Method and electronic apparatus for providing data statistics information.

Abstract

The objective is to provide an information provision method and an electronic device thereof. More specifically, embodiments of this specification provide a method and an electronic device thereof for dynamically processing event data into feature event data and providing data statistics information corresponding to customer requests based on calculations of the feature event data. The data statistics information provision method according to this disclosure may include the steps of: setting up a feature event data format and a feature management set including one or more features for processing event data acquired in response to events confirmed on a service provided by the electronic device into feature event data corresponding to features; setting up the service to process and manage event data on the service into feature event data corresponding to each feature included in the feature management set according to the feature event data format; confirming first feature event data corresponding to a first feature included in the request information from the feature management set in response to customer request information related to data statistics; and providing data statistics information corresponding to the request information based on calculations on the first feature event data.

Description

Technical Field

[0001] The present disclosure relates to a method for providing data statistical information and an electronic device thereof, and more particularly, to a method for dynamically processing event data into feature event data and providing data statistical information corresponding to customer requests based on the calculation of the feature event data, and an electronic device thereof.

Background Art

[0002] With the popularization of the use of the Internet, the e-commerce market is expanding. While the proportion of visiting offline stores to purchase goods is decreasing, the proportion of purchasing goods through e-commerce using a computer or smartphone is rapidly increasing.

[0003] In an e-commerce service that mediates product transactions between consumers and sellers on a network, data related to consumers, products, and / or stores can be systematically collected, and service providers can generate and provide statistical information on rapidly changing consumer order trends, order patterns, page visit histories, etc. based on the collected data, or provide services suitable for consumer characteristics based on such statistical information. The statistical information can include information for meaningful statistics that can be collected for service users, stores, products, etc., and such statistical information can be provided through calculations on feature event data that matches the features for calculating the statistics.

[0004] As the amount of data generated from events resulting from user, store, and / or product-related actions becomes increasingly massive, the ability to manage features for meaningful statistics and to compute the corresponding statistics is crucial. However, traditional feature computation is limited to serial features, and the frequent need to re-execute calculations when adding new features necessitates multidimensional computation, creating a need for a method to efficiently add new features while maintaining low computational complexity.

[0005] In this regard, prior art such as Korean Patent Publication No. 10-1654847 or Korean Patent Publication No. 10-0840129 can be referenced. [Overview of the project] [Problems that the invention aims to solve]

[0006] The embodiments of this specification aim to provide an information provision method and an electronic apparatus thereof. More specifically, the embodiments of this specification aim to provide a method and an electronic apparatus thereof for dynamically processing event data into feature event data and providing data statistical information that responds to customer requests based on calculations of the feature event data.

[0007] The technical problems that this embodiment aims to solve are not limited to those described above, and other technical problems can be inferred from the following embodiments. [Means for solving the problem]

[0008] A method for providing data statistics information for an electronic device according to one embodiment may be provided, comprising the steps of: setting up a feature event data format and a feature management set including one or more features for processing event data acquired in response to events confirmed on a service provided by the electronic device into feature event data corresponding to features; setting up the device to process and manage event data on the service into feature event data corresponding to each feature included in the feature management set according to the feature event data format; confirming first feature event data corresponding to a first feature included in the request information from the feature management set in response to customer request information related to data statistics; and providing data statistics information corresponding to the request information based on calculations performed on the first feature event data.

[0009] A method for providing data statistics information for an electronic device according to one embodiment may be provided, wherein events are confirmed based on actions taken by the service user on the service, and the event data includes data generated by the service in response to the actions.

[0010] A method for providing data statistics information for an electronic device according to one embodiment is provided, wherein the feature event data format includes one or more fields for feature event data, and the one or more fields are set based on at least some of the fields included in the event data.

[0011] A method for providing data statistics information for an electronic device according to one embodiment may be provided, wherein at least some fields are identified from among the fields of event data determined based on inputs that set fields for event data.

[0012] A method for providing data statistics information for an electronic device according to one embodiment may be provided, wherein each feature included in a feature management set is determined based on an input that sets at least one field included in one or more fields for each feature.

[0013] A method for providing data statistics information for an electronic device according to one embodiment may be provided, wherein one or more fields include a subject field that specifies the subject of the data and a subject value field that specifies the data value corresponding to the subject of the data.

[0014] A method for providing data statistics information for an electronic device according to one embodiment may be provided, wherein one or more fields include an object field that specifies a data object and an object value field that specifies a data value corresponding to the data object.

[0015] A method for providing data statistics information for an electronic device according to one embodiment may be provided, the method for providing data statistics information comprising one or more fields including a feature identification field for a feature identifier, an operator field for setting an operator to be used for data calculations, and a time field for the time when event data was acquired on the service.

[0016] A method for providing data statistics information for an electronic device according to one embodiment may be provided, further comprising the steps of: confirming one event data included in event data; confirming one or more feature event data obtained by processing one event data based on one or more features; and setting up information regarding the mapping relationship for one event data and one or more feature event data.

[0017] A method for providing data statistics information for an electronic device according to one embodiment is provided, the method for providing data statistics information comprising the steps of: confirming first feature event data; confirming a data subject for the first feature, a data object for the first feature, and an operator for the first feature; confirming a plurality of feature event data in which the data subject for the first feature is specified as a data subject field on the feature event data format; and confirming first feature event data selected from the plurality of feature event data based on the data object for the first feature and the operator for the first feature.

[0018] A method for providing data statistics information for an electronic device according to one embodiment may be provided, the method for providing data statistics information comprising the steps of: confirming first feature event data; setting a data inquiry period corresponding to the requested information; and confirming first feature event data selected from a plurality of feature event data based on the data inquiry period, the data object for the first feature, and the operator for the first feature.

[0019] A method for providing data statistics information for an electronic device according to one embodiment may be provided, wherein the first feature event data includes feature event data in which a data object for the first feature is specified in the data object field on the feature event data format, an operator for the first feature is specified in the operator field on the feature event data format, and a time point specified in the time point field on the feature event data format is included in the data query period.

[0020] A method for providing data statistics information for an electronic device according to one embodiment may be provided, wherein the data statistics information includes information relating to the result of calculating first feature event data based on an operator for a first feature.

[0021] A method for providing data statistics information for an electronic device according to one embodiment, further comprising the step of obtaining requested information from a customer, wherein the requested information includes information about a feature group including multiple features for the customer, and the first feature may be a method for providing data statistics information included in the feature group.

[0022] A method for providing data statistics information for an electronic device according to one embodiment may be provided, further comprising the step of adding a second feature to the feature management set if a first feature included in a feature group is not found in the feature management set.

[0023] A method for providing data statistics information for an electronic device according to one embodiment may be provided, further comprising the step of setting up a customer-specific feature management set containing multiple features in the feature management set, based on the fact that multiple features are included in the feature management set, in order to correspond to the customer.

[0024] A method for providing data statistics information for an electronic device according to one embodiment may be provided, further comprising the steps of: confirming a first customer-specific feature management set for a first customer and a second customer-specific feature management set for a second customer; confirming the number of features common to the first customer-specific feature management set and the second customer-specific feature management set; and setting the first customer and the second customer as similar customer groups if both the first ratio of the number of common features to the number of features included in the first customer-specific feature management set and the second ratio of the number of common features to the number of features included in the second customer-specific feature management set are equal to or greater than a critical ratio.

[0025] An electronic device for providing data statistical information of an electronic device according to an embodiment, including a memory storing at least one program; and by executing at least one program, it processes event data obtained according to events confirmed on the services provided by the electronic device into feature event data corresponding to features for a feature event data format and a feature management set including one or more features, sets to process and manage the event data on the service into feature event data corresponding to each feature included in the feature management set according to the feature event data format, and according to customer request information related to data statistics, checks the first feature event data corresponding to the first feature included in the request information from the feature management set, and provides data statistical information corresponding to the request information based on calculations on the first feature event data, and an electronic device including a processor may be provided.

[0026] A computer-readable non-temporary recording medium recording a program for causing a computer to execute a data statistical information providing method according to an embodiment may be provided.

Advantages of the Invention

[0027] According to the present disclosure, the electronic device can efficiently manage data by setting to process and manage the event data on the service into feature event data corresponding to each feature included in the feature management set according to the feature event data format.

[0028] The electronic device can be made to correspond to customer request information and effectively provide data statistical information in accordance with rapidly changing business scenarios.

[0029] Electronic devices can increase the efficiency of customer management by setting up dedicated feature management sets for each customer, comparing common features among customers, and managing each customer as a similar customer group.

[0030] The effects of the present invention are not limited to those mentioned above, and any further effects not mentioned may be clearly understood by a person of the art ordinary from the description of the claims. [Brief explanation of the drawing]

[0031] [Figure 1] This figure shows the configuration of the electronic device 100 according to various embodiments. [Figure 2] This figure illustrates the operation method of an electronic device 100 for providing data statistical information in various embodiments. [Figure 3] This figure illustrates how an electronic device 100 operates to verify first feature event data corresponding to a first feature included in customer request information according to various embodiments. [Figure 4] This figure illustrates the operation method of an electronic device 100 that is configured to process event data into feature event data and manage it according to one embodiment. [Figure 5] This figure illustrates the operation method of an electronic device 100 that provides data statistics information corresponding to customer request information according to one embodiment. [Figure 6] This figure illustrates a user interface in one embodiment that allows an administrator to set the features they intend to extract. [Figure 7] This figure illustrates a user interface in one embodiment that allows an administrator to set fields for event data. [Modes for carrying out the invention]

[0032] The terminology used in the embodiments has been selected, as far as possible, to be commonly used terms, taking into account the function described herein, although this may change depending on the intent of the articulators, case law, the emergence of new technologies, etc. In certain cases, the applicant has also arbitrarily selected some terms, in which case their meanings will be described in detail in the relevant explanatory section. Therefore, the terminology used in this disclosure must be defined not merely as names of terms, but based on the meaning of the term and the overall content of this disclosure.

[0033] Throughout the specification, when a part "includes" a component, this does not mean that it excludes other components, but rather that it may include other components, unless otherwise stated. Furthermore, terms such as "...part" and "...module" used in the specification mean a unit that processes at least one function or operation, which may be embodied by hardware or software, or by a combination of hardware and software.

[0034] Throughout the specification, the expression “at least one of a, b, and c” may encompass “a alone,” “b alone,” “c alone,” “a and b,” “a and c,” “b and c,” or “all of a, b, and c.”

[0035] The embodiments of this disclosure will be described below in detail, with reference to the attached figures, so that they can be easily implemented by a person with ordinary skill in the art to which this disclosure pertains. However, this disclosure can be embodied in a variety of different forms and is not limited to the embodiments described herein.

[0036] The embodiments of this disclosure will be described in detail below with reference to the figures.

[0037] Figure 1 is a diagram showing the configuration of the electronic device 100 in various embodiments.

[0038] Referring to Figure 1, the electronic device 100 may include a transceiver 110, a memory 120, and a processor 130, and may be capable of providing data statistics. The electronic device 100 shown in Figure 1 only shows components relevant to this embodiment. Therefore, it will be obvious to an ordinary person of the art that the electronic device 100 may further include other general-purpose components in addition to those shown in Figure 1.

[0039] The transceiver 110 can communicate with other devices. Therefore, the electronic device 100 can send and receive information with other devices via the transceiver 110. Here, communication, i.e., the sending and receiving of data, can be wired or wireless. For this purpose, the transceiver 110 may include a wired communication module that connects to the internet etc. via a LAN (Local Area Network), a mobile communication module that connects to a mobile communication network via a mobile communication base station to send and receive data, a short-range communication module that uses a WLAN (Wireless Local Area Network) series communication method such as Wi-Fi or a WPAN (Wireless Personal Area Network) series communication method such as Bluetooth® or Zigbee®, a satellite communication module that uses a GNSS (Global Navigation Satellite System) such as GPS (Global Positioning System), or a combination thereof.

[0040] Memory 120 is hardware that stores various data processed within the electronic device 100. Memory 120 can store data processed by the electronic device 100 and data being processed. Memory 120 can also store data driven by the electronic device 100. Furthermore, memory 120 can store applications, drivers, etc., driven by the electronic device 100. Memory 120 may include RAM (random access memory) such as DRAM (dynamic random access memory) and SRAM (static random access memory), ROM (read-only memory), EEPROM (electrically erasable programmable read-only memory), CD-ROM, Blu-ray or other optical disc storage, HDD (hard disk drive), SSD (solid state drive), or flash memory.

[0041] The processor 130 controls the overall operation of the electronic device 100. To this end, the processor 130 performs calculations and processing of various types of information and can control the operation of the components of the electronic device 100. For example, the processor 130 may be made to execute a program or application for providing data statistics. The processor 130 can be embodied in a computer or similar device by hardware, software, or a combination thereof. Hardware-wise, the processor 130 can be embodied in the form of an electronic circuit that processes electrical signals and performs control functions, and software-wise, it can be embodied in the form of a program that drives the hardware-wise processor 130. On the other hand, unless otherwise specified in the following description, the operation of the electronic device 100 can be interpreted as being performed by the control of the processor 130.

[0042] In summary, diverse embodiments can be realized through diverse means. For example, diverse embodiments can be realized through hardware, firmware, software, or a combination thereof.

[0043] In the case of hardware implementation, the method, in various embodiments, can be implemented by one or more ASICs (application-specific integrated circuits), DSPs (digital signal processors), DSPDs (digital signal processing devices), PLDs (programmable logic devices), FPGAs (field programmable gate arrays), processors, controllers, microcontrollers, microprocessors, etc.

[0044] In the case of implementation by firmware or software, the methods in various embodiments can be implemented in the form of modules, procedures, or functions that perform the functions or operations described below. For example, software code may be stored in memory and driven by a processor. The memory may be located inside or outside the processor and may exchange data with the processor by various already known means.

[0045] The following sections will describe various embodiments in more detail based on the technical concept described above. The previously described concepts may apply to the various embodiments described below. For example, operations, functions, terms, etc., not defined in the various embodiments described below may be described and implemented based on the previously described concepts.

[0046] Figure 2 is a diagram illustrating the operation methods of the electronic device 100 for providing data statistical information according to various embodiments.

[0047] Referring to Figure 2, the electronic device 100 provides data statistics information corresponding to customer request information. To perform the operation of providing data statistics information, it sets up a feature management set containing a feature event data format and one or more features (S210), processes and manages event data into feature event data corresponding to each feature included in the feature management set according to the feature event data format (S220), checks for the first feature event data corresponding to the first feature included in the customer request information from the feature management set according to the customer request information related to data statistics (S230), and can provide data statistics information corresponding to the customer request information based on calculations on the first feature event data (S240).

[0048] As shown in Figure 2, the operation by which the electronic device 100 provides data statistics information corresponding to customer request information may be performed for a service provided by the electronic device 100 or a service related to the electronic device 100, and such service may include an e-commerce service in which a user orders and purchases items sold by a seller, or a food delivery intermediary service that mediates food delivery between a user and a store, and in an embodiment, the electronic device 100 may be included in a service server that provides at least one of the e-commerce service or the food delivery intermediary service.

[0049] In various embodiments, in step S210, the electronic device 100 can configure a feature event data format and a feature management set. Specifically, the electronic device 100 can configure a feature event data format for processing event data into feature event data corresponding to features, and configure a feature management set that includes features for obtaining statistics according to certain attributes for the feature event data. Here, the event data may include data obtained from a data source in response to events observed on the service provided by the electronic device 100.

[0050] In embodiments, events may be identified based on actions taken by a user of the service on the service, and event data may include data generated by the service in response to user actions. Actions may correspond to specific user actions performed on the service, such as a user searching for a store, a user visiting a store page, and / or a user placing an order from a store menu. An event is a service event that occurs as a result of a user action and may be understood as occurring independently for the user or between the user and a store or seller, etc., in response to the user's actions.

[0051] In one embodiment, event data is queued in a message queue upon the occurrence of an event, and the electronic device 100 can retrieve such event data from the message queue (or, in this application, referred to as a data source). The message queue may include Apache Kafka, which can initiate, subscribe to, store, and process data streamed in real time. Apache Kafka is a high-capacity real-time log processing system and may be a message queuing system that processes messages using a publish / subscribe paradigm. Apache Kafka is a highly scalable and high-capacity distributed messaging system that can ensure stable and sustained message delivery performance. Kafka applies the producer-consumer problem and uses three system components—producer / consumer / broker—to set up topics for large amounts of data, configure partitions based on the topics, and store them sequentially. The electronic device 100 can acquire event data from the aforementioned Kafka, and can set up a feature event data format for processing the acquired event data into feature event data corresponding to a feature, as well as a feature management set containing one or more features.

[0052] In an embodiment, the feature event data format may include one or more fields for feature event data. The feature event data format may include at least one of the following: a subject field specifying the subject of the first feature event data; a subject value field specifying the data value corresponding to the subject of the first feature event data; an object field specifying the object of the first feature event data; an object value field specifying the data value corresponding to the object of the first feature event data; an operator field setting an operator to be used for calculations of the first feature event data; a time point field for the point in time when the event data corresponding to the first feature event data was acquired on the service; and a feature identifier field for the identifier of the first feature corresponding to the first feature event data. For example, if a feature is set up to check the number of times user A of the service visited the page of store B in the past 5 hours, the feature event information to be checked for the feature may include information about user A in the subject field, information about store B in the object field, information about the sum in the operator field, and information about any point in time within the past 5 hours when the event data generated in response to user A's action of visiting store B was acquired on the service. In an embodiment, the subject field may include an identifier relating to at least one of a user, seller, and / or store that may be the subject of data generating an event on the service, and the operator field may include information about a function for calculating data statistics from event data, the function of which may include, for example, sum, count, average, first, last, max, min, set, unique count, topK, etc.

[0053] In an embodiment, one or more fields for feature event data included in a feature event data format may be set based on at least some of the fields included in the event data. In other words, one or more fields included in a feature event data format may be set based on mapping to at least some of the fields included in the event data. For example, if a customer requests data statistics related to user A, and the event data is set to include a field for identifying user A's serial number (memberSrl), then the subject field included in the feature event data format may be set to include user A's memberSrl, and the subject value field included in the feature event data format may be set to include the specific value of user A's memberSrl. In this case, setting the subject field included in the feature event data format to include memberSrl for a user may be done based on the fact that the subject field included in the feature event data format is mapped to a field in the event data that is set to include memberSrl.

[0054] In one embodiment, at least some of the fields in the event data that are used to set one or more fields for feature event data may be identified from the fields in the event data determined based on the input for setting the fields for the event data. That is, the fields in the event data may be determined based on the input for setting the fields in the event data by an administrator, and at least some of the fields in the event data thus determined may be used to set one or more fields for feature event data.

[0055] In one embodiment, features included in a feature management set may be determined based on an input that sets at least one of the one or more fields included in the feature for the feature. That is, at least some of the fields for setting the feature may be determined directly through an input that the administrator sets, and the administrator may determine at least some of the fields included in the feature by directly selecting the fields for the feature or by setting the fields for the feature based on a mapping relationship with the fields in the event data described above.

[0056] Embodiments in which features included in a feature management set are determined based on the inputs set for each feature, and embodiments in which at least some fields included in the event data are identified from the fields in the event data, will be described in detail below with reference to Figures 6 and 7.

[0057] In various embodiments, in step 220, the electronic device 100 may be configured to process and manage event data on the service into feature event data corresponding to each feature included in the feature management set, according to the feature event data format. For example, depending on the settings of the electronic device 100, event data may be processed into first feature event data corresponding to a first feature, and into second feature event data corresponding to a second feature, in which case the first feature event data and the second feature event data may correspond to processed data processed to conform to the feature event data format. Embodiments in which event data is processed and managed into feature event data corresponding to each feature will be described in detail below with reference to Figure 4.

[0058] In various embodiments, in step S230, the electronic device 100 can verify first feature event data corresponding to the first feature. For example, the electronic device 100 can obtain request information from a customer and, depending on the customer's request information, can verify first feature event data corresponding to the first feature included in the customer's request information. The customer's request information may be information about a customer's request to verify data statistics related to a service, and may include, for example, a request to verify data statistics necessary to recommend a suitable store to a user. Such request information may include features necessary to calculate the data statistics requested by the customer, and may include multiple features for verifying multiple data statistics if the customer wishes to verify multiple data statistics. Furthermore, such multiple features may be included in the request information in the form of information about a feature group. Based on the information about the feature group, the electronic device 100 can verify each feature included in the feature group, and if the first feature included in the feature group is verified in the feature management set, it can verify first feature event data corresponding to the first feature. Subsequently, the electronic device 100 can perform calculations on the first feature event data and provide the customer with first data statistics information corresponding to the first feature, and the customer can verify the first data statistics information.

[0059] In one embodiment, the electronic device 100 can add a second feature to the feature management set. Specifically, if the customer's request information includes a first feature and a second feature, the electronic device 100 may need to check the first feature event data corresponding to the first feature and the second feature event data corresponding to the second feature. However, it is also possible that only the first feature is checked in the feature management set and the second feature is not checked in the feature management set. In this case, the electronic device 100 can add the second feature to the feature management set. Once the second feature is added to the feature management set, the same operations of the electronic device 100 described above can be performed on the second feature. For example, the electronic device 100 can check the second feature event data corresponding to the second feature, perform calculations on the second feature event data, and provide the customer with second data statistics corresponding to the second feature, which the customer can then check. In this way, the electronic device 100 can accurately extract feature event data for features corresponding to customer requests by processing event data into feature event data according to the configured feature management set. If the relevant feature is not found in the feature management set, it can be easily added. As a result, data statistics corresponding to the features requested by the customer can be efficiently provided.

[0060] In various embodiments, in step S240, the electronic device 100 can provide data statistics corresponding to customer request information based on calculations performed on the first feature event data. Here, the data statistics may include meaningful data statistics that need to be collected about users, delivery personnel, stores, etc. on the service, and may include various data statistics for confirming, for example, information about stores that users frequently visit, information about other stores that offer similar menus to stores that users frequently visit, and / or information about stores that users rate highly. In embodiments, the data statistics may include information about the results of calculations performed on the first feature event data based on an operator for the first feature. For example, if the operator for the first feature is a sum operator, the electronic device 100 can confirm information about the result of combining all the first feature event data as data statistics corresponding to the first feature and provide it to the customer.

[0061] In this embodiment, the electronic device 100 can set information regarding the mapping relationship between event data and feature event data. Specifically, the electronic device 100 can identify first event data from the event data on the service, identify one or more feature event data that have been processed from the first event data based on one or more features included in the feature management set, and at this time, set information regarding the mapping relationship between the first event data and one or more feature event data. That is, if the feature management set includes multiple features, one event data may be processed into multiple feature event data, so the mapping relationship between these can be set so that multiple feature event data processed from one event data can be identified.

[0062] For example, if a feature management set including a first feature and a second feature is set up, and the first event data is processed into first feature event data corresponding to the first feature and second feature event data corresponding to the second feature, the electronic device 100 can set up mapping relationship information indicating that the first feature event data and the second feature event data were processed from the first event data.

[0063] In the embodiment, information regarding mapping relationships may be set based on the identification information of event data and the identification information of feature event data. For example, if first feature event data and second feature event data are processed from first event data, the electronic device 100 can map the first event data identification information corresponding to the first event data to the first feature event identification information corresponding to the first feature event data and the second feature event identification information corresponding to the second feature event data, and can set and manage information regarding such correspondence relationships as information regarding mapping relationships for the first event data, first feature event data, and second feature event data. The electronic device 100 can store and manage such information regarding mapping relationships in a database, or, if the feature corresponding to the feature event data is a feature requested by a particular customer, it can provide the information regarding the mapping relationships along with data statistics to that particular customer.

[0064] In one embodiment, the electronic device 100 can set up a customer-specific feature management set. Specifically, the electronic device 100 can obtain request information from a customer, identify multiple features based on information about the feature group included in the request information, and, if it confirms that all of the relevant multiple features are included in the feature management set, it can set up a customer-specific feature management set within the feature management set that corresponds to the customer and includes the relevant multiple features. In another embodiment, if the electronic device 100 confirms that only some of the multiple features included in the request information are included in the feature management set, it can add the remaining features not included in the feature management set to the feature management set, and then set up a customer-specific feature management set from the feature management set to which the remaining features have been added, that corresponds to the customer and includes the relevant multiple features.

[0065] For example, if the request information obtained from the first customer includes both the first and second features, and the feature management set includes both the first and second features, the electronic device 100 can set up a feature management set specifically for the first customer that includes both the first and second features. As another example, if the request information obtained from the first customer includes both the first and second features, but the feature management set only includes the first feature, the electronic device 100 can add the second feature to the feature management set and then set up a feature management set specifically for the first customer that includes both the first and second features based on the feature management set to which the second feature has been added. By setting up and managing customer-specific feature management sets corresponding to customers and using these customer-specific feature management sets to provide data statistics corresponding to customer request information, the electronic device 100 can improve the efficiency of customer-specific management in services where business scenarios are rapidly changing.

[0066] In this embodiment, the electronic device 100 can set the first customer and the second customer as similar customer groups based on the first customer-specific feature management set and the second customer-specific feature management set. Specifically, the electronic device 100 checks the number of features common to the first customer-specific feature management set and the second customer-specific feature management set, calculates a first ratio of the number of common features to the number of features included in the first customer-specific feature management set and a second ratio of the number of common features to the number of features included in the second customer-specific feature management set, and if both ratios are greater than or equal to a critical ratio, the first customer and the second customer can be set and managed as similar customer groups. If the proportion of features common to each customer is high in each customer's dedicated feature management set, each customer can be classified into a group that requests similar data statistics, and therefore, the relevant customers can be set and managed as similar customer groups.

[0067] For example, if the first customer-specific feature management set and the second customer-specific feature management set each contain five features, and there are three common features, and the critical ratio is 0.5, then both the first and second ratios are 3 / 5, which is greater than or equal to the critical ratio of 0.5, so the first and second customers can be set as the first similar customer group. By setting and managing each customer as a similar customer group based on the number of common features in each customer-specific feature management set, the electronic device 100 can increase the efficiency of customer management and potentially provide customers included in similar customer groups with faster data statistics.

[0068] On the other hand, the specific operation of the electronic device 100, which checks the feature event data corresponding to the features included in the customer request information in Figure 2, can be performed by the method shown in Figure 3 below.

[0069] Figure 3 shows how an electronic device 100 operates to verify first feature event data corresponding to a first feature included in customer request information according to various embodiments.

[0070] Referring to Figure 3, the electronic device 100 checks the first feature event data and, in order to perform the operation of checking the first feature event data, checks the data subject for the first feature, the data object for the first feature, and the operator for the first feature S310, checks multiple feature event data in which the data subject for the first feature is specified as the data subject field on the feature event data format S320, and can check the first feature event data selected from the multiple feature event data based on the data object for the first feature and the operator for the first feature S330.

[0071] According to various embodiments, the electronic device 100 can identify the data subject for the first feature, the data object for the first feature, and the operator for the first feature. For example, the electronic device 100 can identify memberSrl as information identifying the data subject for the first feature, identify amount as information identifying the data object for the first feature, and identify sum as the operator for the first feature.

[0072] According to various embodiments, the electronic device 100 can identify multiple feature event data where the data subject for the first feature is specified as the data subject field on the feature event data format. In other words, the electronic device 100 can identify multiple feature event data from among the feature event data where the data subject corresponding to the data subject field is the data subject for the first feature. For example, if the data subject for the first feature is identified as memberSrl, the electronic device 100 can identify multiple feature event data where the data subject field on the feature event data format is specified as memberSrl. That is, the electronic device 100 can primarily classify feature event data based on the subject field of the feature event data.

[0073] According to various embodiments, the electronic device 100 can identify first feature event data selected from among multiple feature event data based on the data object for the first feature and the operator for the first feature. For example, if the data object for the first feature is identified as amount and the operator for the first feature is sum, the electronic device 100 can select feature event data from among multiple feature event data in which the data object field is specified as amount and the operator field is specified as sum, and can identify the feature event data thus selected as first feature event data. In other words, the electronic device 100 can primarily classify feature event data based on the subject field of the feature event data, and secondarily classify feature event data based on at least one of the object field and operator field of the feature event data, and can identify feature event data corresponding to features included in customer request information.

[0074] In one embodiment, the electronic device 100 may set a data query period corresponding to the customer's request information in order to confirm feature event data corresponding to the features included in the customer's request information. In this case, the first feature event data can be confirmed based on the set data query period, the data object for the first feature, and the operator for the first feature. For example, if the data query period corresponding to the customer's request information is from 00:00 to 05:00, the data object for the first feature is confirmed as amount, and the operator for the first feature is sum, the electronic device 100 can confirm as the first feature event data event data where the data object field on the feature event data format is specified as amount, the operator field is specified as sum, and the time specified in the time field on the feature event data format is within 00:00 to 05:00. Here, the time specified in the time field on the feature event data format can mean the time when the event data corresponding to the feature event data was acquired on the service based on a user action. As a result, the electronic device 100 can classify feature event data primarily based on the subject field of the feature event data, secondarily based on at least one of the object field and operator field of the feature event data, and tertiarily based on the time field of the feature event data.

[0075] Figure 4 is a diagram illustrating the operation method of an electronic device 100 configured to process and manage event data into feature event data according to one embodiment. Identification number 401 may be event data, identification number 402 may be a feature management module included in the electronic device to manage a feature management set, identification number 403 may be a feature event data format, identification number 404 may be a data processing unit included in the electronic device, and identification number 405 may be a data calculation unit included in the electronic device.

[0076] Referring to Figure 4, as an event occurs based on an action taken by a user on the service, event data is queued in Kafka, and the electronic device 100 can obtain event data 401 from Kafka. At this time, the event data 401 obtained by the electronic device 100 may include one or more fields. For example, in Figure 4, the event data 401 may include a field for memberSrl ("10005"), a field for storeId ("23648"), a field for pcid ("QS234RTTY"), a field for eventType ("Impression"), a field for amount ("1456"), and a field for orderId ("23384").

[0077] The electronic device 100 can configure a feature event data format and a feature management set containing one or more features for processing the event data 401 in Figure 4 into feature event data 406, 407, and 408 corresponding to the features. Based on the feature management module 402 included in the electronic device 100, a feature event data format 403 can be identified that includes at least one of the following: subject fields, subject value fields, object field, object value field, feature identification field (featureId), calculators, and time field (trxTime). Each field included in the feature event data format 403 can be managed to be set based on at least some of the fields included in the event data. For example, the electronic device 100 can manage, based on the feature management module 402, so that the data subject fields included in the feature event data format 403 are set by the memberSrl field, storeId field, and pcid field of the event data 401, and so that the data object fields included in the feature event data format 403 are set by the amount field of the event data 401.

[0078] The electronic device 100 can be configured to process and manage event data 401 using the feature event data format 403 to create feature event data 406, 407, and 408 corresponding to each feature included in the feature management set. For example, the data processing unit 404 included in the electronic device 100 can process event data 401 using the feature event format 403 set based on the feature management module 402 to create first feature event data 406 corresponding to the first feature, second feature event data 407 corresponding to the second feature, and third feature event data 408 corresponding to the third feature. In this case, if the feature management set does not include the first feature, second feature, and third feature, the electronic device 100 can add the first feature, second feature, and third feature to the feature management set. For example, the feature management module 402 can add the first feature corresponding to memberSrl, the second feature corresponding to storeId, and the third feature corresponding to pcid to the feature management set. As a result, the data processing unit 404 can process the event data 401 into a first feature event data 406 in which the subject field of the feature event data format 403 is specified as memberSrl, a second feature event data 407 in which the subject field is specified as storeId, and a third feature event data 408 in which the subject field is specified as pcid. Each of the subject value fields of the respective feature event data 406, 407, and 408 can be set to contain values ​​corresponding to the memberSrl value field ("10005"), the storeId value field ("23648"), and the pcid value field ("QS234RTTY") of the event data 401.

[0079] The electronic device 100 can check feature event data corresponding to the features included in the customer's request information from the feature management set, in response to the request information related to data statistics. For example, if the customer's request information includes a first feature corresponding to memberSrl, a second feature corresponding to storeId, and a third feature corresponding to pcid, the electronic device 100 can check the first feature event data 406, the second feature event data 407, and the third feature event data 408.

[0080] The electronic device 100 can provide data statistics corresponding to customer requests based on calculations performed on feature event data. For example, the data calculation unit 405 included in the electronic device 100 can calculate the first feature event data 406 based on the operator for the first feature ("sum, count, avg") specified in the operator field of the first feature event data 406, calculate the second feature event data 407 based on the operator for the second feature ("sum, avg") specified in the operator field of the second feature event data 407, and calculate the third feature event data 408 based on the operator for the third feature ("distinct") specified in the operator field of the third feature event data 408, thereby allowing the user to verify the data statistics. The electronic device 100 can transmit the data statistics to Kafka and store them in the feature store, or provide them to the customer. By configuring the electronic device 100 to dynamically process and manage event data on the service into feature event data in this way, it is possible to minimize the impact on the calculation work of other features even when adding features by performing multidimensional calculations.

[0081] Figure 5 is a diagram illustrating the operation method of an electronic device 100 that provides data statistics corresponding to customer request information according to one embodiment. Identification number 501 may be one event data obtained by the electronic device 100 from Kafka, identification number 502 may be a first feature event data processed from event data 501, identification number 503 may be a second feature event data processed from event data 501, and identification number 504 may be a third feature event data processed from event data 501.

[0082] Identification number 505 may be first feature event data obtained by processing multiple event data including the one event data using the first feature; identification number 506 may be second feature event obtained by processing multiple event data including the one event data using the second feature; and identification number 507 may be third feature event obtained by processing multiple event data including the one event data using the third feature.

[0083] Identification number 508 may represent first statistical information based on first feature event data, identification number 509 may represent second statistical information based on second feature event data, and identification number 509 may represent third statistical information based on third feature event data.

[0084] Referring to Figure 5, the electronic device 100 can continuously receive event data from Kafka and can be configured to process and manage the received event data into feature event data corresponding to features. For example, the electronic device 100 can receive event data 501 from Kafka and be configured to process it into first feature event data 502 corresponding to a first feature, second feature event data 503 corresponding to a second feature, and third feature event data 504 corresponding to a third feature. Thus, event data 501 can be processed into first feature event data 502, second feature event data 503, and third feature event data 504.

[0085] In one embodiment, the electronic device 100 can obtain request information from a customer, and the request information may include information about a feature group that includes multiple features for the customer. For example, request information obtained by the electronic device 100 from a first customer may include information about a feature group that includes a first feature, a second feature, and a third feature for the first customer. In order to provide the customer with data statistics information corresponding to each of the first, second, and third features, the electronic device 100 can process multiple event data on the service to suit each feature and, based on this, identify the first feature event data 505 corresponding to the first feature, the second feature event data 506 corresponding to the second feature, and the third feature event data 507 corresponding to the third feature.

[0086] In this embodiment, the electronic device 100 can verify the data subject for the first feature, the data object for the first feature, and the operator for the first feature in order to verify the first feature event data. After verifying a plurality of feature event data in which the data subject for the first feature is specified as the data subject field on the feature event data format, the electronic device 100 can verify the first feature event data selected from the plurality of feature event data based on the data object for the first feature and the operator for the first feature.

[0087] For example, the electronic device 100 can identify memberSrl, which is the data subject for the first feature; amount, which is the data object for the first feature; and sum, count, and avg, which are operators for the first feature. After identifying multiple feature event data where the data subject field in the feature event data format is specified as memberSrl, the device can identify the first feature event data 505 among the multiple feature event data where the data object field in the data format is specified as amount and the operator fields include sum, count, and avg.

[0088] As another example, the electronic device 100 can verify the storeId, which is the data subject for the second feature; the amount, which is the data object for the second feature; and the sum and count, which are operators for the second feature. After verifying multiple feature event data where the data subject field in the feature event data format is specified as storeId, it can then verify the second feature event data 506 among the multiple feature event data where the data object field in the data format is specified as amount and the operator fields include sum and count.

[0089] In this embodiment, the electronic device 100 can verify the data subject for the first feature, the data object for the first feature, and the operator for the first feature in order to verify the first feature event data, and can set a data query period corresponding to the customer's request information. After verifying multiple feature event data in which the data subject for the first feature is specified as the data subject field on the feature event data format, the device can verify the first feature event data selected from the verified multiple feature event data based on the set data query period, the data object for the first feature, and the operator for the first feature.

[0090] For example, in order to verify the first feature event data, the electronic device 100 can verify memberSrl, which is the data subject for the first feature, amount, which is the data object for the first feature, and sum, count, and avg, which are operators for the first feature, and can set the data query period corresponding to the customer's request information to the past 5 hours. After verifying multiple event data in the feature event data format in which the data subject field is specified as memberSrl, the electronic device 100 can verify the first feature event data 505 in which the data object field in the feature event data format is specified as amount, the operator fields include sum, count, and avg, and the time point specified in the time point field (trxTime) falls within the past 5 hours.

[0091] In one embodiment, the electronic device 100 can calculate feature event data and provide data statistics to the customer. Specifically, the electronic device 100 can provide the customer with information regarding the results of calculating the first feature event data based on the operators included in the operator fields of the feature event data. For example, the electronic device 100 can provide the customer with first statistical information 508 based on the sum operator and count operator included in the operator fields of the first feature event data 505. By providing statistical information related to the user, the electronic device 100 can enable the customer to determine the various activities of the user on the service. For example, the customer can use the statistical information provided by the electronic device 100 to check the stores and menus that the user prefers, according to the user's preferences and behavior, or further, the customer may use the statistical information to manage whether the user revisits the store or reorders the menu.

[0092] Figure 6 is an illustrative diagram showing a user interface in one embodiment that allows an administrator to set the features to be extracted. The electronic device 100 provides the administrator with a user interface as shown in Figure 6, and allows the administrator to input information about the features to be extracted.

[0093] Referring to Figure 6, the electronic device 100 allows the administrator to set filter conditions for event data through page 600 and set operation attributes such as operation functions corresponding to operators, subject fields, object fields, and object field value types. The administrator can enter one or more subjects in the subject field and one or more objects in the object field. Each feature determined based on such administrator input may be included in a feature management set, through which event data can be processed into feature event data.

[0094] Figure 7 is an illustrative diagram showing a user interface in one embodiment that allows an administrator to set fields for event data. The electronic device 100 provides the administrator with a user interface as shown in Figure 7, allowing the administrator to input information about the event data to be acquired.

[0095] Referring to Figure 7, the electronic device 100 allows the administrator to set data source attributes such as the name, type, and category of the data source from which event data is acquired via page 700, and to set the fields to be acquired from the data source, the field acquisition type, the field acquisition logic, etc. The fields included in the event data can be confirmed based on such administrator input, and the electronic device 100 can set the feature event data format based on at least some of the fields included in such event data.

[0096] The electronic device according to the above-described embodiment may include a processor, memory for storing and executing program data, permanent storage such as a disk drive, a communication port for communicating with external devices, and user interface devices such as a touch panel, keys, and buttons. A method embodied in a software module or algorithm may be stored on a computer-readable recording medium as computer-readable code or program instructions executable on the processor. Here, computer-readable recording media include magnetic storage media (e.g., ROM (read-only memory), RAM (random-access memory), floppy disks, hard disks, etc.) and optical reading media (e.g., CD-ROM, DVD (Digital Versatile Disc)). Computer-readable recording media may be distributed across a network of computer systems, and computer-readable code may be stored and executed in a distributed manner. The medium may be computer-readable, stored in memory, and executed by a processor.

[0097] This embodiment may be represented by a functional block configuration and various processing stages. Such functional blocks may be embodied by a variety of hardware and / or software configurations that perform specific functions. For example, the embodiment may employ integrated circuit configurations such as memory, processing, logic, look-up tables, etc., which can perform various functions under the control of one or more microprocessors or other control devices. Just as the components may be executed by software programming or software elements, this embodiment includes various algorithms embodied by data structures, processes, routines, or combinations of other programming configurations, which may be embodied in programming or scripting languages ​​such as C, C++, Java, assembler, etc. Functional aspects may be embodied by algorithms executed by one or more processors. Furthermore, this embodiment may employ prior art for electronic environment configuration, signal processing, and / or data processing, etc. The terms “mechanism,” “element,” “means,” and “configuration” may be used broadly and are not limited to mechanical and physical configurations. The terms may also include the meaning of a series of software processes (routines) in conjunction with processors, etc.

[0098] The embodiments described above are merely examples, and other embodiments may be realized within the scope of the claims described later.

Claims

1. A method for providing data statistics information for electronic devices, The steps include setting up a feature event data format for processing event data acquired in response to events confirmed on the service provided by the electronic device into feature event data corresponding to a feature, and a feature management set that includes one or more features, The steps include: configuring the service to process and manage event data on the service in accordance with the feature event data format into feature event data corresponding to each feature included in the feature management set; In response to customer request information related to data statistics, the step of checking the first feature event data corresponding to the first feature included in the request information from the feature management set, A method for providing data statistics information, comprising the step of providing data statistics information corresponding to the request information based on calculations performed on the first feature event data.

2. The aforementioned event is confirmed based on an action taken by a user of the service on the service. The method for providing data statistics information according to claim 1, wherein the event data includes data generated by the service in response to the action.

3. The aforementioned feature event data format includes one or more fields for feature event data, The data statistics information provision method according to claim 1, wherein the one or more fields are set based on at least some of the fields included in the event data.

4. The data statistics information provision method according to claim 3, wherein at least some of the fields are identified from among the fields of event data determined based on the input that sets the fields for event data.

5. The data statistics information provision method according to claim 3, wherein each feature included in the feature management set is determined based on an input that sets at least one field included in the one or more fields for each feature.

6. The method for providing data statistical information according to claim 3, wherein the one or more fields include a data subject field (subject field) that specifies the subject of the data and a data subject value field (subject value field) that specifies the data value corresponding to the data subject.

7. The method for providing data statistical information according to claim 3, wherein the one or more fields include a data object field (object field) that specifies a data object and a data object value field (object value field) that specifies a data value corresponding to the data object.

8. The data statistics information provision method according to claim 3, wherein the one or more fields include a feature identifier field for a feature identifier, an operator field for setting an operator to be used for data calculations, and a time field for the time when event data was acquired on the service.

9. The aforementioned method for providing data statistics information is: The step of checking one event data included in the aforementioned event data, The steps include: confirming one or more feature event data obtained by processing one of the aforementioned event data based on one or more features; The data statistics information provision method according to claim 1, further comprising the step of setting up information regarding mapping relationships for one event data and one or more feature event data.

10. The step of checking the first feature event data is: A step of identifying the data subject for the first feature, the data object for the first feature, and the operator for the first feature, The steps include: confirming a plurality of feature event data in which the data subject for the first feature is specified as a data subject field in the feature event data format; A method for providing data statistics information according to claim 1, comprising the step of confirming first feature event data selected from among the plurality of feature event data based on the data object for the first feature and the operator for the first feature.

11. The step of checking the first feature event data is: The step of setting a data inquiry period corresponding to the aforementioned request information, A method for providing data statistics information according to claim 10, comprising the step of confirming the first feature event data selected from the plurality of feature event data based on the data query period, the data object for the first feature, and the operator for the first feature.

12. The first feature event data is, A method for providing data statistics information according to claim 11, wherein a data object for the first feature is specified in the data object field on the feature event data format, an operator for the first feature is specified in the operator field on the feature event data format, and the feature event data includes feature event data in which the time point specified in the time point field on the feature event data format is included in the data query period.

13. The data statistics information provision method according to claim 1, wherein the data statistics information includes information relating to the results of calculating the first feature event data based on an operator for the first feature.

14. The aforementioned method for providing data statistics information is: The process further includes the step of obtaining the requested information from the customer, The requested information includes information about a feature group that includes multiple features for the customer, The first feature is included in the feature group, and the method for providing data statistical information according to claim 1.

15. The aforementioned method for providing data statistics information is: The data statistics information provision method according to claim 14, further comprising the step of adding the second feature to the feature management set if the second feature included in the feature group is not found in the feature management set.

16. The aforementioned method for providing data statistics information is: The method for providing data statistics information according to claim 14, further comprising the step of setting up a customer-specific feature management set containing the plurality of features in the feature management set in response to the customer, based on the fact that the plurality of features are included in the feature management set.

17. The aforementioned method for providing data statistics information is: The steps include reviewing the first customer-specific feature management set for the first customer and the second customer-specific feature management set for the second customer, The steps include: confirming the number of features common to the first customer-specific feature management set and the second customer-specific feature management set; The data statistics information provision method according to claim 16, further comprising the step of setting the first customer and the second customer as similar customer groups if both the first ratio of the number of common features to the number of features included in the first customer-specific feature management set and the second ratio of the number of common features to the number of features included in the second customer-specific feature management set are equal to or greater than a critical ratio.

18. An electronic device for providing data statistics information, Memory in which at least one program is stored, By executing at least one of the aforementioned programs, a feature management set is set up that includes a feature event data format for processing event data acquired in response to events confirmed on the service provided by the electronic device into feature event data corresponding to a feature, and one or more features. The service is configured to process and manage event data on the aforementioned service into feature event data corresponding to each feature included in the feature management set, according to the feature event data format. In response to customer request information related to data statistics, the first feature event data corresponding to the first feature included in the request information is checked from the feature management set, and, An electronic device including a processor that provides data statistics information corresponding to the request information based on calculations performed on the first feature event data.

19. A computer-readable non-temporary recording medium that stores a program for causing a computer to execute the data statistical information provision method described in claim 1.

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