Target object determination method and device, electronic equipment and storage medium
By using the logical operation method of binary arrays in data analysis, the target object is determined, and the problem of low large-scale data analysis speed is solved, achieving more efficient data analysis.
Patent Information
- Application Number
- CN202311395029.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-10-25
- Publication Date
- 2025-04-25
Smart Images
Figure CN119887252A_ABST
Abstract
Description
Technical Field
[0001] The present disclosure relates to the technical field of data analysis, and in particular to a target object determination method, device, electronic device and storage medium. Background Art
[0002] Data analysis refers to the use of appropriate statistical analysis methods to analyze a large amount of collected data, summarize, understand and digest them, in order to maximize the development of data functions and give full play to the role of data. Data analysis is the process of detailed study and summary of data in order to extract useful information and form conclusions.
[0003] In the actual data analysis process, users often need to perform single-dimensional or multi-dimensional analysis on data sets of hundreds of billions of data. In this case, due to the large scale of the data set, how to improve the data analysis rate is an urgent problem to be solved. Summary of the invention
[0004] In order to solve the above technical problem or at least partially solve the above technical problem, the present disclosure provides a target object determination method, device, electronic device and storage medium.
[0005] In a first aspect, the present disclosure provides a method for determining a target object, comprising:
[0006] Acquire a candidate object set and at least two target categories; the candidate object set includes multiple objects, each of which includes attribute information of multiple dimensions; any two of the target categories belong to different dimensions;
[0007] Determine a binary array of each target category respectively;
[0008] Performing a logical operation on all the binary arrays to obtain a logical operation result;
[0009] Based on the logic operation result, a target object is determined, where the target object is an object in the candidate object set and belongs to all the target categories.
[0010] In a second aspect, the present disclosure further provides a target object determination device, comprising:
[0011] An acquisition module, used to acquire a candidate object set and at least two target categories; the candidate object set includes multiple objects, each of which includes attribute information of multiple dimensions; any two of the target categories belong to different dimensions;
[0012] A first determination module, used to determine a binary array of each target category respectively;
[0013] An operation module, used for performing a logic operation on all the binary arrays to obtain a logic operation result;
[0014] The second determination module is used to determine a target object based on the logical operation result, where the target object is an object in the candidate object set and belongs to all the target categories.
[0015] In a third aspect, the present disclosure further provides an electronic device, the electronic device comprising:
[0016] one or more processors;
[0017] A storage device for storing one or more programs;
[0018] When the one or more programs are executed by the one or more processors, the one or more processors implement the target object determination method as described above.
[0019] In a fourth aspect, the present disclosure further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the target object determination method as described above.
[0020] Compared with the prior art, the technical solution provided by the embodiments of the present disclosure has the following advantages:
[0021] The technical solution provided by the embodiment of the present disclosure is to set a binary array to determine each target category respectively; perform a logical operation on all binary arrays to obtain a logical operation result; and determine the target object based on the logical operation result. The target object is an object in the candidate object set, and the target object belongs to all target categories. In essence, the target object is determined by performing a logical operation on the binary array, rather than by setting query conditions and matching the attributes of the object with the query conditions one by one. Since the rate at which electronic devices perform logical operations on binary arrays is much faster than matching the attributes of the object with the query conditions one by one. Therefore, the technical solution provided by the present application can increase the data analysis rate. BRIEF DESCRIPTION OF THE DRAWINGS
[0022] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.
[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.
[0024] Figure 1 A flowchart of a method for determining a target object provided by an embodiment of the present disclosure;
[0025] Figure 2 A schematic diagram of a target object determination method provided by an embodiment of the present disclosure;
[0026] Figure 3 is a structural schematic diagram of a target object determination device in an embodiment of the present disclosure;
[0027] Figure 4 It is a structural schematic diagram of an electronic device in an embodiment of the present disclosure. DETAILED DESCRIPTION
[0028] In order to more clearly understand the above-mentioned objectives, features and advantages of the present disclosure, the scheme of the present disclosure will be further described below. It should be noted that the embodiments of the present disclosure and the features in the embodiments can be combined with each other without conflict.
[0029] In the following description, many specific details are set forth to facilitate a full understanding of the present disclosure, but the present disclosure may also be implemented in other ways different from those described herein; it is obvious that the embodiments in the specification are only part of the embodiments of the present disclosure, rather than all of the embodiments.
[0030] Figure 1 This is a flow chart of a method for determining a target object provided by an embodiment of the present disclosure. This embodiment is applicable to the case where data analysis is performed in a client. This method can be performed by a target object determination device, which can be implemented in software and / or hardware. This device can be configured in an electronic device, such as a terminal, specifically including but not limited to a smart phone, a handheld computer, a tablet computer, a wearable device with a display screen, a desktop computer, a notebook computer, an all-in-one machine, a smart home device, etc. Alternatively, this embodiment is applicable to the case where data analysis is performed in a server. This method can be performed by a target object determination device, which can be implemented in software and / or hardware. This device can be configured in an electronic device, such as a server.
[0031] like Figure 1 As shown, the method may specifically include:
[0032] S110, obtaining a candidate object set and at least two target categories; the candidate object set includes multiple objects, each object includes attribute information of multiple dimensions; any two target categories belong to different dimensions.
[0033] The object is the subject of the analysis. In different scenarios, the object refers to different things. For example, in an e-commerce scenario, the e-commerce operation team wants to understand the distribution of the price dimension of the goods ordered during a certain promotion period. The object is the goods.
[0034] Each object has multiple attributes. The attributes of an object are different depending on what the object refers to. For example, if the object is a commodity, the attributes of the object may include the specific price of the object, the specific category to which the object belongs, the specific marketing activities that the object participates in (such as full-reduction activities, limited-time purchase activities), etc. The attribute information of an object is information used to describe the attributes of the object.
[0035] The dimension may be, for example, a category of an object attribute. For example, if the object is a commodity, the dimension may be price, category, marketing activities in which the object participates, and the like.
[0036] For example, product A is a women's dress, and its selling price is 15 yuan. Women's dress is the attribute information of product A in the category dimension, and 15 yuan is the attribute information of product A in the price dimension.
[0037] A candidate object set is a collection of objects that have not been processed or analyzed.
[0038] A category is a specific category or grouping. Under any dimension, by setting classification rules, multiple categories can be obtained under the dimension. For example, under the price dimension, multiple categories can be set, such as a price range of 0 yuan to 20 yuan, a price range of 21 yuan to 100 yuan, a price range of 101 yuan to 1,000 yuan, and a price range of more than 1,000 yuan.
[0039] The target category is the category that users are interested in and needs to be used for data analysis.
[0040] Any two target categories belonging to different dimensions means that when there are multiple target categories, each target category is a grouping result under a different dimension. For example, one target category is a price range of 0-20 yuan, and the other target category is women's clothing. The target category of the price range of 0-20 yuan belongs to the grouping result under the price dimension. The target category of women's clothing belongs to the grouping result under the category dimension.
[0041] The target object is an object in the candidate object set, and the target object belongs to all target categories.
[0042] S120 , respectively determine a binary array for each target category.
[0043] The binary array is used to reflect which objects in the candidate object set belong to the target category and which objects do not belong to the target category.
[0044] This application does not limit the specific setting method of the binary array of the target category.
[0045] In one embodiment, the candidate object set includes M objects; the binary array includes M bits; each bit corresponds to an object; in different binary arrays, the same bit corresponds to the same object; in the binary array, the value of the bit corresponding to the first category of objects is a first numerical value, and the value of the bit corresponding to the second category of objects is a second numerical value; the first category of objects are objects in the candidate object set that belong to the target category corresponding to the binary array, and the second category of objects are objects in the candidate object set that do not belong to the target category corresponding to the binary array.
[0046] Optionally, the first value is 1, and the second value is 0. Alternatively, the first value is 0, and the second value is 1.
[0047] For example, suppose the operation team wants to analyze the situation of products in the women's clothing category with a price range of 0-20 yuan sold on a certain e-commerce platform. The candidate object set includes all products sold on the e-commerce platform. There are two target categories, "women's clothing" and "0-20 yuan price range". The target objects are products in the women's clothing category with a price range of 0-20 yuan.
[0048] See also Figure 2 , assuming that the candidate object set includes 25 products (i.e., objects) in total, and the binary array is set to include 25 bits in total. In the binary array, the Qth bit represents the Qth product in the candidate object set. Q is a positive integer, and 1≤Q≤25.
[0049] If the first value is set to 1 and the second value is set to 0, assuming that among these 25 products, there are 17 products that belong to the target category of "women's clothing", including the 1st to 13th products in the candidate set, and the 22nd to 25th products. For the target category of "women's clothing", these 17 products are first-category objects. In the binary array corresponding to "women's clothing", the corresponding bit value of these 17 first-category objects is 1. Among these 25 products, there are 8 products that do not belong to the target category of "women's clothing", including the 14th to 21st products in the candidate set. For the target category of "women's clothing", these 8 products are second-category objects. In the binary array corresponding to "women's clothing", the corresponding bit value of these 8 second-category objects is 0. The final binary array of the target category of "women's clothing" is as follows: Figure 2 The first binary array is shown in .
[0050] If the first value is set to 1 and the second value is set to 0, assuming that among the 25 products, there are 10 products that belong to the target category of "0-20 yuan price range", including the 4th, 5th, 6th, 9th, 14th, 15th, 16th, 19th, 20th and 25th products in the candidate set. For the target category of "0-20 yuan price range", these 10 products are first-class objects. In the binary array corresponding to "0-20 yuan price range", the corresponding bit value of these 10 first-class objects is 1. Among the 25 products, there are 15 products that do not belong to the target category of "0-20 yuan price range", including the 1st to 3rd products, the 7th product, the 8th product, the 10th to 13th products, the 17th product, the 18th product, and the 21st to 24th products in the candidate set. For the target category "price range 0-20 yuan", these 15 products are second-class objects. In the binary array corresponding to "price range 0-20 yuan", the corresponding bit value of these 15 second-class objects is 0. The final binary array of the target category "price range 0-20 yuan" is as follows: Figure 2 The second binary array is shown in .
[0051] There are many implementation methods for this step, which are not limited in this application. Exemplarily, the implementation method for this step includes: obtaining a candidate array set; the candidate array set includes a correspondence between binary arrays and categories; and determining a binary array of each target category in the candidate array set.
[0052] The candidate array set is a summary result of binary arrays generated for the candidate object set in advance according to the attribute information of each object in the candidate object set. The candidate array set includes a plurality of correspondences between binary arrays and categories, and the categories in different correspondences are different.
[0053] Exemplarily, under the price dimension, four categories are set, such as the price range of 0-20 yuan, the price range of 21-100 yuan, the price range of 101-1000 yuan, and the price range of more than 1000 yuan. Under the category dimension, four categories are set, such as clothing, fresh food, daily necessities, and electronic products. Determine the binary array of each category separately, and determine a total of 8 binary arrays. These 8 binary arrays and their corresponding categories are added to the candidate array set as a corresponding relationship. Later, when performing data analysis, according to the purpose of analysis, directly query the binary array corresponding to the category to be analyzed.
[0054] By setting the binary array of each target category in the candidate array set, the process of obtaining the binary array from the candidate object set is actually advanced. When performing subsequent data analysis, the step of obtaining the binary array from the candidate object set is not temporarily executed according to the analysis purpose, but the previously obtained binary array is directly called, which can further shorten the time of data analysis.
[0055] S130, performing logical operations on all binary arrays to obtain logical operation results.
[0056] The logical operation may specifically include at least one of the following: an AND operation, an OR operation, and a NOT operation.
[0057] S140: Determine a target object based on the result of the logic operation, where the target object is an object in the candidate object set and belongs to all target categories.
[0058] Optionally, the implementation method of this step includes determining the target object based on the value of each bit in the logic operation result.
[0059] Exemplarily, if the first value is 1 and the second value is 0, S130 includes: performing an AND operation on all binary arrays to obtain a logic operation result; S140 includes: determining the object corresponding to the bit with a value of 1 in the logic operation result as the target object.
[0060] Alternatively, if the first value is 0 and the second value is 1, S130 includes: performing an OR operation on all binary arrays to obtain a logic operation result; S140 includes: determining the object corresponding to the bit with a value of 0 in the logic operation result as the target object.
[0061] For example, assuming that the first value is 1, the second value is 0, and the candidate object set is 25 objects. Figure 2 , the first binary array and the second binary array each include 25 bits. The first bit in the first binary array and the second binary array corresponds to the first object in the candidate object set, and the second bit in the first binary array and the second binary array corresponds to the second object in the candidate object set. The meanings of the remaining bits in the first binary array and the second binary array are similar.
[0062] The logical operation rule of the AND operation is: 1&1=1, 0&1=0, 1&0=0, 0&0=0. Wherein, "&" represents the operation symbol of the AND operation. Based on the logical operation rule of the AND operation, the AND operation is performed on the values of the same bit in the first binary array and the second binary array respectively. The operation result is as follows: Figure 2 See Figure 2, in the sum operation result, there are 5 bits with a value of 1, and the remaining bits have a value of 0. In the sum operation result, the objects represented by the bits with a value of 1 belong to both the target category corresponding to the first binary array and the target category corresponding to the second binary array, and are target objects.
[0063] The logical operation rules of the OR operation are: 1|1=1, 0|1=1, 1|0=1, 0|0=0. Among them, "|" represents the operation symbol of the OR operation. If the first value is 0 and the second value is 1, based on the logical operation rules of the OR operation, the values of the same bit in all binary arrays are respectively ORed. In the result of the OR operation, the object represented by the bit with a value of 0 belongs to both the target category corresponding to the first binary array and the target category corresponding to the second binary array, and is the target object.
[0064] The above technical solution sets a binary array to determine each target category respectively; performs a logical operation on all binary arrays to obtain a logical operation result; and determines a target object based on the logical operation result. The target object is an object in the candidate object set, and the target object belongs to all target categories. In essence, the target object is determined by performing a logical operation on the binary array, rather than by setting query conditions and matching the properties of the object with the query conditions one by one. Since the speed at which electronic devices perform logical operations on binary arrays is much faster than matching the properties of the object with the query conditions one by one, the technical solution provided by the present application can improve the data analysis rate.
[0065] The technical solution provided by this application is particularly suitable for data analysis scenarios with large data sets. Because the larger the data set, the longer it takes to match the attributes of the object with the query conditions one by one, and the method of performing logical operations on binary arrays can highlight its advantage of short time consumption.
[0066] On the basis of the above technical solutions, if a total of P target categories are obtained, logical operations are performed on all binary arrays to obtain logical operation results, including: obtaining historical operation results; if the historical operation results are logical operation results of part of the binary data in the target array set, logical operations are performed based on the historical operation results and candidate binary arrays to obtain logical operation results of all binary arrays; the target array set includes binary arrays corresponding to the P target categories respectively, and the target binary array is the binary data used to obtain the historical operation results; the target binary array belongs to the target array set, and the candidate binary array is the remaining binary array in the target array set except the target binary array; P is a positive integer greater than or equal to 3.
[0067] A total of P target categories are obtained, which means that P binary arrays will be formed in S120. The P binary arrays correspond to the P target categories one by one, and the target array set includes the P binary arrays.
[0068] Exemplarily, the target array set includes P binary arrays, namely m1, m2, ..., mj, m(j+1), ..., mp. If a sum operation is performed on all binary arrays, it can be expressed as Z:
[0069] Z=m1&m2&…&mj&m(j+1)&…&mp.
[0070] If the historical operation result is N, N = m1&m2&…&mj, then m1, m2,…, mj are all target binary arrays, and m(j+1),…, mp are candidate binary arrays. Then,
[0071] Z=N&m(j+1)&…&mp.
[0072] By setting the historical operation results as the logical operation results of part of the binary data in the target array set, logical operations are performed based on the historical operation results and the candidate binary arrays to obtain the logical operation results of all binary arrays. In essence, the historical operation results are fully utilized to obtain the logical operation results of all binary arrays to avoid repeated logical operations on the same binary array, so as to further improve the time consumption of determining the target object and increase the data analysis rate.
[0073] On the basis of the above technical solution, optionally, after S130, it also includes: storing the logic operation result and obtaining a binary array used for the logic operation result.
[0074] The logical operation results stored by the technical solution provided by this application will eventually be converted into historical operation results and applied to subsequent data analysis. Therefore, the purpose of this setting is to facilitate the subsequent implementation of "performing logical operations based on historical operation results and candidate binary arrays to obtain logical operation results of all binary arrays".
[0075] The technical solution provided by this application is further explained below with reference to specific examples.
[0076] Assume that the e-commerce operation team wants to understand the quantity distribution of women's clothing sold on the e-commerce platform in different price ranges. There are four price ranges, including the price range of 0-20 yuan, the price range of 21-100 yuan, the price range of 101-1000 yuan, and the price range of more than 1000 yuan. During the analysis process, the target object determination method provided by this application needs to be executed four times in total.
[0077] When the target object determination method provided by this application is executed for the first time, the candidate object set includes all the goods sold on the e-commerce platform. There are two target categories, namely "women's clothing" and "price in the range of 0-20 yuan". If m01 represents the binary array of "women's clothing" and m10 represents the binary array of "price in the range of 0-20 yuan", the target object is the goods that belong to both "women's clothing" and "price in the range of 0-20 yuan". If the first numerical value is 1 and the second numerical value is 0, the goods corresponding to the bits with a value of 1 in m01&m10 are the target objects. By counting the number of bits with a value of 1 in m01&m10, the number of goods that belong to both "women's clothing" and "price in the range of 0-20 yuan" can be obtained.
[0078] When the target object determination method provided by this application is executed for the second time, the candidate object set includes all the goods sold on the e-commerce platform. There are two target categories, namely "women's clothing" and "price range of 21 yuan to 100 yuan". If m01 represents the binary array of "women's clothing" and m20 represents the binary array of "price range of 21 yuan to 100 yuan", the target object is the goods that belong to both "women's clothing" and "price range of 21 yuan to 100 yuan". If the first numerical value is 1 and the second numerical value is 0, the goods corresponding to the bits with a value of 1 in m01 & m20 are the target objects. By counting the number of bits with a value of 1 in m01 & m20, the number of goods that belong to both "women's clothing" and "price range of 21 yuan to 100 yuan" can be obtained.
[0079] When the target object determination method provided in this application is executed for the third time, the candidate object set includes all the goods sold on the e-commerce platform. There are two target categories, namely "women's clothing" and "price range of 101 yuan to 1000 yuan". If m01 represents the binary array of "women's clothing" and m30 represents the binary array of "price range of 101 yuan to 1000 yuan", the target object is the goods that belong to both "women's clothing" and "price range of 101 yuan to 1000 yuan". If the first numerical value is 1 and the second numerical value is 0, the goods corresponding to the bits with a value of 1 in m01 & m30 are the target objects. By counting the number of bits with a value of 1 in m01 & m30, the number of goods that belong to both "women's clothing" and "price range of 101 yuan to 1000 yuan" can be obtained.
[0080] When the target object determination method provided by the present application is executed for the fourth time, the candidate object set includes all the goods sold on the e-commerce platform. There are two target categories, namely "women's clothing" and "price range above 1,000 yuan". If m01 represents the binary array of "women's clothing" and m40 represents the binary array of "price range above 1,000 yuan", the target object is the goods that belong to both "women's clothing" and "price range above 1,000 yuan". If the first numerical value is 1 and the second numerical value is 0, the goods corresponding to the bits with a value of 1 in m01 & m40 are the target objects. By counting the number of bits with a value of 1 in m01 & m40, the number of goods that belong to both "women's clothing" and "price range above 1,000 yuan" can be obtained.
[0081] After determining the number of products that are both "women's clothing" and "priced in the range of 0-20 yuan", the number of products that are both "women's clothing" and "priced in the range of 21 yuan-100 yuan", the number of products that are both "women's clothing" and "priced in the range of 101 yuan-1000 yuan", and the number of products that are both "women's clothing" and "priced in the range of more than 1000 yuan", we can obtain the distribution of the number of women's clothing products sold on e-commerce platforms in different price ranges.
[0082] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should know that the present invention is not limited by the described action sequence, because according to the present invention, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.
[0083] Figure 3 Schematic diagram of the structure of a target object determination device in an embodiment of the present disclosure. The target object determination device provided in the embodiment of the present disclosure can be configured in a client, or can be configured in a server. Figure 3 , the target object determination device specifically includes:
[0084] The acquisition module 310 is used to acquire a candidate object set and at least two target categories; the candidate object set includes multiple objects, each of which includes attribute information of multiple dimensions; any two target categories belong to different dimensions;
[0085] A first determination module 320, configured to respectively determine a binary array of each of the target categories;
[0086] An operation module 330 is used to perform a logic operation on all the binary arrays to obtain a logic operation result;
[0087] The second determination module 340 is used to determine a target object based on the logic operation result, where the target object is an object in the candidate object set and belongs to all the target categories.
[0088] Furthermore, the candidate object set includes M objects; the binary array includes M bits; each bit corresponds to an object; in different binary arrays, the same bit corresponds to the same object;
[0089] In the binary array, the value of the bit corresponding to the first category of objects is a first numerical value, and the value of the bit corresponding to the second category of objects is a second numerical value; the first category of objects are objects in the alternative object set that belong to the target category corresponding to the binary array, and the second category of objects are objects in the alternative object set that do not belong to the target category corresponding to the binary array.
[0090] Further, the second determining module 340 is used to:
[0091] The target object is determined based on the value of each bit in the logic operation result.
[0092] Further, if the first value is 1 and the second value is 0, the second determination module 340 is configured to:
[0093] Performing an AND operation on all the binary arrays to obtain a logic operation result; determining the object corresponding to the bit with a value of 1 in the logic operation result as the target object;
[0094] If the first value is 0 and the second value is 1, the second determination module 340 is used to:
[0095] Perform an OR operation on all the binary arrays to obtain a logic operation result; and determine the object corresponding to the bit with a value of 0 in the logic operation result as the target object.
[0096] Furthermore, if a total of P target categories are obtained, the second determination module 340 is used to:
[0097] Get historical calculation results;
[0098] If the historical operation result is a logical operation result of part of the binary data in the target array set, a logical operation is performed based on the historical operation result and the candidate binary array to obtain the logical operation result of all the binary arrays; the target array set includes binary arrays corresponding to P target categories respectively, and the target binary array is the binary data used to obtain the historical operation result; the target binary array belongs to the target array set, and the candidate binary array is the remaining binary arrays in the target array set except the target binary array; P is a positive integer greater than or equal to 3.
[0099] Furthermore, the device also includes a storage module, which is used to perform logical operations on all the binary arrays, and after obtaining the logical operation results, store the logical operation results and the binary arrays used to obtain the logical operation results.
[0100] Further, the first determining module 320 is used to:
[0101] Obtain a candidate array set; the candidate array set includes a correspondence between binary arrays and categories;
[0102] In the candidate array set, a binary array of each target category is determined.
[0103] The target object determination device provided in the embodiment of the present disclosure can execute the steps executed by the client or server in the target object determination method provided in the embodiment of the method of the present disclosure, and has execution steps and beneficial effects, which will not be repeated here.
[0104] Figure 4 Schematic diagram of the structure of an electronic device in the embodiment of the present disclosure. Figure 4 , which shows a schematic diagram of the structure of an electronic device 1000 suitable for implementing the embodiment of the present disclosure. The electronic device 1000 in the embodiment of the present disclosure may include but is not limited to mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle terminals (such as vehicle navigation terminals), wearable electronic devices, etc., and fixed terminals such as digital TVs, desktop computers, smart home devices, etc. Figure 4 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.
[0105] like Figure 4 As shown, the electronic device 1000 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 1001, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1008 to a random access memory (RAM) 1003 to implement the target object determination method of the embodiment described in the present disclosure. In the RAM 1003, various programs and information required for the operation of the electronic device 1000 are also stored. The processing device 1001, the ROM 1002, and the RAM 1003 are connected to each other via a bus 1004. An input / output (I / O) interface 1005 is also connected to the bus 1004.
[0106] Typically, the following devices may be connected to the I / O interface 1005: input devices 1006 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; output devices 1007 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1008 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication devices 1009 may allow the electronic device 1000 to communicate with other devices wirelessly or by wire to exchange information. Although Figure 4 The electronic device 1000 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead.
[0107] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program contains a program code for executing the method shown in the flowchart, thereby implementing the target object determination method as described above. In such an embodiment, the computer program can be downloaded and installed from the network through the communication device 1009, or installed from the storage device 1008, or installed from the ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment of the present disclosure are executed.
[0108] It should be noted that the computer-readable medium mentioned above in the present disclosure may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present disclosure, a computer-readable signal medium may include an information signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated information signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.
[0109] In some embodiments, the client and the server may communicate using any known or future developed network protocol such as HTTP (HyperText Transfer Protocol), and may be interconnected with any form or medium of digital information communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any known or future developed network.
[0110] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.
[0111] The computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device:
[0112] Acquire a candidate object set and at least two target categories; the candidate object set includes multiple objects, each of which includes attribute information of multiple dimensions; any two of the target categories belong to different dimensions;
[0113] Determine a binary array of each target category respectively;
[0114] Performing a logical operation on all the binary arrays to obtain a logical operation result;
[0115] Based on the logic operation result, a target object is determined, where the target object is an object in the candidate object set and belongs to all the target categories.
[0116] Optionally, when the above one or more programs are executed by the electronic device, the electronic device may also execute other steps described in the above embodiments.
[0117] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages or a combination thereof, including, but not limited to, object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).
[0118] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.
[0119] The units involved in the embodiments described in the present disclosure may be implemented by software or hardware, wherein the name of a unit does not, in some cases, limit the unit itself.
[0120] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.
[0121] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
[0122] According to one or more embodiments of the present disclosure, the present disclosure provides an electronic device, including:
[0123] one or more processors;
[0124] A memory for storing one or more programs;
[0125] When the one or more programs are executed by the one or more processors, the one or more processors implement any target object determination method provided in the present disclosure.
[0126] According to one or more embodiments of the present disclosure, the present disclosure provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any target object determination method provided by the present disclosure.
[0127] The embodiment of the present disclosure further provides a computer program product, which includes a computer program or instructions, and when the computer program or instructions are executed by a processor, the target object determination method as described above is implemented.
[0128] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.
[0129] The above description is only a specific embodiment of the present disclosure, so that those skilled in the art can understand or implement the present disclosure. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure will not be limited to the embodiments described herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.
Claims
1. A method for determining a target object, characterized in that: include: Obtain a candidate object set and at least two target categories; The candidate object set includes a plurality of objects, each of which includes attribute information of multiple dimensions; Any two of the target categories belong to different dimensions; Determine a binary array of each target category respectively; Performing a logical operation on all the binary arrays to obtain a logical operation result; Based on the logic operation result, a target object is determined, where the target object is an object in the candidate object set and belongs to all the target categories.
2. The method according to claim 1, characterized in that The candidate object set includes M objects; the binary array includes M bits; each bit corresponds to an object; in different binary arrays, the same bit corresponds to the same object; In the binary array, the value of the bit corresponding to the first category of objects is a first numerical value, and the value of the bit corresponding to the second category of objects is a second numerical value; the first category of objects are objects in the alternative object set that belong to the target category corresponding to the binary array, and the second category of objects are objects in the alternative object set that do not belong to the target category corresponding to the binary array.
3. The method according to claim 2, characterized in that The determining the target object based on the logical operation result includes: The target object is determined based on the value of each bit in the logic operation result.
4. The method according to claim 3, characterized in that: If the first value is 1 and the second value is 0, performing a logical operation on all the binary arrays to obtain a logical operation result includes: performing an AND operation on all the binary arrays to obtain a logical operation result; The determining the target object based on the value of each bit in the logic operation result includes: determining the object corresponding to the bit with a value of 1 in the logic operation result as the target object; If the first numerical value is 0 and the second numerical value is 1, performing a logical operation on all the binary arrays to obtain a logical operation result includes: performing an OR operation on all the binary arrays to obtain a logical operation result; determining the target object based on the numerical value of each bit in the logical operation result includes: determining the object corresponding to the bit with a numerical value of 0 in the logical operation result as the target object.
5. The method according to claim 1, characterized in that If a total of P target categories are obtained, the logic operation is performed on all the binary arrays to obtain the logic operation results, including: Get historical calculation results; If the historical operation result is a logical operation result of part of the binary data in the target array set, a logical operation is performed based on the historical operation result and the candidate binary array to obtain the logical operation result of all the binary arrays; the target array set includes binary arrays corresponding to P target categories respectively, and the target binary array is the binary data used to obtain the historical operation result; the target binary array belongs to the target array set, and the candidate binary array is the remaining binary arrays in the target array set except the target binary array; P is a positive integer greater than or equal to 3.
6. The method according to claim 1, characterized in that After performing logical operations on all the binary arrays to obtain logical operation results, the method further includes: The logic operation result is stored and a binary array used to obtain the logic operation result is obtained.
7. The method according to claim 1, characterized in that The step of respectively determining a binary array of each target category includes: Obtain a candidate array set; the candidate array set includes a correspondence between binary arrays and categories; In the candidate array set, a binary array of each target category is determined.
8. A target object determination device, characterized in that: include: An acquisition module, used to acquire a candidate object set and at least two target categories; The candidate object set includes a plurality of objects, each of which includes attribute information of multiple dimensions; Any two of the target categories belong to different dimensions; A first determination module, used to determine a binary array of each target category respectively; An operation module, used for performing a logic operation on all the binary arrays to obtain a logic operation result; The second determination module is used to determine a target object based on the logical operation result, where the target object is an object in the candidate object set and belongs to all the target categories.
9. An electronic device, characterized in that: The electronic device comprises: one or more processors; A storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 7.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.