to the matched rule, constructing rule tree nodes, and connecting the nodes to form a rule tree. The method comprises the following specific steps: and matching the label with the grammar rule, finding the grammar rule corresponding to the label, constructing a node, wherein the value of the node is label information until all label information is matched with the grammar rule, and constructing a rule tree.

In an exemplary embodiment, the implementation process of obtaining the rule pool corresponding to the rule tree to be generated includes: acquiring the classification requirement of the target object, wherein the classification requirement is used for indicating the quantity to be classified, the category to be classified and the rule pattern of grammar rules of the target object; and configuring a plurality of grammar rules included in the rule pool according to the classification requirement.

Optionally, in the above embodiment, the rule pool includes a plurality of grammar rules, where the grammar rules are a rule pattern determined according to specific service requirements, for example, the service requirements need to count users of water in six evening per week (16 to 19 points), and then a grammar rule corresponding to water in six evening per week is configured in the rule pool. A rule tree can be formed by a plurality of grammar rules, for example, the grammar rule corresponding to the weekend water is a father node of the rule tree, then the grammar rule corresponding to the Saturday water is a child node of the father node, finally, the rule tree is formed by a plurality of nodes, and the nodes on the rule tree can be screened to realize complex classification requirements through the rule tree of the embodiment.

In an exemplary embodiment, for the implementation process of determining the classification result of the target object according to the rule tree in step S206, the implementation process specifically includes: determining a parent node in the rule tree as a first classification result of the target object, and determining a child node of the parent node as a second classification result of the target object, wherein the classification result comprises: the first classification result and the second classification result.

Alternatively, in the above embodiment, for example, the father node is the weekend water and the child node is the friday evening water, then the first classification result is all users of the friday water, and the second classification result is the user of the friday evening water. Specifically, a plurality of child nodes may be included under a parent node, and then the second classification result may further include a user using water in the evening on sunday, a user using water in the morning on Saturday, and so on, by determining the first classification result and the second classification result, regular data of water behaviors of the user under different granularities can be obtained, and when analyzing the user behaviors, classification results with low granularity or high granularity can be selected according to service requirements.

In an exemplary embodiment, after the step S206 is performed to determine the classification result of the target object according to the rule tree, the method further includes: receiving an acquisition request initiated by terminal equipment; responding to the acquisition request, and determining whether the terminal equipment has the acquisition authority for acquiring the classification result; and sending the classification result of the target object to the terminal equipment under the condition that the terminal equipment has the acquisition permission.

When the classified data is acquired, the classified result is only inquired about a part of devices with acquiring rights, specifically, for example, the user inquires about own water use time distribution on the mobile phone, the server judges that the classified data has acquiring rights, the server sends the water use time distribution result of the user to the mobile phone of the user, when the user inquires about the water use time distribution of the family member on the mobile phone, the server judges that the classified data has acquiring rights, the water use time distribution result of the family member of the user is sent to the mobile phone of the user, when the user inquires about the water use time distribution of other unrelated persons on the mobile phone, the server judges that the classified data does not have acquiring rights, and the inquiry request of the user is refused.

In an exemplary embodiment, for the execution process of generating the tag list for the target object in the step S202, the method specifically includes: determining whether the target object opens a generation right or not, wherein the generation right is used for indicating whether the target object allows regular data of an execution target event of the target object in a preset period to be acquired or not; and generating a tag list for the target object under the condition that the target object has opened the generation permission.

It should be noted that, a part of users may not need to use the related water service with statistical water usage time distribution, or the users do not want to collect own water usage information, so the users may set the generation permission of the closing classification result by themselves, and may open the generation permission again when the users need to use the related water service.

Through the embodiment, the classification requirement of the service is converted into the atomized label information, so that the classification range can be effectively enlarged, and the development cost of the subsequent classification rules is reduced. And the classification rules adopt a rule grammar to convert the rule calculation process into a rule tree process, so that the classification process can be configured, classification nodes can be formed by the classification process data, and the classification flexibility is greatly improved.

In order to better understand the process of the method for determining the classification result, the following describes the implementation method flow for determining the classification result in combination with the alternative embodiment, but is not used for limiting the technical scheme of the embodiment of the application.

In this embodiment, a method for determining a classification result is provided, and fig. 3 is a schematic diagram of a method for determining a classification result according to an embodiment of the present application, as shown in fig. 3: the method is realized by the big data end and the service end together, firstly, the event needing to be counted and the preset period are determined, then a plurality of tag information is generated according to service requirements to obtain a tag pool, then the tag pool of the service end synchronizes the tag pool generated by the big data end, then a rule tree is calculated according to a rule pool configured manually, a user classification result is obtained through screening rules after the rule tree is generated, the process of obtaining the user classification result is calculated at the service end and stored in a table, different services can flexibly select a plurality of rules to classify, the table of the user classification result is synchronized and stored by the big data end, and the classification result of the corresponding service can be queried from the table when the service module needs to use the user classification result.

In an alternative embodiment, fig. 4 is a schematic diagram of a rule tree according to an embodiment of the present application, where a monday 7-point rule, a wednesday 10-point rule, and a wednesday 9-point rule are label information, and a corresponding grammar rule can be generated according to the label information, for example, a grammar rule generated according to the monday 7-point rule, the wednesday 7-point rule is A7B7, a grammar rule generated according to the wednesday 10-point rule, and the wednesday 9-point rule is F10G9, and then a plurality of grammar rules form the whole rule tree, where each grammar rule corresponds to one node of the rule tree, when determining a classification result, the classification result can be obtained by selecting a designated node, and a plurality of nodes can be simultaneously selected according to service requirements, so as to greatly improve classification efficiency and classification flexibility.

It should be noted that a rule tree is a machine learning model for classifying input data by a series of rules. The rule tree construction process, which generally includes selecting features for classification from an input dataset, dividing the dataset into different subsets, constructing a rule for classifying the data according to differences in feature values for each subset until all data are properly classified or a stop condition is reached, may be implemented by a CYK (Cocke-young-Kasami algoritm) algorithm, named by the name of three creators, which is an algorithm for computing context-free grammar, and automatically combines rule-compliant tree structures from bottom to top. The classification process of the rule tree is simple and visual and easy to explain, so that the rule tree is widely used in practical application.

From the description of the above embodiments, it will be clear to a person skilled in the art that the method according to the above embodiments may be implemented by means of software plus the necessary general hardware platform, but of course also by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising several instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method of the various embodiments of the present application.

Fig. 5 is a block diagram of a structure of a classification result determining apparatus according to an embodiment of the present application; as shown in fig. 5, includes:

The generating module 52 is configured to generate a tag list for the target object, where the tag list includes: the system comprises a plurality of tag information, a plurality of target objects and a plurality of control units, wherein each tag information in the plurality of tag information is used for indicating regular data of execution target events of the target objects in a preset period;

A first determining module 54, configured to determine a rule tree of the target object according to the plurality of tag information included in the tag list;

A second determining module 56 is configured to determine a classification result of the target object according to the rule tree.

By the device, a tag list is generated for the target object, wherein the tag list comprises the following components: the system comprises a plurality of tag information, wherein each tag information in the plurality of tag information is used for indicating regular data of an execution target event of the target object in a preset period, a rule tree of the target object is determined according to the plurality of tag information included in the tag list, and a classification result of the target object is determined according to the rule tree. The method solves the problems of poor classification expansibility and accuracy of the target object in the prior art, and further realizes the effect of flexible classification.

In one exemplary embodiment, the generation module 52 is further configured to: determining tag types of the plurality of tag information, wherein the tag types are used for indicating unit time and the target event included in the preset period; acquiring rule sub-data of the target object for executing the target event in the unit time according to the type of the search tag; and determining rule data of the execution target event of the target object in a preset period according to the rule sub-data corresponding to all the unit time.

In an exemplary embodiment, the first determining module 54 further includes: an obtaining unit, configured to obtain a rule pool corresponding to the rule tree to be generated, where the rule pool includes: a plurality of grammar rules; a first determining unit, configured to determine, for any tag information in the plurality of tag information, a target grammar rule matching with the any tag information from the rule pool; the construction unit is used for constructing a node of any label information in the rule tree according to the target grammar rule, wherein the value of the node is any label information; a second determining unit configured to determine the rule tree in a case where the plurality of tag information has all constructed nodes in the rule tree.

In an exemplary embodiment, the above-mentioned acquisition unit is further configured to: acquiring the classification requirement of the target object, wherein the classification requirement is used for indicating the quantity to be classified, the category to be classified and the rule pattern of grammar rules of the target object; and configuring a plurality of grammar rules included in the rule pool according to the classification requirement.

In one exemplary embodiment, the second determining module 56 is further configured to: determining a parent node in the rule tree as a first classification result of the target object, and determining a child node of the parent node as a second classification result of the target object, wherein the classification result comprises: the first classification result and the second classification result.

In one exemplary embodiment, the second determining module 56 is further configured to: receiving an acquisition request initiated by terminal equipment; responding to the acquisition request, and determining whether the terminal equipment has the acquisition authority for acquiring the classification result; and sending the classification result of the target object to the terminal equipment under the condition that the terminal equipment has the acquisition permission.

In one exemplary embodiment, the generation module 52 is further configured to: determining whether the target object opens a generation right or not, wherein the generation right is used for indicating whether the target object allows regular data of an execution target event of the target object in a preset period to be acquired or not; and generating a tag list for the target object under the condition that the target object has opened the generation permission.

An embodiment of the present application also provides a storage medium including a stored program, wherein the program executes the method of any one of the above.

Alternatively, in the present embodiment, the above-described storage medium may be configured to store program code for performing the steps of:

S1, generating a tag list for a target object, wherein the tag list comprises the following components: the system comprises a plurality of tag information, a plurality of target objects and a plurality of control units, wherein each tag information in the plurality of tag information is used for indicating regular data of execution target events of the target objects in a preset period;

s2, determining a rule tree of the target object according to the plurality of tag information included in the tag list;

s3, determining a classification result of the target object according to the rule tree.

An embodiment of the application also provides an electronic device comprising a memory having stored therein a computer program and a processor arranged to run the computer program to perform the steps of any of the method embodiments described above.

Optionally, the electronic apparatus may further include a transmission device and an input/output device, where the transmission device is connected to the processor, and the input/output device is connected to the processor.

Alternatively, in the present embodiment, the above-described processor may be configured to execute the following steps by a computer program:

S1, generating a tag list for a target object, wherein the tag list comprises the following components: the system comprises a plurality of tag information, a plurality of target objects and a plurality of control units, wherein each tag information in the plurality of tag information is used for indicating regular data of execution target events of the target objects in a preset period;

s2, determining a rule tree of the target object according to the plurality of tag information included in the tag list;

s3, determining a classification result of the target object according to the rule tree.

Alternatively, in the present embodiment, the storage medium may include, but is not limited to: a U-disk, a read-only memory (ROM), a random access memory (Random Access Memory RAM), a removable hard disk, a magnetic disk, or an optical disk, etc., which can store program codes.

Alternatively, specific examples in this embodiment may refer to examples described in the foregoing embodiments and optional implementations, and this embodiment is not described herein.

It will be appreciated by those skilled in the art that the modules or steps of the application described above may be implemented in a general purpose computing device, they may be concentrated on a single computing device, or distributed across a network of computing devices, they may alternatively be implemented in program code executable by computing devices, so that they may be stored in a memory device for execution by computing devices, and in some cases, the steps shown or described may be performed in a different order than that shown or described, or they may be separately fabricated into individual integrated circuit modules, or multiple modules or steps within them may be fabricated into a single integrated circuit module for implementation. Thus, the present application is not limited to any specific combination of hardware and software.

The foregoing is merely a preferred embodiment of the present application and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present application, which are intended to be comprehended within the scope of the present application.

Claims (10)

1. A method for determining a classification result, comprising:

generating a tag list for the target object, wherein the tag list comprises the following components: the system comprises a plurality of tag information, a plurality of target objects and a plurality of control units, wherein each tag information in the plurality of tag information is used for indicating regular data of execution target events of the target objects in a preset period;

determining a rule tree of the target object according to the plurality of tag information included in the tag list;

And determining a classification result of the target object according to the rule tree.

2. The method of claim 1, wherein prior to generating the tag list for the target object, the method further comprises:

Determining tag types of the plurality of tag information, wherein the tag types are used for indicating unit time and the target event included in the preset period;

acquiring rule sub-data of the target object for executing the target event in the unit time according to the type of the search tag;

And determining rule data of the execution target event of the target object in a preset period according to the rule sub-data corresponding to all the unit time.

3. The method of determining a classification result according to claim 2, wherein determining a rule tree of the target object from the plurality of tag information included in the tag list includes:

obtaining a rule pool corresponding to the rule tree to be generated, wherein the rule pool comprises: a plurality of grammar rules;

for any tag information in the plurality of tag information, determining a target grammar rule matched with the any tag information from the rule pool;

Constructing a node of any label information in the rule tree according to the target grammar rule, wherein the value of the node is any label information;

the rule tree is determined in a case where the plurality of tag information has all constructed nodes in the rule tree.

4. The method for determining the classification result according to claim 3, wherein obtaining a rule pool corresponding to the rule tree to be generated comprises:

Acquiring the classification requirement of the target object, wherein the classification requirement is used for indicating the quantity to be classified, the category to be classified and the rule pattern of grammar rules of the target object;

and configuring a plurality of grammar rules included in the rule pool according to the classification requirement.

5. The method of claim 1, wherein determining the classification result of the target object based on the rule tree comprises:

Determining a parent node in the rule tree as a first classification result of the target object, and determining a child node of the parent node as a second classification result of the target object, wherein the classification result comprises: the first classification result and the second classification result.

6. The method of claim 1, further comprising, after determining the classification result of the target object according to the rule tree:

receiving an acquisition request initiated by terminal equipment;

Responding to the acquisition request, and determining whether the terminal equipment has the acquisition authority for acquiring the classification result;

And sending the classification result of the target object to the terminal equipment under the condition that the terminal equipment has the acquisition permission.

7. The method of claim 1, wherein generating a tag list for the target object comprises:

Determining whether the target object opens a generation right or not, wherein the generation right is used for indicating whether the target object allows regular data of an execution target event of the target object in a preset period to be acquired or not;

and generating a tag list for the target object under the condition that the target object has opened the generation permission.

8. A classification result determining apparatus, comprising:

The generating module is used for generating a tag list for the target object, wherein the tag list comprises the following components: the system comprises a plurality of tag information, a plurality of target objects and a plurality of control units, wherein each tag information in the plurality of tag information is used for indicating regular data of execution target events of the target objects in a preset period;

A first determining module, configured to determine a rule tree of the target object according to the plurality of tag information included in the tag list;

And the second determining module is used for determining the classification result of the target object according to the rule tree.

9. A computer-readable storage medium, characterized in that the computer-readable storage medium comprises a stored program, wherein the program, when run, performs the method of any one of claims 1 to 7.

10. An electronic device comprising a memory and a processor, characterized in that the memory has stored therein a computer program, the processor being arranged to execute the method according to any of the claims 1 to 7 by means of the computer program.