Rapid page configuration method and device for customer customization and medium

Abstract

The invention relates to the technical field of data caching, and discloses a rapid page configuration method and device for customer customization and a medium, and the method comprises the steps: obtaining a user demand, behavior data and an accessory library, encrypting and uploading the user demand and the behavior data to a preset block chain, obtaining an intelligent contract, and storing the intelligent contract in the accessory library; extracting a basic accessory from an accessory library according to a questionnaire demand in the user demand by using an intelligent contract; semantic analysis is carried out on supplementary demands in the user demands to obtain supplementary information demands, and supplementary accessories are screened out from the accessory library by utilizing the supplementary information demands; calculating the actual accessory use probability of the user according to the behavior data, and performing weight configuration on the supplementary accessory and the basic accessory according to the actual accessory use probability of the user to obtain to-be-processed accessory information; and performing personalized page construction according to the to-be-processed accessory information to obtain a customized page. According to the method, the individuation degree of page configuration can be improved, and privacy data of a user can be protected.

Description

Technical Field

[0001] The present invention relates to the technical field of data cache, and in particular to a method, device and medium for quickly configuring a page customized for a customer. Background Art

[0002] With the rapid development of Internet technology and the increasingly diversified consumer needs, web pages, as the core platform for enterprises to interact with users, have become a key strategy for improving user experience, achieving specific business goals and shaping brand image. To adapt to this trend, the rapid configuration service of customized pages for corporate customers has emerged, aiming to help corporate customers build web page layouts, functional modules and visual styles that meet their specific needs in a relatively short period of time.

[0003] However, the existing customized page configuration method usually selects one or more page templates suitable for the type of corporate customers from a series of template libraries, and manually adjusts the page elements and attributes of the page templates through the background management system to achieve rapid configuration of the page. However, this method can only provide some basic template options, and cannot effectively analyze and apply the needs provided by users, nor can it customize personalized service pages according to the needs of corporate customers, making it difficult to deeply customize and personalize corporate customers. At the same time, corporate customers cannot ensure the security and privacy protection of user sensitive information during the customization process, which increases the compliance risks and trust crisis faced by enterprises. In summary, the existing customized page configuration method still has the problems of insufficient personalization and lack of data security protection mechanism. Summary of the invention

[0004] The present invention provides a method, device and medium for quickly configuring a customized page, the main purpose of which is to solve the problem of insufficient personalization of the existing customized page configuration method and the problem of lack of data security mechanism when customizing pages.

[0005] To achieve the above object, the present invention provides a method for quickly configuring a page customized for a customer, comprising:

[0006] Obtain user needs, behavior data, and an accessories library, encrypt and upload the user needs and behavior data to a preset blockchain, obtain a smart contract, and use the smart contract to extract basic accessories from the accessories library according to the questionnaire requirements in the user needs;

[0007] Performing semantic analysis on the supplementary requirements in the user requirements to obtain supplementary information requirements, and using the supplementary information requirements to filter out supplementary accessories from the accessories library;

[0008] Calculating the user's actual accessory usage probability according to the behavior data, and using the user's actual accessory usage probability to weight the supplementary accessories and the basic accessories to obtain accessory information to be processed;

[0009] A personalized page is constructed according to the accessory information to be processed to obtain a customized page.

[0010] Optionally, encrypting and uploading the user demand and behavior data to a preset blockchain to obtain a smart contract includes:

[0011] Encrypting the user demand and the behavior to obtain encrypted data;

[0012] Encapsulating the encrypted data to obtain a blockchain transaction;

[0013] Uploading the blockchain transaction to the blockchain to obtain uploaded data;

[0014] A smart contract is generated based on the uploaded data.

[0015] Optionally, extracting basic accessories from the accessories library according to the questionnaire requirements in the user requirements by using the smart contract includes:

[0016] Utilize the smart contract to analyze the questionnaire requirements and obtain accessory features;

[0017] Conditionally matching the accessory feature with the accessory library to obtain accessory information;

[0018] The accessory information is used to sort the accessory features to obtain a basic accessory.

[0019] Optionally, performing semantic parsing on the supplementary requirements in the user requirements to obtain the supplementary information requirements includes:

[0020] Performing word segmentation and part-of-speech tagging on the supplementary demand to obtain a word segmentation phrase;

[0021] Performing syntactic analysis on the supplementary demand using the segmented phrase to obtain a syntactic tree;

[0022] Performing entity relationship mapping on the segmented phrases using the supplementary requirements to obtain key entity concepts;

[0023] Using the supplementary requirements and the key entity concepts, the segmented phrases are labeled with semantic roles to obtain role objects;

[0024] Constructing a syntax tree using the role object, the key entity concept and the syntax tree;

[0025] Performing logical form representation on the syntax tree to obtain a logical form;

[0026] The logical form is semantically transformed to obtain supplementary information requirements.

[0027] Optionally, constructing a syntax tree using the role object, the key entity concept and the syntax tree includes:

[0028] Using the key entity concept to add labels to the syntax tree to obtain a basic syntax tree;

[0029] Structural adjustment is performed on the role object and the basic syntax tree to obtain an event structure;

[0030] Relation edges are added to the event structure to obtain a syntax tree.

[0031] Optionally, the performing logical form representation on the syntax tree to obtain a logical form includes:

[0032] Extracting logical atoms from the syntax tree to obtain basic units;

[0033] Convert the data nodes and network edges in the syntax tree into logical expressions using the basic units;

[0034] Quantitatively expressing the logical expression to obtain a quantified result;

[0035] Converting the logical expression into a logical structure using the syntax tree and the quantization result;

[0036] The logical structure is equivalently transformed to obtain a logical form.

[0037] Optionally, calculating the user's actual accessory usage probability according to the behavior data includes:

[0038] Performing feature screening on the behavior data to obtain relevant features;

[0039] Constructing a sparse matrix using the related features, the basic accessories and the supplementary accessories;

[0040] The sparse matrix is ​​decomposed to obtain a user preference matrix and an accessory feature matrix, wherein the matrix decomposition is performed using the following formula:

[0041] R=U∑V T

[0042] Where R is a sparse matrix, U is a user preference vector matrix, V is an accessory feature vector matrix, T is a matrix transpose operation, and ∑ is a preset diagonal matrix;

[0043] Calculating predicted scores of the basic accessories and the supplementary accessories using the user preference matrix and the accessory feature matrix;

[0044] The predicted score is converted into the user's actual accessory usage probability.

[0045] Optionally, the building of a personalized page according to the to-be-processed accessory information to obtain a customized page includes:

[0046] Sorting the to-be-processed accessory information by weight to obtain a sorting result;

[0047] Using the sorting result, each accessory in the to-be-processed accessory information is matched with each position in the pre-acquired page template to obtain a corresponding result;

[0048] According to the corresponding result, the interface information of the accessory to be processed is used to replace the interface information at the corresponding position of the page template to obtain a customized page.

[0049] In order to solve the above problem, the present invention further provides an electronic device, the electronic device comprising:

[0050] at least one processor; and,

[0051] a memory communicatively connected to the at least one processor; wherein,

[0052] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the above-mentioned method for quickly configuring pages customized for customers.

[0053] In order to solve the above problems, the present invention also provides a computer-readable storage medium, in which at least one computer program is stored. The at least one computer program is executed by a processor in an electronic device to implement the above-mentioned method for rapid configuration of customized pages.

[0054] The embodiment of the present invention improves the security and privacy protection of data during transmission and storage by encrypting and uploading user demand and behavior data to the blockchain, and at the same time, utilizes the tamper-proof characteristics of the blockchain to improve the transparency and trust of the data; by semantically parsing the supplementary demand, the customer's deep supplementary information demand can be accurately identified, and the accessories can be selected from the accessories library by using the supplementary information demand, so that the recommended accessories can be more in line with the user's specific situation and preference, and the accuracy and personalization of the recommendation can be improved; by calculating the probability of accessory use based on user behavior data, the user's potential needs can be predicted, so that the recommendation is closer to the user's actual usage habits, and weight configuration is performed based on the probability of use to reduce the proportion of unnecessary accessories, which is helpful to optimize supply chain management and improve resource utilization efficiency; by constructing a personalized page based on the accessory information to be processed, a customized browsing experience is provided for the user, and the friendliness and interactivity of the user interface are improved. Therefore, the method, device and medium for rapid configuration of customized pages for customers proposed by the present invention can solve the problem of insufficient personalization of the existing customized page configuration method for customers and the problem of lack of data security guarantee mechanism when customizing pages. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 A schematic diagram of a process for a method for quickly configuring a customized page for a customer provided by an embodiment of the present invention;

[0056] Figure 2 A schematic diagram of a process of uploading a blockchain according to an embodiment of the present invention;

[0057] Figure 3 A schematic diagram of a calculation flow of an actual accessory usage probability provided by an embodiment of the present invention;

[0058] Figure 4 A schematic diagram of the structure of an electronic device for implementing the method for rapid page configuration customized for customers provided by an embodiment of the present invention.

[0059] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0060] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0061] The embodiment of the present application provides a method for quickly configuring a page customized for a customer. The execution subject of the method for quickly configuring a page customized for a customer includes but is not limited to at least one of the electronic devices such as a server, a terminal, etc. that can be configured to execute the method provided by the embodiment of the present application. In other words, the method for quickly configuring a page customized for a customer can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be an independent server, or it can be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and basic cloud computing services such as big data and artificial intelligence platforms.

[0062] Reference Figure 1 FIG. 1 is a flow chart of a method for quickly configuring a page customized for a customer according to an embodiment of the present invention. In this embodiment, the method for quickly configuring a page customized for a customer includes:

[0063] S1. Obtain user needs, behavior data and an accessories library, encrypt the user needs and behavior data and upload them to a preset blockchain to obtain a smart contract, and use the smart contract to extract basic accessories from the accessories library according to the questionnaire requirements in the user needs.

[0064] In an embodiment of the present invention, the user needs include questionnaire needs and supplementary needs, wherein the questionnaire needs refer to the basic customer needs collected by questionnaire polling. By obtaining the questionnaire needs, the user's specific expectations for the functions, styles, etc. of specific accessories can be directly obtained, avoiding guessing or vague understanding of user needs and improving the targeted matching of accessories; the supplementary needs refer to the user's supplementary suggestions collected in the form of a dialog box. By conducting in-depth semantic analysis of the supplementary needs, the user's potential demand details and related needs can be excavated, and the accessory selection can be further enriched and refined to ensure that the provided accessories are more in line with the user's personalized expectations.

[0065] In the embodiment of the present invention, the behavior data refers to user preference data and industry trend data, wherein the industry trend includes consumers' accessory click rate, accessory usage rate, order quantity, order sequence, etc.

[0066] In an embodiment of the present invention, the accessory library refers to a systematic and structured resource collection, which contains various accessory elements that can be selected and configured. These elements are used to meet the different needs of customers in the process of rapid configuration of customized pages, including accessory name, category, function description, instructions for use, preview image (or sample code), applicable scenarios, dependencies, usage interface, version information unique identifier and other information.

[0067] In an embodiment of the present invention, by uploading user needs and behavior data to a preset blockchain, user needs, behavior data and an accessories library can be encrypted to ensure that sensitive information is not stolen or tampered with by unauthorized third parties during transmission and storage, thereby effectively protecting user privacy and commercial secrets. At the same time, by extracting basic accessories through smart contracts, automatic matching between questionnaire requirements and basic accessories supply can be achieved, greatly improving the response speed between supply and demand.

[0068] Ginseng Figure 2 As shown, the user demand and behavior data are encrypted and uploaded to the preset blockchain to obtain a smart contract, including:

[0069] S21, encrypting the user demand and the behavior to obtain encrypted data;

[0070] S22, encapsulating the encrypted data to obtain a blockchain transaction;

[0071] S23, uploading the blockchain transaction to the blockchain to obtain uploaded data;

[0072] S24. Generate a smart contract based on the uploaded data.

[0073] In the embodiment of the present invention, the data encryption refers to implementing a hierarchical encryption strategy for each specific information in the user demand and behavior data, thereby ensuring the security of the overall data, wherein the hierarchical encryption strategy refers to generating a unique subkey for each data field, and using the key to perform encryption processing on the content of the corresponding field. The subkey is obtained by calculating the preset key using the data field and a nonlinear function.

[0074] Among them, the following formula can be used for encryption:

[0075] C i =S i ⊕K i

[0076] Among them, C i is the encrypted data corresponding to the i-th field, S i is the i-th field, K iis the key corresponding to the i-th field, and ⊕ is the exclusive OR operator.

[0077] In an embodiment of the present invention, the encrypted user demand and behavior data is used as the data payload of the transaction, and the transaction metadata is constructed according to the data payload, the identity identifier of the transaction initiator (usually its blockchain address, which can be understood as a unique email address, but used for blockchain transactions), the timestamp (recording the exact time when the transaction occurred), and the transaction type (for example, marking this transaction as a data upload type). The private key of the transaction initiator is used to perform a hash operation on the above-constructed transaction metadata to generate a unique hash value. The hash value is used to perform an encryption operation on the private key of the initiator to obtain a digital signature. The transaction structure is constructed using the transaction metadata, the digital signature, and a preset blockchain version number, input and output list, lock script, unlock script and other data to obtain a blockchain transaction.

[0078] In detail, the private key is a key held by an individual in asymmetric encryption and used for signing and decryption, ensuring the security authentication of transactions; while the encryption key is used to encrypt and protect the data field itself.

[0079] In an embodiment of the present invention, the blockchain upload refers to using the nodes in the blockchain network to verify whether the data in the blockchain transaction is valid, that is, checking whether the transaction format is correct, whether the digital signature matches the initiator's public key, and whether the transaction complies with other rules of the blockchain. When the majority of nodes pass the verification, the blockchain transaction will be added to the blockchain, that is, the upload is completed.

[0080] In the embodiment of the present invention, the preset source code is deployed to the blockchain after the upload is completed, and the parameters of the source code are initialized to obtain a smart contract.

[0081] In detail, the smart contract defines a data structure representing the accessory library, and includes a function for receiving questionnaire data in user requirements. This function can realize the function of parsing questionnaire requirements, that is, converting questionnaire requirements into accessory features.

[0082] In the embodiment of the present invention, extracting basic accessories from the accessories library according to the questionnaire requirements in the user requirements by using the smart contract includes:

[0083] Utilize the smart contract to analyze the questionnaire requirements and obtain accessory features;

[0084] Conditionally matching the accessory feature with the accessory library to obtain accessory information;

[0085] The accessory information is used to sort the accessory features to obtain a basic accessory.

[0086] In an embodiment of the present invention, the data conversion refers to converting the requirements submitted by the user through a questionnaire into a data format that can be processed by the smart contract, by converting the answers to the questionnaire questions into specific identifiers or parameters, which are used to screen the basic accessories in the accessories library.

[0087] In an embodiment of the present invention, it is implemented inside a smart contract by traversing the accessories library and matching according to the conditions transmitted by the questionnaire requirements (such as accessory type, specification, grade, etc.). If a basic accessory that meets the accessory characteristics is found, the unique identifier and data interface corresponding to the basic accessory are stored in a temporary collection, and finally the accessory information is obtained.

[0088] In an embodiment of the present invention, the accessory features are classified and matched with preset classification labels, such as labeling according to the function of the accessory (such as "processor", "memory"), applicable scenarios (such as "gaming-only", "business office") or performance level (such as "entry-level", "high-end"); the basic accessories are classified using the classification labels to obtain a set of accessories distinguished by different labels, wherein each set represents a class of accessory information with common characteristics; the classified accessory set is stored in the form of a structured data table to obtain basic accessories, and each data table in the basic accessories corresponds to a classification label, which contains all accessory information under this category.

[0089] The basic accessories refer to a collection of all accessory information that meets the user's questionnaire requirements, stored in the form of a structured data table. The accessories list contains information such as the name, category, and function description of the accessories that meet the user's questionnaire requirements. The accessory features refer to the user's requirement features parsed from the questionnaire requirements. For example, if the question in the questionnaire requirement is "What do you want this accessory to be used for? High performance computing", and then high performance computing is converted into a computing identifier corresponding to the accessories library, then the computing identifier is the accessory feature.

[0090] In the embodiment of the present invention, detailed user demand information can be systematically collected through the questionnaire demand, and then basic accessories that best meet the user's needs can be selected from the accessories library, and the specific needs of different users can be accurately identified, thereby improving the accuracy of matching.

[0091] S2. Perform semantic analysis on the supplementary requirements in the user requirements to obtain supplementary information requirements, and use the supplementary information requirements to filter out supplementary accessories from the accessories library.

[0092] In an embodiment of the present invention, the semantic analysis refers to a process of deeply understanding and interpreting the supplementary demand part of the user demand to extract the real meaning, intention and contextual association behind it, so as to more accurately understand the user's preferences and needs.

[0093] In the embodiment of the present invention, semantic analysis of the supplementary requirements in the user's requirements can deeply understand the user's actual needs and preferences, provide more personalized and accurate accessory recommendations, and improve user satisfaction.

[0094] In the embodiment of the present invention, the semantic analysis of the supplementary requirements in the user requirements to obtain the supplementary information requirements includes:

[0095] Performing word segmentation and part-of-speech tagging on the supplementary demand to obtain a word segmentation phrase;

[0096] Performing syntactic analysis on the supplementary demand using the segmented phrase to obtain a syntactic tree;

[0097] Performing entity relationship mapping on the segmented phrases using the supplementary requirements to obtain key entity concepts;

[0098] Using the supplementary requirements and the key entity concepts, the segmented phrases are labeled with semantic roles to obtain role objects;

[0099] Constructing a syntax tree using the role object, the key entity concept and the syntax tree;

[0100] Performing logical form representation on the syntax tree to obtain a logical form;

[0101] The logical form is semantically transformed to obtain supplementary information requirements.

[0102] In an embodiment of the present invention, by removing all symbols in the supplementary requirements, the supplementary requirements are split into single sentences using the positions of the symbols; removing the preset stop words in the sentences, the sentences are split into word segmentation results; establishing a set of part-of-speech states according to preset part-of-speech categories (such as nouns, verbs, adjectives), and initializing the probability of occurrence of each part-of-speech; using the transition probability between parts of speech (i.e., the probability of a certain part of speech followed by another part of speech) and the emission probability (the probability of a certain word belonging to a certain part of speech) to calculate the probability distribution of each word in the text corresponding to each part-of-speech category; according to the calculated probability distribution, the most likely part-of-speech tag is assigned to each word, the part-of-speech tag is combined with its corresponding vocabulary to form a phrase vector with a part-of-speech tag, and the phrase vector is used as a word segmentation phrase. Wherein, the stop words refer to a predefined series of common words that contribute less to the analysis task, including words or characters that have no practical meaning or appear frequently.

[0103] In an embodiment of the present invention, a feature vector is constructed using the words, parts of speech and positions in the supplementary requirements of the segmented phrase, and a preset dependency analyzer is used to perform dependency prediction on the feature vector to predict the relationship between each word and the words it depends on (head word and dependent word), as well as the type of such dependency (such as subject-predicate relationship, verb-object relationship, etc.), that is, dependency relationship, and a syntactic tree is constructed using the dependency relationship.

[0104] In which, each node of the syntax tree represents a vocabulary, the edge represents the dependency relationship, pointing to its dependent words, and the syntax tree has a unique root node, representing the trunk of the entire sentence; specifically, the dependency analyzer can be a deep learning network model such as a recurrent neural network, by accepting the feature vector and obtaining the final hidden state at the last time step, and calculating the score of each possible dependency pair based on the hidden state, the score represents the score of the dependency relationship between each possible head word and the dependent word, and finally outputs the head word and the dependent word and the dependency type based on the score.

[0105] In an embodiment of the present invention, each segmentation phrase is matched with the rules in the rule library, the entity boundary in the supplementary demand is identified, and according to the successfully matched rules, the correct type label is assigned to the identified entity to obtain a named entity; and the named entity is associated with a preset unique identifier. The rule library refers to a regular expression or vocabulary list containing professional terms related to the enterprise page configuration, component names (such as "navigation bar", "carousel"), service types (such as "SEO optimization", "payment interface integration"), etc.

[0106] In the embodiment of the present invention, a predicate is extracted from the participle phrase, i.e., a verb, adjective, or other word that can express an action, state, or attribute, and semantic role recognition is performed on the supplementary demand based on the extracted predicate, i.e., the named entities adjacent to the predicate in the supplementary demand are screened out, and role labels are assigned to all the words in the syntax tree corresponding to the supplementary demand one by one, and the assigned role labels are vector-combined with the words to obtain a role object. The role label refers to the agent (i.e., the transaction that performs the action), the patient (the transaction that the action is performed), and the place (where it is performed). For example, "the system can add a slider that displays the latest products on the homepage", then the predicate is "add", the agent is the system, the patient is the slider for the latest products, and the place is the homepage.

[0107] In the embodiment of the present invention, the step of constructing a syntax tree using the role object, the key entity concept and the syntax tree includes:

[0108] Using the key entity concept to add labels to the syntax tree to obtain a basic syntax tree;

[0109] Structural adjustment is performed on the role object and the basic syntax tree to obtain an event structure;

[0110] Relation edges are added to the event structure to obtain a syntax tree.

[0111] In detail, all key entity concepts and their attributes are extracted, each node (participle phrase) of the syntactic tree is traversed, and the matching degree between these nodes and the key entity concepts is calculated. If the node content corresponds to an identified key entity, the corresponding entity label is added to the node. For the matched entity nodes, consider adding more attribute labels, such as entity type (personal name, place name, organization, etc.), unique identifier, etc., to obtain the basic grammar tree.

[0112] In detail, the role labels are used to create data nodes identical to the basic syntax tree, and the roles they play in the events (such as agent, patient, time, place, etc.) are marked on these nodes; based on the annotated role labels, the data is locally structured to ensure clear expression of role relationships, that is, edges are added between directly related nodes.

[0113] In detail, the node relationships in the event structure are further identified to identify other semantic relationships besides direct dependency relationships, such as causality, conditionality, accompaniment, etc., and additional edges are further added to the event structure to represent these relationships. These edges can be solid lines or dashed lines. The event structure is added to the basic syntax tree to obtain a grammatical tree.

[0114] In the embodiment of the present invention, the logical form representation refers to converting the sentences in the supplementary requirements into a formalized and structured representation. For example, the supplementary requirement is "I hope to add an 'Add to Cart' button at the bottom of each product details page, and the button color must be consistent with the theme color." Among them, the logical relationship in the supplementary requirement is identified, and the expression of the logical relationship is reconstructed. Let P(x) represent "x is a product details page", B(y) represent "y is an 'Add to Cart' button", L(x,c) represent "there is an element with color c at the bottom of page x", C(c1,c2) ​​represent "color c1 is consistent with color c2", T represents "theme color", then the logical form of the supplementary requirement is in, is a universal quantifier, meaning "all", → means implication, Indicates that for all product detail pages x, It means there is at least one button y, ∧ means logical AND, and Color(y) means the color of button y.

[0115] In the embodiment of the present invention, the step of performing logical form representation on the syntax tree to obtain a logical form includes:

[0116] Extracting logical atoms from the syntax tree to obtain basic units;

[0117] Convert the data nodes and network edges in the syntax tree into logical expressions using the basic units;

[0118] Quantitatively expressing the logical expression to obtain a quantified result;

[0119] Converting the logical expression into a logical structure using the syntax tree and the quantization result;

[0120] The logical structure is equivalently transformed to obtain a logical form.

[0121] In detail, by traversing the syntax tree, syntactic structures such as noun phrases, verb phrases, prepositional phrases, and corresponding dependencies are identified, and the identified smallest named entity is transformed into a logical atom, and an expression is defined for the logical atom, such as "add button" is B(y).

[0122] In detail, all data nodes and network edges are converted into logical expressions using the basic unit and the syntax tree. For example, the supplementary requirement is "add a red buy button at the top of all product detail pages", and the syntax tree is "add->buy button (action-target)", "add->at the top of...->product detail page (action-position)", and the corresponding basic unit is B(y): indicating the operation of adding a button, where y represents the specific attributes of the button, L(x): indicating the page location, x is the location description, P(x): indicating the page type, x is the page name, and the logical expression of "add->buy button (action-target)" is: The logical expression of "Add->At the top of...->Product details page (action-location)" is:

[0123] Specifically, the quantitative information in the logical expression is clarified and standardized, that is, the universal quantifier (such as "all") and the existential quantifier (such as "some") are distinguished. For example, if the supplementary requirement is "add a red buy button at the top of all product detail pages", the quantitative information is "all product detail pages", and all are represented as Then the logical expression is quantized, and the quantization result is

[0124] Specifically, the quantification results are merged using the association relationship between the syntax trees. That is, the logical structure corresponding to the supplementary requirement of "adding a red purchase button at the top of all product detail pages" is: The ExistsAddedButton(x,y) represents the concept of "a button with attribute y added to page x".

[0125] Specifically, the formed logical structure is subjected to logical equivalence transformation, that is, the connectives in the logical structure (such as conjunction ∧, disjunction ∨, implication →, equivalent ), quantifier (universal quantifier Existential Quantifier ), proposition variables and predicates use logical reasoning rules to merge similar terms to obtain logical forms, where the logical reasoning rules refer to De Morgan's laws, distributive laws, absorbing laws, etc.

[0126] In the embodiment of the present invention, the semantic conversion refers to further converting the logical form into a format that meets specific application requirements, such as a query language expression, etc., so as to obtain specific supplementary information requirements.

[0127] In the embodiment of the present invention, the step of selecting supplementary accessories from the accessories library by using the supplementary information requirements is basically the same as the step of extracting basic accessories from the accessories library by using the smart contract according to the questionnaire requirements in the user requirements in the above step, and will not be elaborated here.

[0128] In the embodiment of the present invention, by performing semantic analysis on the user's supplementary needs and deeply understanding the user's specific needs, accessories that meet the user's supplementary information needs can be accurately matched, thereby providing the user with personalized and accurate accessories.

[0129] S3. Calculate the actual accessory usage probability of the user according to the behavior data, and use the actual accessory usage probability of the user to weight the supplementary accessories and the basic accessories to obtain accessory information to be processed.

[0130] In an embodiment of the present invention, by weighting the supplementary accessories and basic accessories obtained by the user according to the behavioral data, i.e., the user preference data and the industry trend data, commonly used accessories can be given a larger weight, thereby optimizing the operational efficiency of the user's enterprise.

[0131] Ginseng Figure 3 As shown, the actual accessory usage probability of the user is calculated based on the behavior data, including:

[0132] S31, performing feature screening on the behavior data to obtain relevant features;

[0133] S32, constructing a sparse matrix according to the relevant features, the basic accessories and the supplementary accessories;

[0134] S33, performing matrix decomposition on the sparse matrix to obtain a user preference matrix and an accessory feature matrix;

[0135] S34, calculating the predicted scores of the basic accessories and the supplementary accessories using the user preference matrix and the accessory feature matrix;

[0136] S35: Convert the predicted score into the user's actual accessory usage probability.

[0137] In an embodiment of the present invention, a cross-classification table is created based on the behavioral data, each cell in the table represents the frequency or frequency of a combination of a category of a feature and a category of a target variable, based on the marginal sums of rows and columns, the expected frequency of each cell is calculated under the assumption that the variables are independent of each other, the chi-square statistic and the degrees of freedom are calculated based on the actual frequency and the expected frequency, the P value is calculated using a preset chi-square distribution table and the degrees of freedom, the size relationship between the P value and the preset significance level is compared, and relevant features are screened out from the behavioral data based on the size relationship, wherein the P value reflects the probability of whether the difference between the observed frequency and the expected frequency is purely accidental, and the smaller the P value, the more significant the relationship between the feature and the target variable is considered to be; the degrees of freedom are calculated by multiplying the number of rows and the number of columns, and the chi-square statistic is obtained by calculating the standard deviation of the observed frequency and the expected frequency, and then dividing the standard deviation by the expected frequency, and then summing them.

[0138] In an embodiment of the present invention, an interaction index is calculated based on the consumer data and the accessory data in the relevant features, such as performing a weighted calculation based on the accessory click rate and the consumer order quantity to obtain an interaction index value, and a two-dimensional sparse matrix is ​​created based on the interaction index value, the consumer data, and the accessory data. Each row represents a consumer, each column represents an accessory, and the elements in the matrix represent the interaction index value between the user and the accessory.

[0139] In the embodiment of the present invention, the following formula is used to perform matrix decomposition:

[0140] R=U∑V T

[0141] Among them, R is a sparse matrix, U is a user preference vector matrix, V is an accessory feature vector matrix, T is a matrix transpose operation, and ∑ is a preset diagonal matrix.

[0142] In detail, by decomposing the sparse matrix, two low-dimensional matrices are obtained. The non-zero elements of the sparse matrix represent the ratings or preferences of specific users for specific accessories. Each row vector in the user preference vector matrix expresses the personalized preference pattern of the corresponding user. Each column vector in the accessory feature vector matrix captures the unique attributes or categories of an accessory. The diagonal matrix contains a measure of importance in the process of converting from high-dimensional to low-dimensional space, and larger measure values ​​correspond to more important features.

[0143] In the embodiment of the present invention, a prediction score is obtained by performing a dot product operation on the user preference vector and the accessory feature vector. The prediction score refers to the user's preference for the accessory predicted based on the behavior data.

[0144] In an embodiment of the present invention, in order to convert the predicted score into the actual usage probability, the score can be normalized, such as converting the score into a probability distribution through a normalization function to ensure that the sum of the probabilities of all accessories is 1, thereby obtaining the actual usage probability of each accessory by the user.

[0145] In the embodiment of the present invention, the weight configuration of the supplementary accessories and the basic accessories is performed using the actual accessory usage probability of the user to obtain the accessory information to be processed, which means that the configuration weights of the basic accessories and the supplementary accessories are calculated using the actual accessory usage probability of the user, and the configuration weights are mapped to the basic accessories and the supplementary accessories to obtain the accessory information to be processed.

[0146] In the embodiment of the present invention, by calculating the actual accessory usage probability of the user based on the behavior data, it is possible to predict the usage demand, and then build a personalized page for the user based on the usage demand, provide the user with a personalized customized page, and improve the user experience.

[0147] S4. Construct a personalized page according to the accessory information to be processed to obtain a customized page.

[0148] In an embodiment of the present invention, the personalized page construction refers to performing page layout according to the accessory information to be processed, and placing the basic accessories and the supplementary accessories in different positions using the weight information in the accessory information to be processed to obtain a customized page.

[0149] In the embodiment of the present invention, by realizing personalized construction of the page, it is possible to accurately display the accessory information that the user is interested in or needs, effectively highlight the characteristics and needs of the user's business, reduce the user's search and screening time, and make the page content more in line with the user's actual needs, thereby improving user satisfaction and participation.

[0150] In the embodiment of the present invention, a personalized page is constructed according to the to-be-processed accessory information to obtain a customized page, including:

[0151] Sorting the to-be-processed accessory information by weight to obtain a sorting result;

[0152] Using the sorting result, each accessory in the to-be-processed accessory information is matched with each position in the pre-acquired page template to obtain a corresponding result;

[0153] According to the corresponding result, the interface information of the accessory to be processed is used to replace the interface information at the corresponding position of the page template to obtain a customized page.

[0154] In the embodiment of the present invention, by constructing a customized page to display content that meets the user's specific needs and preferences, the user's decision path is effectively shortened, the user is quickly guided to the components they are most likely to use, and the user experience is optimized.

[0155] like Figure 4 FIG. 1 is a schematic diagram of the structure of an electronic device for implementing a method for quickly configuring a page customized for a customer provided by an embodiment of the present invention.

[0156] The electronic device may include a processor 10, a memory 11, a communication bus 12 and a communication interface 13, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as a page quick configuration program customized for a customer.

[0157] The processor 10 includes one or more central processing units (CPU), microprocessors, digital processing chips, graphics processors and a combination of various control chips, etc., and executes various functions of the electronic device and processes data by running or executing programs or modules stored in the memory 11 (for example, executing a program for calculating the optimal printing and dyeing time for textiles, etc.), and calling data stored in the memory 11.

[0158] The memory 11 includes at least one type of readable storage medium. The memory 11 can be used not only to store application software and various data installed in the electronic device, such as the code of the optimal printing and dyeing time calculation program for textiles, but also to temporarily store data that has been output or is to be output.

[0159] The communication bus 12 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus is configured to realize connection and communication between the memory 11 and at least one processor 10, etc.

[0160] The communication interface 13 is used for communication between the electronic device and other devices, and includes a network interface and a user interface.

[0161] The figure only shows an electronic device with components. Those skilled in the art will understand that the structure shown in the figure does not constitute a limitation on the electronic device, and may include fewer or more components than shown in the figure, or combine certain components, or arrange the components differently.

[0162] For example, although not shown, the electronic device may also include a power source (such as a battery) for supplying power to each component. Preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that the power management device can realize functions such as charging management, discharging management, and power consumption management. The power source may also include one or more DC or AC power sources, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

[0163] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited to this structure.

[0164] The page quick configuration program customized for a customer stored in the memory 11 of the electronic device is a combination of multiple instructions. When running in the processor 10, it can achieve:

[0165] Obtain user needs, behavior data, and an accessories library, encrypt and upload the user needs and behavior data to a preset blockchain, obtain a smart contract, and use the smart contract to extract basic accessories from the accessories library according to the questionnaire requirements in the user needs;

[0166] Performing semantic analysis on the supplementary requirements in the user requirements to obtain supplementary information requirements, and using the supplementary information requirements to filter out supplementary accessories from the accessories library;

[0167] Calculating the user's actual accessory usage probability according to the behavior data, and using the user's actual accessory usage probability to weight the supplementary accessories and the basic accessories to obtain accessory information to be processed;

[0168] A personalized page is constructed according to the accessory information to be processed to obtain a customized page.

[0169] Specifically, the specific implementation method of the processor 10 for the above instructions can refer to the description of the relevant steps in the corresponding embodiment of the accompanying drawings, which will not be repeated here.

[0170] Furthermore, if the module / unit integrated in the electronic device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, and a read-only memory (ROM).

[0171] The present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor of an electronic device, the computer program can implement:

[0172] Obtain user needs, behavior data, and an accessories library, encrypt and upload the user needs and behavior data to a preset blockchain, obtain a smart contract, and use the smart contract to extract basic accessories from the accessories library according to the questionnaire requirements in the user needs;

[0173] Performing semantic analysis on the supplementary requirements in the user requirements to obtain supplementary information requirements, and using the supplementary information requirements to filter out supplementary accessories from the accessories library;

[0174] Calculating the user's actual accessory usage probability according to the behavior data, and using the user's actual accessory usage probability to weight the supplementary accessories and the basic accessories to obtain accessory information to be processed;

[0175] A personalized page is constructed according to the accessory information to be processed to obtain a customized page.

[0176] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, media and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative, for example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

[0177] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0178] In addition, each functional module in each embodiment of the present invention may be integrated into one processing unit, each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0179] It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0180] Therefore, no matter from which point of view, the embodiments should be regarded as illustrative and non-restrictive, and the scope of the present invention is not limited only according to the above description, and it is intended that all changes within the meaning and scope of equivalent elements within the scope of protection are included in the present invention.

[0181] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Among them, artificial intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0182] In addition, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices stated in the system can also be implemented by one unit or device through software or hardware. The words first, second, etc. are used to indicate names, and do not indicate any particular order.

[0183] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for quickly configuring a customized page, characterized in that: The method comprises: Obtain user needs, behavior data, and an accessories library, encrypt and upload the user needs and behavior data to a preset blockchain, obtain a smart contract, and use the smart contract to extract basic accessories from the accessories library according to the questionnaire requirements in the user needs; Performing semantic analysis on the supplementary requirements in the user requirements to obtain supplementary information requirements, and using the supplementary information requirements to filter out supplementary accessories from the accessories library; Calculating the user's actual accessory usage probability according to the behavior data, and using the user's actual accessory usage probability to weight the supplementary accessories and the basic accessories to obtain accessory information to be processed; A personalized page is constructed according to the accessory information to be processed to obtain a customized page.

2. The method for quickly configuring a customized page according to claim 1, characterized in that: The user demand and behavior data are encrypted and uploaded to the preset blockchain to obtain a smart contract, including: Encrypting the user demand and the behavior to obtain encrypted data; Encapsulating the encrypted data to obtain a blockchain transaction; Uploading the blockchain transaction to the blockchain to obtain uploaded data; A smart contract is generated based on the uploaded data.

3. The method for quickly configuring a customized page according to claim 1, characterized in that: The extracting basic accessories from the accessories library according to the questionnaire requirements in the user requirements by using the smart contract includes: Utilize the smart contract to analyze the questionnaire requirements and obtain accessory features; Conditionally matching the accessory feature with the accessory library to obtain accessory information; The accessory information is used to sort the accessory features to obtain a basic accessory.

4. The method for quickly configuring a customized page according to claim 1, characterized in that: The semantic analysis of the supplementary requirements in the user requirements to obtain the supplementary information requirements includes: Performing word segmentation and part-of-speech tagging on the supplementary demand to obtain a word segmentation phrase; Performing syntactic analysis on the supplementary demand using the segmented phrase to obtain a syntactic tree; Performing entity relationship mapping on the segmented phrases using the supplementary requirements to obtain key entity concepts; Using the supplementary requirements and the key entity concepts, the segmented phrases are labeled with semantic roles to obtain role objects; Constructing a syntax tree using the role object, the key entity concept and the syntax tree; Performing logical form representation on the syntax tree to obtain a logical form; The logical form is semantically transformed to obtain supplementary information requirements.

5. The method for quickly configuring a customized page according to claim 4, characterized in that: The step of constructing a syntax tree using the role object, the key entity concept and the syntax tree includes: Using the key entity concept to add labels to the syntax tree to obtain a basic syntax tree; Structural adjustment is performed on the role object and the basic syntax tree to obtain an event structure; Relation edges are added to the event structure to obtain a syntax tree.

6. The method for quickly configuring a customized page according to claim 4, characterized in that: The step of performing logical form representation on the syntax tree to obtain a logical form includes: Extracting logical atoms from the syntax tree to obtain basic units; Convert the data nodes and network edges in the syntax tree into logical expressions using the basic units; Quantitatively expressing the logical expression to obtain a quantified result; Converting the logical expression into a logical structure using the syntax tree and the quantization result; The logical structure is equivalently transformed to obtain a logical form.

7. The method for quickly configuring a customized page according to claim 1, characterized in that: The calculating the actual accessory usage probability of the user according to the behavior data includes: Performing feature screening on the behavior data to obtain relevant features; Constructing a sparse matrix according to the relevant features, the basic accessories and the supplementary accessories; The sparse matrix is ​​decomposed to obtain a user preference matrix and an accessory feature matrix, wherein the matrix decomposition is performed using the following formula: R=U∑V T Where R is a sparse matrix, U is a user preference vector matrix, V is an accessory feature vector matrix, T is a matrix transpose operation, and ∑ is a preset diagonal matrix; Calculating predicted scores of the basic accessories and the supplementary accessories using the user preference matrix and the accessory feature matrix; The predicted score is converted into the user's actual accessory usage probability.

8. The method for quickly configuring a customized page according to claim 1, characterized in that: The step of constructing a personalized page according to the to-be-processed accessory information to obtain a customized page includes: Sorting the to-be-processed accessory information by weight to obtain a sorting result; Using the sorting result, each accessory in the to-be-processed accessory information is matched with each position in the pre-acquired page template to obtain a corresponding result; According to the corresponding result, the interface information of the accessory to be processed is used to replace the interface information at the corresponding position of the page template to obtain a customized page.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the customer-customized page rapid configuration method as described in any one of claims 1 to 8.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method for quickly configuring a page customized for a customer as described in any one of claims 1 to 8 is implemented.

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