Method for acquiring object features and related equipment

Abstract

The invention provides a method for acquiring object features and related equipment. The method comprises the following steps: acquiring object information of an object; calculating a query identifier corresponding to the object information based on the object information according to a preset algorithm; wherein the object information and the query identifier are in one-to-one correspondence; obtaining feature data corresponding to the object information according to the query identifier; and in response to the situation that the feature data corresponding to the object information cannot be obtained according to the query identifier, calculating the feature data of the object information, and associating and storing the calculated feature data and the query identifier.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular to a method for acquiring object features and related equipment. Background Art

[0002] In the field of computer technology, object features can be used to process and analyze object information. In related technologies, using features to complete processing and analysis can improve efficiency.

[0003] However, the inventors of the present disclosure have discovered that different objects may have the same object information. If feature calculations are performed multiple times on the same object information due to different reasons for the objects, it is easy to cause a waste of computing resources. Summary of the invention

[0004] The present disclosure proposes a method for acquiring object features and related devices to solve or partially solve the above problems.

[0005] In a first aspect of the present disclosure, a method for acquiring object features is provided, comprising:

[0006] Get object information of an object;

[0007] According to a preset algorithm, based on the object information, a query identifier corresponding to the object information is calculated; wherein the object information and the query identifier are in one-to-one correspondence;

[0008] Acquire feature data corresponding to the object information according to the query identifier;

[0009] In response to the inability to obtain the feature data corresponding to the object information according to the query identifier, the feature data of the object information is calculated, and the calculated feature data is associated with the query identifier and stored.

[0010] In a second aspect of the present disclosure, a device for acquiring object features is provided, comprising:

[0011] The first acquisition module is configured to: acquire object information of an object;

[0012] A calculation module is configured to: calculate a query identifier corresponding to the object information based on the object information according to a preset algorithm; wherein the object information and the query identifier are in one-to-one correspondence;

[0013] A second acquisition module is configured to: acquire feature data corresponding to the object information according to the query identifier;

[0014] The calculation and storage module is configured to: in response to being unable to obtain the feature data corresponding to the object information according to the query identifier, calculate the feature data of the object information, and associate and store the calculated feature data with the query identifier.

[0015] In a third aspect of the present disclosure, a computer device is provided, comprising one or more processors, a memory; and one or more programs, wherein the one or more programs are stored in the memory and executed by the one or more processors, and the programs include instructions for executing the method described in the first aspect.

[0016] According to a fourth aspect of the present disclosure, a non-volatile computer-readable storage medium containing a computer program is provided. When the computer program is executed by one or more processors, the processors execute the method described in the first aspect.

[0017] In a fifth aspect of the present disclosure, a computer program product is provided, comprising computer program instructions, which, when executed on a computer, cause the computer to execute the method described in the first aspect.

[0018] The method and related equipment for obtaining object features provided by the embodiments of the present disclosure calculate the query identifier of the object information according to a preset algorithm, and first obtain the feature data based on the query identifier, and calculate the feature data when the feature data cannot be obtained, which can save a lot of computing resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the present disclosure or related technologies, the drawings required for use in the embodiments or related technical descriptions are briefly introduced below. Obviously, the drawings described below are only embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0020] Figure 1 A schematic diagram showing an exemplary system provided by an embodiment of the present disclosure is shown.

[0021] Figure 2A A schematic diagram showing another exemplary system provided by an embodiment of the present disclosure is shown.

[0022] Figure 2B A schematic diagram of a detail page of an exemplary object according to an embodiment of the present disclosure is shown.

[0023] Figure 3 A flowchart of an exemplary method provided by an embodiment of the present disclosure is shown.

[0024] Figure 4A schematic diagram of an exemplary device provided by an embodiment of the present disclosure is shown.

[0025] Figure 5 A schematic diagram of the hardware structure of an exemplary computer device provided in an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0026] In order to make the objectives, technical solutions and advantages of the present disclosure more clearly understood, the present disclosure is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings.

[0027] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present disclosure should be understood by people with ordinary skills in the field to which the present disclosure belongs. The "first", "second" and similar words used in the embodiments of the present disclosure do not indicate any order, quantity or importance, but are only used to distinguish different components. "Including" or "comprising" and similar words mean that the elements or objects appearing before the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0028] It is understandable that before using the technical solutions of each embodiment of the present disclosure, the type, scope of use, usage scenarios, etc. of the personal information involved will be informed to the user in an appropriate manner, and the user's authorization will be obtained.

[0029] For example, in response to receiving an active request from a user, a prompt message is sent to the user to clearly remind the user that the operation requested to be performed will require obtaining and using the user's personal information. Thus, the user can independently choose whether to provide personal information to software or hardware such as an electronic device, application, server, or storage medium that performs the operation of the technical solution of the present disclosure according to the prompt message.

[0030] As an optional but non-limiting implementation, in response to receiving the user's active request, the prompt information may be sent to the user in the form of a pop-up window, in which the prompt information may be presented in text form. In addition, the pop-up window may also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0031] It is understandable that the above notification and the process of obtaining user authorization are merely illustrative and do not constitute a limitation on the implementation of the present disclosure. Other methods that meet relevant laws and regulations may also be applied to the implementation of the present disclosure.

[0032] Figure 1 A schematic diagram of an exemplary system 100 provided by an embodiment of the present disclosure is shown.

[0033] like Figure 1 As shown, the system 100 may include a terminal device 102, a terminal device 104, a server 106, and a database server 108. A medium (e.g., a network) providing a communication link may be included between the terminal device 102, the terminal device 104 and the server 106 and the database server 108. The network may include various connection types, such as wired, wireless communication links, or optical fiber cables, etc.

[0034] Exemplarily, various applications (APPs) may be installed on the terminal device 104, such as life service applications, collaborative office applications, video conferencing applications, reading applications, video applications, social applications, payment applications, web browsers, and instant messaging tools.

[0035] The terminal device 102 and the terminal device 104 here can be hardware or software. When the terminal device 102 and the terminal device 104 are hardware, they can be various electronic devices with display screens, including but not limited to smart phones, tablet computers, e-book readers, MP3 players, laptop computers (Laptops) and desktop computers (PCs), etc. When the terminal device 102 and the terminal device 104 are software, they can be installed in the electronic devices listed above. It can be implemented as multiple software or software modules (for example, to provide distributed services), or it can be implemented as a single software or software module. No specific limitation is made here.

[0036] The server 106 may be a server that provides various services, such as a background server that provides support for various applications displayed on the terminal devices 102 and 104. The database server 108 may also be a database server that provides various services. It is understood that if the server 106 can implement the relevant functions of the database server 108, the database server 108 may not be set in the system 100.

[0037] Here, the server 106 and the database server 108 can also be hardware or software. When they are hardware, they can be implemented as a distributed server cluster consisting of multiple servers, or as a single server. When they are software, they can be implemented as multiple software or software modules (for example, for providing distributed services), or as a single software or software module. No specific limitation is made here.

[0038] It should be noted that the information generation method provided in the embodiment of the present disclosure may be executed by the terminal device 102 and / or the terminal device 104. It should be understood that Figure 1 The number of terminal devices, users, servers and database servers in the embodiment is only for illustration. Any number of terminal devices, users, servers and database servers may be provided as required.

[0039] In some embodiments, a life service application or software may be installed in the terminal device 104, and the user 112 may use the application or software to obtain services related to food, clothing, housing and transportation, such as shopping.

[0040] As an exemplary scenario, the user 112 can use the life service application of the terminal device 104 to shop, for example, by providing a product picture to find similar products. Exemplarily, the terminal device 104 uploads the product picture to the server 106, and the server 106 can calculate features based on the product picture, and then find products similar to the product picture by feature comparison.

[0041] Due to the large number of commodities, if the features of each commodity are calculated in real time and then compared with the features of the commodity images, the real-time calculation pressure will be significantly increased. In some embodiments, a feature library can be built for the features of each commodity. Exemplarily, the user 110 can use the terminal device 102 to send a request to create a feature library to the server 106, so that the server 106 creates a feature library based on the request and stores the feature library in the database server 108. The request can include the range of objects used to create the feature library, for example, a certain type of object (e.g., footwear).

[0042] After creating the feature library, you can use the features of the product images to compare with the product features in the feature library to find similar products.

[0043] It is understandable that such a feature library creation method requires relatively large computing resources and storage resources.

[0044] The inventors of the present disclosure have discovered that, since there are many merchants on the shopping platform, the same product may be sold by multiple stores, and the product sales link (or product sales page) corresponding to each store corresponds to an object identifier (PID). In other words, substantially the same product (for example, the same book) may correspond to multiple PIDs. Thus, when creating a feature library using product features, in order to distinguish products from different stores, the product features are usually calculated based on the product information corresponding to the PID (for example, product sales links, product sales pages, etc.), and then a feature library is created based on the calculated product features. Since the product information corresponding to different PIDs of the same product has a high degree of repetition (for example, the same picture and / or the same text description, etc.), if feature calculations are performed separately for the product information corresponding to each PID, there will be a lot of calculation duplication and redundancy, consuming unnecessary computing resources.

[0045] In view of this, an embodiment of the present disclosure provides a method for acquiring object features to solve or partially solve the above problems.

[0046] Figure 2A FIG. 2 is a schematic diagram of an exemplary system 200 provided by an embodiment of the present disclosure. The system 200 may be used to obtain object features and store object features. Optionally, the system 200 may be implemented as Figure 1 The server 106 may be implemented as Figure 1 The server 106 and the database server 108 are connected.

[0047] In the initial state, it may be necessary to create a feature library for an object (e.g., a commodity) so as to process and analyze the object based on the object features. As an optional implementation scenario, a feature library may be created for a certain type of object (e.g., a dress), and the object identifier (PID) of all objects of this type may be obtained. The server 106 may generate a feature calculation request for each object, and the request may carry the object identifier 2022 of the object.

[0048] like Figure 2A As shown, in some embodiments, the first service 202 may obtain the attribute information of the object based on the object identifier 2022. Optionally, the first service 202 may be a product packaging service, which is used to obtain basic attribute information of the product based on the PID, such as the uniform resource locator system (URL) address of the image contained in the product sales page, the title of the product (e.g., "XX fairy-like holiday style dress autumn new style slimming"), the text in the product sales page (e.g., the description text of the product), and the like.

[0049] After the attribute information of the object is acquired, the object information of the object may be acquired according to the attribute information.

[0050] Optionally, the text in the commodity sales page may be directly used as the object information of the object to calculate the text features of the object.

[0051] For the URL address of the picture included in the commodity sales page, the picture information corresponding to the URL address can be requested from the second service 204 based on the URL address. Optionally, the second service 204 can be a picture download service, and the picture information can be binary information of the picture.

[0052] After obtaining the object information (e.g., text, image information) of the object, the object information may be sent to the third service 206 for processing. Optionally, according to different requirements, image information, text information and / or multimodal data containing both image information and text information may be provided as object information to the third service 206 to meet the requirements of different scenarios.

[0053] In some cases, the third service 206 may first determine a query identifier corresponding to the object information. The query identifier may be used to query existing features in the feature library. Alternatively, for a database that uses key-value pairs to implement data query, the query identifier may be a key, and may be a primary key of the data.

[0054] In some embodiments, when the object information is picture information used to describe the object, the query identifier corresponding to the object information can be calculated based on the picture information according to a preset algorithm.

[0055] The preset algorithm can be any algorithm, and can calculate a unique result based on the image information, so that the image information corresponds to the query identifier one by one. In this way, when searching for feature data corresponding to the image information in the feature library based on the query identifier, the unique feature data corresponding to the image information can be found.

[0056] In some embodiments, the preset algorithm can be an encryption algorithm. In this way, a commonly used encryption algorithm can be used to calculate a unique information similar to a private key based on the image information as a query identifier. On the one hand, the uniqueness of the query identifier is guaranteed. On the other hand, the existing encryption algorithm is used to avoid the need for algorithm design, thereby improving efficiency.

[0057] Optionally, the encryption algorithm may be, for example, the message digest algorithm MD5, so that MD5 may be used to implement fast calculation of the query identifier, and the lengths of the query identifiers obtained based on the MD5 algorithm are all the same, which is conducive to ensuring the consistency of the query identifier.

[0058] It can be understood that in some embodiments, when the object information is text information or multimodal data used to describe the object, the above-mentioned embodiment can also be used to calculate the query identifier, which will not be described in detail here.

[0059] In some embodiments, the object includes a product, and the object information is text information for describing the product (e.g., the product title, text information on the details page, etc.). The third service 206 can extract the product title corresponding to the product from the text information as the query identifier according to a preset algorithm. Optionally, the preset algorithm can identify the identifier corresponding to the product title in the text information, and then extract the product title from the text information as the query identifier based on the identifier.

[0060] Different from using encryption algorithms to calculate the query identifier, using the extracted product title as the query identifier of the text feature corresponding to the text information can save the calculation process and further save computing resources. In addition, the title of the product is usually long and contains the brand name (for example, "XX brand fairy-like holiday style long dress autumn new style slim and versatile"), which is usually unique and easy to obtain. In some cases, if the uniqueness of the product title cannot be guaranteed, other text information of the object obtained from the first service 202 can be added to the query identifier to be used as the query identifier together with the product title.

[0061] For multimodal data, the query identifiers corresponding to the image information and text information therein may be concatenated together as the query identifier corresponding to the multimodal data.

[0062] In this way, a one-to-one correspondence between object information and query identifier is established.

[0063] Next, the third service 206 may obtain the feature data corresponding to the object information according to the query identifier. For example, the feature data corresponding to the object information may be obtained from the feature library 212 based on the query identifier. Alternatively, for a database that uses key-value pairs to implement data query, the value obtained based on the query identifier (key) may be the corresponding feature data.

[0064] It can be understood that in the initial state, there may not be any feature data in the feature library 212, so the feature data corresponding to the object information cannot be obtained according to the query identifier. At this time, the third service 206 can call the model reasoning service to calculate the feature data of the object information, for example, calling the feature calculation model 216 of the model reasoning service to calculate the feature data of the object information. Optionally, if the object information is image information, the image feature can be calculated based on the image information, if the object information is text information, the text feature can be calculated based on the text information, and if the object information is multimodal data, the multimodal feature can be calculated based on the multimodal data.

[0065] In some embodiments, if the object is a commodity, the object information includes multiple object information corresponding to the object, the feature data includes multiple feature data corresponding to the multiple object information, and the query identifier includes multiple query identifiers corresponding to the multiple object information.

[0066] Figure 2B A schematic diagram of an exemplary object detail page 220 according to an embodiment of the present disclosure is shown.

[0067] like Figure 2B As shown, for example, a single object may include pictures 222 to 226 and text 228. Picture 222 may be a header picture, and there may be multiple pictures. The user may switch header pictures by sliding gestures. Therefore, the pictures included in the object may not only be Figure 2B Pictures 222 to 226 are shown in FIG.

[0068] In some embodiments, an image feature and a query identifier can be calculated based on the image information corresponding to each image, so that the same object can have multiple image features and multiple query identifiers. In addition, a text feature can be calculated based on text information, and the text information can also correspond to a query identifier. In addition, a multimodal feature can be calculated based on the multimodal data of the image information and text information of all images, and the multimodal data can also correspond to a query identifier. In this way, for the same object, multiple object information, multiple feature data, and multiple query identifiers can be obtained.

[0069] After the characteristic data is calculated, the calculated characteristic data may be associated with the query identifier and stored in a characteristic library.

[0070] Optionally, the calculated feature data and the query identifier associated therewith may be stored in a table, and then the table may be provided to the feature storage service 210 for storage.

[0071] In some embodiments, the image features and query identifiers corresponding to the individual image information and the text features and query identifiers corresponding to the individual text information can be stored in the first storage module (or first feature library) 212, so that the corresponding image features or text features can be queried from the first storage module 212 for the individual image information or the individual text information. Therefore, each row of data in the table can be split to obtain information with features and query identifiers as key-value pairs, and stored in the first storage module 212. The first feature library created in the first storage module 212 can be used as a cache library for the feature operator of the third service 206 in the future, so that it can obtain feature data based on the query identifier, reduce the repeated calls of the model reasoning service, and thus reduce the pressure of the model reasoning service. In addition, since the image features of the individual image information are stored separately and the text features are also stored separately, when the query identifiers are the same, the corresponding image features or text features can be found from the first storage module 212, without the need to repeatedly store the same image features or text features, thereby reducing resource waste.

[0072] In some embodiments, Figure 2A As shown, the feature storage service 210 can also associate the multiple feature data corresponding to the object with the object identifier (PID) of the object and store them in the second storage module 214 (or the second feature library). In this way, in some scenarios, the user can still query the feature data corresponding to the object based on the object identifier.

[0073] At this point, the feature data of the first object has been stored in the database. When the next request comes, the above steps can be executed again. When the third service 206 can obtain the feature data corresponding to the object information according to the query identifier, since the first storage module 212 has already stored data at this time, in some cases, for example, the query identifier corresponding to a single image can find the corresponding image feature in the first storage module 212, the third service 206 records the image feature and can no longer call the feature calculation model 216 to repeatedly calculate the image feature. For object information for which feature data cannot be found, the feature calculation model 216 can still be called to calculate the feature data.

[0074] In this way, when the feature data corresponding to all the object information of the second object are obtained (queried or calculated), the third service 206 can provide the table of query identifiers and feature data to the feature storage service 210 for feature storage. The feature data obtained by the query in the table can be marked as 1, so that the feature storage service 210 can no longer store the feature data, and the feature data marked as 0 can be stored in the first storage module 212. Optionally, the multiple feature data corresponding to the second object can also be associated with the object identifier (PID) of the object and stored in the second storage module 214.

[0075] In this way, the aforementioned steps are repeated to process the data of the next object until the features of all objects are acquired and stored in the feature library, and the building of the feature library is completed. Subsequently, the created feature library can be used to acquire the object features, so that when completing some real-time tasks, the real-time tasks can be completed based on the queried features. When the features cannot be queried, the feature calculation model can be called for real-time calculation to ensure the effective completion of the real-time tasks. It can be understood that the way of acquiring the object features when executing the real-time tasks is similar to the steps of the aforementioned embodiment, and will not be repeated here.

[0076] In some embodiments, the data stored in the first storage module 212 may be deleted or cleaned up based on an expiration automatic deletion mechanism (Time to Live, TTL for short) to ensure the timeliness of the data and save storage resources.

[0077] In some embodiments, data stored in the second storage module 214 can be deleted or cleaned based on an automatic expiration deletion mechanism (Time to Live, TTL for short), or can be explicitly deleted by specifying a query identifier to ensure the timeliness of the data and save storage resources.

[0078] In some embodiments, in addition to creating a feature library or completing real-time tasks, when the feature calculation model is updated (for example, the algorithm itself is updated, the model parameters are updated, etc.), the aforementioned method also needs to be triggered to update the feature library. Specifically, the feature data of the object information can be re-determined based on the updated feature calculation model, and then the feature data of the object information that has been stored can be replaced with the re-determined feature data of the object information. It can be understood that in this process, since the feature data may be repeated, a large amount of computing resources can still be saved.

[0079] It can be seen from the above embodiments that the method for obtaining object features provided by the embodiments of the present disclosure, by determining the query identifier of the object information and first obtaining the feature data based on the query identifier, and only calculating the feature data when the feature data cannot be obtained, can greatly reduce the repeated calculation of some features, and can save a lot of computing resources, especially reducing the computing amount of the graphics processing unit (GPU), and improving the feature calculation efficiency.

[0080] It should be noted that the method of the embodiment of the present disclosure can be performed by a single device, such as a computer or a server. The method of the present embodiment can also be applied in a distributed scenario and completed by multiple devices cooperating with each other. In the case of such a distributed scenario, one of the multiple devices can only perform one or more steps in the method of the embodiment of the present disclosure, and the multiple devices will interact with each other to complete the described method.

[0081] It should be noted that the above describes some embodiments of the present disclosure. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the above embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0082] The disclosed embodiment also provides a method for acquiring object features. Figure 3 FIG. 2 is a flow chart of an exemplary method 300 provided by an embodiment of the present disclosure. The method 300 may be implemented by the system 200 of FIG. 2 , such as Figure 3 As shown, the method 300 may include the following steps.

[0083] In step 302, object information of an object may be acquired. Optionally, the object information includes at least one of picture information, text information, and multimodal data for describing the object.

[0084] In step 304, a query identifier corresponding to the object information is calculated based on the object information according to a preset algorithm; wherein the object information and the query identifier are in one-to-one correspondence.

[0085] In step 306, feature data corresponding to the object information is acquired according to the query identifier.

[0086] In step 308, in response to failure to obtain feature data corresponding to the object information according to the query identifier, the feature data of the object information is calculated, and the calculated feature data is associated with the query identifier and stored.

[0087] It can be seen from the above embodiments that the method for obtaining object features provided by the embodiments of the present disclosure calculates the query identifier of the object information according to a preset algorithm, and first obtains the feature data based on the query identifier, and only calculates the feature data when the feature data cannot be obtained. This can greatly reduce the repeated calculation of some features and can save a lot of computing resources, especially reducing the computing power of the graphics processing unit (GPU) and improving the feature calculation efficiency.

[0088] In some embodiments, the object information is picture information used to describe the object, and the preset algorithm is an encryption algorithm. In this way, a common encryption algorithm can be used to calculate a unique information similar to a private key based on the picture information as a query identifier, which ensures the uniqueness of the query identifier on the one hand, and on the other hand, the existing encryption algorithm is used, so that the algorithm design does not need to be performed, thereby improving efficiency.

[0089] Optionally, the encryption algorithm may be, for example, the message digest algorithm MD5, so that MD5 may be used to implement fast calculation of the query identifier, and the lengths of the query identifiers obtained based on the MD5 algorithm are all the same, which is conducive to ensuring the consistency of the query identifier.

[0090] In some embodiments, the object includes a commodity, and the object information is text information for describing the commodity;

[0091] Calculating a query identifier corresponding to the object information based on the object information according to a preset algorithm includes:

[0092] According to a preset algorithm, the product title corresponding to the product is extracted from the text as the query identifier.

[0093] Different from using encryption algorithms to calculate the query identifier, using the extracted product title as the query identifier of the text feature corresponding to the text information can save the calculation process and further save computing resources. In addition, the title of the product is usually long and contains the brand name (for example, "XX brand fairy-like holiday style long dress autumn new style slim and versatile"), which is usually unique and easy to obtain. In some cases, if the uniqueness of the product title cannot be guaranteed, other text information of the object obtained from the first service 202 can be added to the query identifier to be used as the query identifier together with the product title.

[0094] In some embodiments, obtaining object information of an object includes:

[0095] Obtaining an object identifier of the object;

[0096] Acquire attribute information of the object according to the object identifier;

[0097] The object information of the object is acquired according to the attribute information.

[0098] In this way, attribute information can be obtained based on the object identification to determine the object information used to calculate the feature.

[0099] In some embodiments, the object information includes multiple pieces of object information corresponding to the object, the feature data includes multiple pieces of feature data corresponding to the multiple pieces of object information, and the query identifier includes multiple query identifiers corresponding to the multiple pieces of object information. In this way, for the same object, multiple pieces of object information, multiple pieces of feature data, and multiple query identifiers can be obtained, which can more comprehensively express the object.

[0100] In some embodiments, the feature data is associated with the query identifier and stored, including: the feature data is associated with the query identifier one-to-one and stored in the first storage module, which can be used as a cache library for feature operators to obtain feature data based on the query identifier, reduce repeated calls to the model reasoning service, and thus reduce the pressure on the model reasoning service. In addition, since the image features of separate image information are stored separately and the text features are also stored separately, when the query identifiers are the same, the corresponding image features or text features can be found in the first storage module, without the need to repeatedly store the same image features or text features, reducing resource waste.

[0101] In some embodiments, the method further includes: associating the plurality of feature data corresponding to the object with the object identifier of the object and storing them in a second storage module. In this way, in some scenarios, the user can still query the feature data corresponding to the object based on the object identifier.

[0102] In some embodiments, calculating the feature data of the object information includes: calling a feature calculation model to calculate the feature data of the object information. In this way, the method of the embodiment of the present disclosure can greatly reduce the number of model calls and save computing resources.

[0103] In some embodiments, the method further includes: in response to the feature calculation model being updated, redetermining the feature data of the object information; replacing the stored feature data of the object information with the redetermined feature data of the object information, thereby completing the update of the feature data when the feature calculation model is updated.

[0104] The embodiment of the present disclosure also provides a device for acquiring object features. Figure 4 FIG. 4 is a schematic diagram of an exemplary device 400 provided by an embodiment of the present disclosure. Figure 4 As shown, the device 400 can be used to implement the method 300, and can further include the following modules.

[0105] The first acquisition module 402 is configured to: acquire object information of an object;

[0106] The calculation module 404 is configured to: calculate the query identifier corresponding to the object information based on the object information according to a preset algorithm; wherein the object information and the query identifier are in one-to-one correspondence;

[0107] The second acquisition module 406 is configured to: acquire feature data corresponding to the object information according to the query identifier;

[0108] The calculation and storage module 408 is configured to: in response to failure to obtain feature data corresponding to the object information according to the query identifier, calculate the feature data of the object information, and associate and store the calculated feature data with the query identifier.

[0109] In some embodiments, the object information includes at least one of picture information, text information, and multimodal data for describing the object.

[0110] In some embodiments, the object information is picture information used to describe the object, and the preset algorithm is an encryption algorithm.

[0111] In some embodiments, the object includes a commodity, and the object information is text information for describing the commodity;

[0112] The calculation module 404 is configured to extract the product title corresponding to the product from the text as the query identifier.

[0113] In some embodiments, the first acquisition module 402 is configured to:

[0114] Obtaining an object identifier of the object;

[0115] Acquire attribute information of the object according to the object identifier;

[0116] The object information of the object is acquired according to the attribute information.

[0117] In some embodiments, the object information includes a plurality of object information corresponding to the object, the feature data includes a plurality of feature data corresponding to the plurality of object information, and the query identifier includes a plurality of query identifiers corresponding to the plurality of object information.

[0118] In some embodiments, the calculation and storage module 408 is configured to associate the feature data with the query identifier in a one-to-one correspondence and store them in the first storage module.

[0119] In some embodiments, the calculation and storage module 408 is configured to: associate the multiple feature data corresponding to the object with the object identifier of the object and store them in the second storage module.

[0120] In some embodiments, the calculation and storage module 408 is configured to: call a feature calculation model to calculate feature data of the object information.

[0121] In some embodiments, the calculation and storage module 408 is configured to: redetermine the feature data of the object information in response to the feature calculation model being updated; and replace the stored feature data of the object information with the redetermined feature data of the object information.

[0122] For the convenience of description, the above device is described by dividing it into various modules according to its functions. Of course, when implementing the present disclosure, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0123] The device of the above embodiment is used to implement the corresponding method 300 in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be described in detail here.

[0124] The embodiment of the present disclosure also provides a computer device for implementing the above method 300. Figure 5 FIG. 5 is a schematic diagram showing the hardware structure of an exemplary computer device 500 provided in an embodiment of the present disclosure. The computer device 500 can be used to implement Figure 1 The server 106 can also be used to implement Figure 1 In some scenarios, the computer device 500 can also be used to implement Figure 1 The database server 108.

[0125] like Figure 5 As shown, the computer device 500 may include: a processor 502, a memory 504, a network module 506, a peripheral interface 508 and a bus 510. The processor 502, the memory 504, the network module 506 and the peripheral interface 508 are connected to each other in communication within the computer device 500 through the bus 510.

[0126] Processor 502 may be a central processing unit (CPU), an image processor, a neural network processor (NPU), a microcontroller (MCU), a programmable logic device, a digital signal processor (DSP), an application specific integrated circuit (ASIC), or one or more integrated circuits. Processor 502 may be used to perform functions related to the technology described in this disclosure. In some embodiments, processor 502 may also include multiple processors integrated into a single logical component. For example, Figure 5 As shown, processor 502 may include a plurality of processors 502a, 502b, and 502c.

[0127] The memory 504 may be configured to store data (eg, instructions, computer code, etc.). Figure 5 As shown, the data stored in the memory 504 may include program instructions (e.g., program instructions for implementing the method 300 of the embodiment of the present disclosure) and data to be processed (e.g., the memory may store configuration files of other modules, etc.). The processor 502 may also access the program instructions and data stored in the memory 504, and execute the program instructions to operate on the data to be processed. The memory 504 may include a volatile storage device or a non-volatile storage device. In some embodiments, the memory 504 may include a random access memory (RAM), a read-only memory (ROM), an optical disk, a magnetic disk, a hard disk, a solid-state drive (SSD), a flash memory, a memory stick, etc.

[0128] The network interface 506 can be configured to provide the computer device 500 with communication with other external devices via a network. The network can be any wired or wireless network capable of transmitting and receiving data. For example, the network can be a wired network, a local wireless network (e.g., Bluetooth, WiFi, near field communication (NFC)), a cellular network, the Internet, or a combination thereof. It is understood that the type of network is not limited to the above specific examples.

[0129] The peripheral interface 508 can be configured to connect the computer device 500 to one or more peripheral devices to achieve information input and output. For example, the peripheral devices can include input devices such as a keyboard, a mouse, a touch pad, a touch screen, a microphone, and various sensors, and output devices such as a display, a speaker, a vibrator, and an indicator light.

[0130] The bus 510 may be configured to transmit information between various components of the computer device 500 (e.g., the processor 502, the memory 504, the network interface 506, and the peripheral interface 508), such as an internal bus (e.g., a processor-memory bus), an external bus (USB port, PCI-E bus), etc.

[0131] It should be noted that, although the architecture of the above-mentioned computer device 500 only shows the processor 502, the memory 504, the network interface 506, the peripheral interface 508 and the bus 510, in the specific implementation process, the architecture of the computer device 500 may also include other components necessary for normal operation. In addition, it can be understood by those skilled in the art that the architecture of the above-mentioned computer device 500 may also only include the components necessary for implementing the embodiments of the present disclosure, and does not necessarily include all the components shown in the figure.

[0132] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments, the present disclosure also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute method 300 described in any of the above embodiments.

[0133] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0134] The computer instructions stored in the storage medium of the above embodiment are used to enable the computer to execute the method 300 described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0135] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments, the present disclosure further provides a computer program product, which includes a computer program. In some embodiments, the computer program is executable by one or more processors so that the processors execute the described method 300. Corresponding to the execution subject corresponding to each step in each embodiment of the method 300, the processor that executes the corresponding step may belong to the corresponding execution subject.

[0136] The computer program product of the above embodiment is used to enable the processor to execute the method 300 described in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be described in detail here.

[0137] Those skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present disclosure (including the claims) is limited to these examples. Based on the concept of the present disclosure, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present disclosure as described above, which are not provided in detail for the sake of simplicity.

[0138] In addition, to simplify the description and discussion, and in order not to make the embodiments of the present disclosure difficult to understand, the known power / ground connections to the integrated circuit (IC) chips and other components may or may not be shown in the provided figures. In addition, the device can be shown in the form of a block diagram to avoid making the embodiments of the present disclosure difficult to understand, and this also takes into account the fact that the details of the implementation of these block diagram devices are highly dependent on the platform on which the embodiments of the present disclosure will be implemented (that is, these details should be fully within the scope of understanding of those skilled in the art). Where specific details (e.g., circuits) are set forth to describe exemplary embodiments of the present disclosure, it is apparent to those skilled in the art that the embodiments of the present disclosure can be implemented without these specific details or with changes in these specific details. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0139] Although the present disclosure has been described in conjunction with specific embodiments of the present disclosure, many replacements, modifications and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed.

[0140] The embodiments of the present disclosure are intended to cover all such substitutions, modifications and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present disclosure should be included in the scope of protection of the present disclosure.

Claims

1. A method for obtaining object features, comprising: Get object information of an object; According to a preset algorithm, based on the object information, a query identifier corresponding to the object information is calculated; wherein the object information and the query identifier are in one-to-one correspondence; Acquire feature data corresponding to the object information according to the query identifier; In response to the inability to obtain the feature data corresponding to the object information according to the query identifier, the feature data of the object information is calculated, and the calculated feature data is associated with the query identifier and stored.

2. The method of claim 1, wherein: The object information includes at least one of picture information, text information, and multimodal data for describing the object.

3. The method of claim 2, wherein: The object information is picture information used to describe the object, and the preset algorithm is an encryption algorithm.

4. The method of claim 2, wherein: The object includes a commodity, and the object information is text information used to describe the commodity; According to a preset algorithm, based on the object information, a query identifier corresponding to the object information is calculated, including: According to a preset algorithm, the product title corresponding to the product is extracted from the text as the query identifier.

5. The method of claim 2, wherein: Get object information of an object, including: Obtaining an object identifier of the object; Acquire attribute information of the object according to the object identifier; The object information of the object is acquired according to the attribute information.

6. The method of claim 1, wherein: The object information includes a plurality of object information corresponding to the object, the feature data includes a plurality of feature data corresponding to the plurality of object information, and the query identifier includes a plurality of query identifiers corresponding to the plurality of object information.

7. The method of claim 6, wherein: Associating and storing the characteristic data with the query identifier includes: The characteristic data and the query identifier are associated with each other in a one-to-one correspondence and stored in the first storage module.

8. The method of claim 6, further comprising: The plurality of feature data corresponding to the object are associated with the object identifier of the object and stored in the second storage module.

9. The method of claim 1, wherein: Calculating feature data of the object information includes: A feature calculation model is called to calculate feature data of the object information.

10. The method of claim 9, further comprising: In response to the feature calculation model being updated, re-determining the feature data of the object information; The newly determined feature data of the object information is used to replace the already stored feature data of the object information.

11. A device for acquiring object features, comprising: The first acquisition module is configured to: acquire object information of an object; A calculation module is configured to: calculate a query identifier corresponding to the object information based on the object information according to a preset algorithm; wherein the object information and the query identifier are in one-to-one correspondence; A second acquisition module is configured to: acquire feature data corresponding to the object information according to the query identifier; The calculation and storage module is configured to: in response to being unable to obtain the feature data corresponding to the object information according to the query identifier, calculate the feature data of the object information, and associate and store the calculated feature data with the query identifier.

12. A computer device comprising one or more processors, a memory; and one or more programs, wherein the one or more programs are stored in the memory and executed by the one or more processors, and the programs include instructions for executing the method according to any one of claims 1 to 10.

13. A non-volatile computer-readable storage medium containing a computer program, which, when executed by one or more processors, causes the processors to perform the method of any one of claims 1 to 10.

14. A computer program product comprising computer program instructions, which, when executed on a computer, cause the computer to execute the method according to any one of claims 1 to 10.

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