Service association method, device, equipment and storage medium for e-government

Abstract

The present invention discloses a service association method, service association apparatus, service association device, and storage medium for e-government, belonging to the fields of computer software and information service technology. The method comprises: obtaining multiple service items corresponding to different business systems; extracting multiple first knowledge elements corresponding to the multiple service items and generating a first knowledge base of multiple first knowledge elements; associating the first knowledge elements corresponding to service items belonging to the same service category in the first knowledge base as second knowledge elements and generating a second knowledge base of multiple second knowledge elements; and upon receiving a consultation instruction, outputting service guidance information corresponding to the consultation instruction based on the second knowledge base. The present invention aims to improve the integrity of intelligent customer service feedback information and enhance the effectiveness of service retrieval and service response.

Description

Technical Field

[0001] The present invention relates to the field of computer software and information service technology, and in particular to a service association method, a service association apparatus, a service association device and a storage medium for e-government. Background Art

[0002] With the development of internet technology, a wide variety of services are increasingly being provided to users through internet-based channels. However, with the continuous updating of services, the current classification method, which relies on manual classification to individually label services, can easily lead to an excessive number of services under certain categories, while some types are effectively abandoned. Or, due to excessive categorization, two similar services are classified into different categories, making service classification and management difficult. Consequently, when users consult services through intelligent customer service, it is difficult for them to select services that meet their needs from the chaotically classified services. This results in insufficient service information being fed back to users, affecting the effectiveness of intelligent customer service's service retrieval and response. Summary of the Invention

[0003] The main purpose of the present invention is to provide a service association method for e-government, aiming to improve the integrity of intelligent customer service feedback information and improve service retrieval and service response effects.

[0004] To achieve the above-mentioned object, the present invention provides a service association method for e-government, which comprises the following steps:

[0005] Obtain multiple service items corresponding to different business systems;

[0006] extracting a plurality of first knowledge elements corresponding to a plurality of the service items, and generating a first knowledge base of the plurality of the first knowledge elements;

[0007] Associating the first knowledge elements corresponding to service items belonging to the same service category in the first knowledge base as second knowledge elements, and generating a second knowledge base of multiple second knowledge elements;

[0008] When a consultation instruction is received, service guidance information corresponding to the consultation instruction is output according to the second knowledge base.

[0009] Optionally, the step of associating the first knowledge elements corresponding to service items belonging to the same service category in the first knowledge base as second knowledge elements includes:

[0010] Performing semantic analysis on the first knowledge element in the first knowledge base to obtain a semantic analysis result;

[0011] According to the semantic analysis result, the first knowledge elements corresponding to the service items belonging to the same service category in the first knowledge base are associated as corresponding second knowledge elements.

[0012] Optionally, the first knowledge element includes service information corresponding to a service item, and the step of performing semantic analysis on the first knowledge element in the first knowledge base to obtain a semantic analysis result includes:

[0013] Extracting bag-of-words data of service information from the first knowledge element;

[0014] Performing TF-IDF conversion on the bag-of-words data to obtain a feature vector corresponding to the first knowledge element;

[0015] The similarities between the first knowledge elements are determined based on the feature vectors of the first knowledge elements, and the semantic analysis result includes the similarities between the first knowledge elements.

[0016] Optionally, the step of associating the first knowledge elements corresponding to service items belonging to the same service category in the first knowledge base as corresponding second knowledge elements according to the semantic analysis result includes:

[0017] Determine that the first knowledge element whose similarity is greater than or equal to a preset threshold is the first knowledge element corresponding to the service item belonging to the same service category, and associate the corresponding first knowledge element as the corresponding second knowledge element.

[0018] Optionally, the step of extracting a plurality of first knowledge elements corresponding to a plurality of the service items and generating a first knowledge base of the plurality of first knowledge elements includes:

[0019] Extracting service information of each service item, wherein the service information includes concept information, relationship information, and problem information;

[0020] generating the first knowledge element corresponding to the concept information, the relationship information, and the question information;

[0021] Determine the association relationship between the plurality of first knowledge elements according to a preset rule;

[0022] generating the first knowledge base according to the association relationship between the first knowledge element and the first knowledge element;

[0023] The preset rule includes that at least one of the concept information, relationship information and question information of at least two of the first knowledge elements having an associated relationship is the same.

[0024] Optionally, the first knowledge base includes a plurality of first knowledge elements and association relationships between the first knowledge elements, and the step of associating the first knowledge elements corresponding to service items belonging to the same service category in the first knowledge base as second knowledge elements and generating a second knowledge base of the plurality of second knowledge elements includes:

[0025] Performing semantic analysis on the first knowledge element in the first knowledge base to obtain a semantic analysis result;

[0026] Associating the first knowledge elements corresponding to service items belonging to the same service category in the first knowledge base into corresponding second knowledge elements according to the semantic analysis result and the association relationship;

[0027] Determine the association relationship between the corresponding second knowledge element and other second knowledge elements according to the association relationship;

[0028] The second knowledge base is generated according to the association relationship between the second knowledge element and the second knowledge element.

[0029] Optionally, when a consultation instruction is received, the step of outputting service guidance information corresponding to the consultation instruction according to the second knowledge base includes:

[0030] Determine the target service identifier according to the consultation instruction;

[0031] Determine that the second knowledge element associated with the target service identifier in the second knowledge base is the target knowledge element, and generate an introduction page and an introduction page link based on the service information of the service item corresponding to the target knowledge element, and the service guidance information includes the introduction page and the introduction page link.

[0032] In addition, in order to achieve the above-mentioned purpose, the present application also proposes a service association device, which includes:

[0033] The acquisition module is used to obtain multiple service items corresponding to different business systems;

[0034] a processing module configured to extract a plurality of first knowledge elements corresponding to the plurality of service items and generate a first knowledge base of the plurality of first knowledge elements; associate the first knowledge elements corresponding to service items belonging to the same service category in the first knowledge base as second knowledge elements and generate a second knowledge base of the plurality of second knowledge elements;

[0035] The consultation module is used to output service guidance information corresponding to the consultation instruction according to the second knowledge base when a consultation instruction is received.

[0036] In addition, in order to achieve the above-mentioned purpose, the present application also proposes a service association device, which includes: a memory, a processor, and an e-government-oriented service association program stored on the memory and runnable on the processor, and the e-government-oriented service association program is configured to implement the steps of the e-government-oriented service association method as described above.

[0037] In addition, in order to achieve the above-mentioned purpose, the present application also proposes a storage medium, on which a service association program for e-government is stored. When the service association program for e-government is executed by a processor, the steps of the service association method for e-government as described in any of the above items are implemented.

[0038] The present invention proposes a service association method for e-government, which obtains multiple service items corresponding to different business systems, extracts multiple first knowledge elements corresponding to the multiple service items, and generates a first knowledge base of multiple first knowledge elements, preliminarily organizes the information of the multiple service items, and then associates the first knowledge elements corresponding to the service items belonging to the same service category in the first knowledge base as second knowledge elements, and generates a second knowledge base of multiple second knowledge elements, and associates the information of the service items that actually belong to the same service category, so that when a consultation instruction is received, the service guidance information corresponding to the consultation instruction is output according to the second knowledge base. Compared with the current service classification, the present application organizes and associates multiple service items through the first knowledge element and the second knowledge element, so that the consultation instruction for the intelligent customer service can extract the information of the organized and associated service items according to the second knowledge base, provide users with complete service guidance information, and improve the service retrieval and service answering effects of the intelligent customer service. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 A schematic diagram of the hardware structure involved in the operation of an embodiment of the service-related device of the present invention;

[0040] Figure 2 A flow chart of an embodiment of a service association method for e-government affairs according to the present invention;

[0041] Figure 3 A flowchart of another embodiment of the service association method for e-government of the present invention;

[0042] Figure 4 This is a flow chart of another embodiment of the service association method for e-government affairs of the present invention;

[0043] Figure 5 A schematic diagram of devices involved in the operation of an embodiment of a service association device of the present invention;

[0044] Figure 6A reference diagram of the first knowledge element of the e-government service association method of the present invention;

[0045] Figure 7 A reference diagram of a first knowledge base of the e-government service association method of the present invention;

[0046] Figure 8 This is a reference diagram of the second knowledge base of the e-government service association method of the present invention.

[0047] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0048] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0049] The embodiment of the present invention provides a service association device. Figure 1 As shown, the service-associated device may include: a processor 1001, such as a central processing unit, a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to implement connection and communication between these components. The user interface 1003 may include a display screen and an input unit such as a keyboard. Optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface. The memory 1005 may be a high-speed random access memory or a stable non-volatile memory, such as a disk storage device. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0050] Those skilled in the art will understand that Figure 1 The structure shown in the figure does not constitute a limitation on the service-associated device. The service-associated device may also include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0051] like Figure 1 As shown, the memory 1005 as a storage medium may include a service-related program for e-government. Figure 1 In the service association device shown, the network interface 1004 is mainly used for data communication with other devices; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 can be used to call the e-government service association program stored in the memory 1005, and execute the steps of the e-government service association method provided by the embodiment of the present invention.

[0052] The embodiment of the present invention also provides a service association method for e-government. Figure 2 , an embodiment of the service association method for e-government of this application is proposed. In this embodiment, the service association method for e-government includes the following steps:

[0053] Step S10, obtaining multiple service items corresponding to different business systems;

[0054] In this embodiment, the method is mainly applied to an application system that provides e-government services to users. The application system of the e-government service includes multiple business function modules, and the multiple business function modules respectively form multiple different business systems. Different business systems can be used to provide different services, and each service has a corresponding service item with relevant information recorded. Accordingly, different business systems also correspond to different multiple service items, and the service items of related services in each different business system are obtained.

[0055] Step S20, extracting a plurality of first knowledge elements corresponding to a plurality of the service items, and generating a first knowledge base of the plurality of the first knowledge elements;

[0056] Optionally, the information in the above-mentioned service items is defined as service information, and the corresponding first knowledge element is extracted and generated based on the service information of each service, which is equivalent to generating the corresponding first knowledge element for each service. The knowledge element is an indivisible knowledge unit with complete knowledge expression. In this embodiment, each first knowledge element contains the relevant information of a service in the above-mentioned business system, and a first knowledge base of the first knowledge element is generated on this basis. The first knowledge base is a database for storing the first knowledge element. Specifically, when generating the first knowledge element, a corresponding first identifier can be generated for each first knowledge element, and the first identifier is stored in the first knowledge base as an index, and the service information in each first knowledge element is stored as the associated information of the first identifier.

[0057] Step S30, associating the first knowledge elements corresponding to service items belonging to the same service category in the first knowledge base as second knowledge elements, and generating a second knowledge base of multiple second knowledge elements;

[0058] In actual scenarios, the services of the business system will be updated and adjusted, and new services will be continuously launched based on the original services. Therefore, there are many services that are classified as different services due to certain differences in service information or inconsistent text expressions. They actually belong to the same service category. The method of this embodiment includes organizing and associating services for the above situations.

[0059] Furthermore, based on the service information of each first knowledge element in the first knowledge base, service items that actually belong to the same service category are identified, and their corresponding first knowledge elements are the first knowledge elements that belong to the same service category. The corresponding first knowledge elements are mutually associated to form second knowledge elements, and a second knowledge base of second knowledge elements is generated on this basis. Specifically, a corresponding second identifier can be generated for each second knowledge element, and the second identifier is used as an index to store it in the second knowledge base, and the first identifier of the corresponding first knowledge element is stored as the associated information of the second identifier, or the service information of the mutually associated first knowledge elements is integrated to form the service information of the corresponding second knowledge element, and the integrated service information is stored as the associated information of the second identifier; both of the above two methods can determine the service information of multiple services corresponding to each second knowledge element through the index of the second identifier and the first identifier.

[0060] Step S40: When a consultation instruction is received, service guidance information corresponding to the consultation instruction is output according to the second knowledge base.

[0061] Consultation instructions are instructions sent by users when they use the service retrieval or service Q&A functions of intelligent customer service. In addition to the above-mentioned service retrieval or service Q&A, consultation instructions can also be related to intelligent customer service functions such as service association, service recommendation and automatic forms. There is no limitation here. It is actually an instruction to consult a certain category of service and obtain relevant introduction information about the service.

[0062] In the above steps, a second knowledge base of the second knowledge element is generated, the category of the service that the user wants to consult is determined according to the consultation instruction, the relevant service information of the service of this category is retrieved and extracted from the second knowledge base, and the corresponding service guidance information is generated, and the service guidance information is output to the intelligent customer service function port, so that the user can receive feedback information on service retrieval or service Q&A from the intelligent customer service.

[0063] An embodiment of the present invention proposes a service association method for e-government, which obtains multiple service items corresponding to different business systems, extracts multiple first knowledge elements corresponding to the multiple service items, and generates a first knowledge base of multiple first knowledge elements, preliminarily organizes the information of the multiple service items, and then associates the first knowledge elements corresponding to the service items belonging to the same service category in the first knowledge base as second knowledge elements, and generates a second knowledge base of multiple second knowledge elements, and associates the information of service items that actually belong to the same service category, so that when a consultation instruction is received, the service guidance information corresponding to the consultation instruction is output according to the second knowledge base. Compared with the current service classification, the present application organizes and associates multiple service items through the first knowledge element and the second knowledge element, so that the consultation instruction for the intelligent customer service can extract the information of the organized and associated service items according to the second knowledge base, provide users with complete service guidance information, and improve the service retrieval and service answering effects of the intelligent customer service.

[0064] Furthermore, in this embodiment, when a consultation instruction is received, the step of outputting service guidance information corresponding to the consultation instruction according to the second knowledge base includes:

[0065] Determine the target service identifier according to the consultation instruction;

[0066] Determine that the second knowledge element associated with the target service identifier in the second knowledge base is the target knowledge element, and generate an introduction page and an introduction page link based on the service information of the service item corresponding to the target knowledge element, and the service guidance information includes the introduction page and the introduction page link.

[0067] A service identifier is a mark used to categorize services. It can be a keyword for the corresponding service category, such as "social security" or "recruitment," or an identifier composed of letters and numbers. When a user uses the intelligent customer service system, the intelligent customer service system can determine the target service category based on the question text entered or the consultation option selected by the user, and add the target service identifier corresponding to the target service category to the consultation instruction.

[0068] It should be noted that before receiving the consultation instruction of the intelligent customer service, the second knowledge base generated based on this embodiment needs to first assign its corresponding service identifier to each second knowledge element in the second knowledge base, that is, each second knowledge element corresponds to a service category. At the same time, in order to facilitate users to view the various service information corresponding to the second knowledge element, the service information corresponding to the second knowledge element is extracted and integrated into an introduction page that is easy for users to read, and the introduction page and the link to the introduction page are associated with the service identifier of the second knowledge element. Based on this, after determining the target knowledge element according to the target service identifier corresponding to the consultation instruction, the introduction page and the introduction page link related to the corresponding service category can be further matched and directly output to the intelligent customer service for users to read.

[0069] By pre-generating an introduction page for the service based on the second knowledge base and associating a link to the introduction page, the information of each service is organized, which helps users quickly obtain the introduction page of the feedback when using intelligent customer service. The introduction page can also be used to improve the user's reading experience of the intelligent customer service feedback content, thereby improving the service retrieval and service response effects of the intelligent customer service.

[0070] Furthermore, based on the above embodiment, another embodiment of the service association method for e-government of this application is proposed. Figure 3 The step of associating the first knowledge element corresponding to the service items belonging to the same service category in the first knowledge base as the second knowledge element includes:

[0071] Step S31, performing semantic analysis on the first knowledge element in the first knowledge base to obtain a semantic analysis result;

[0072] Considering that services of the same service category may be classified as different services due to inconsistent text expressions, semantic analysis can be used to analyze the service information corresponding to the first knowledge element, and the first knowledge elements with the same semantics can be determined based on the semantic analysis results.

[0073] Step S32: Associating the first knowledge elements corresponding to the service items belonging to the same service category in the first knowledge base into corresponding second knowledge elements according to the semantic analysis result.

[0074] Based on the results of semantic analysis, the semantic similarity of the service information corresponding to each first knowledge element can be determined, so as to judge whether different first knowledge elements belong to the same service category; semantic similarity analysis is performed on every two first knowledge elements in the first knowledge base to determine a number of first knowledge elements corresponding to each service category. The number of associated first knowledge elements under each service category can be greater than or equal to one, and the first knowledge elements belonging to the same service category are associated as corresponding second knowledge elements.

[0075] By performing semantic analysis on the first knowledge element, the similarity of service information can be analyzed from a semantic perspective, thereby achieving association and integration of first knowledge elements that actually belong to the same service category, thereby improving the accuracy of service classification.

[0076] Furthermore, in this embodiment, the first knowledge element includes service information corresponding to a service item, and the step of performing semantic analysis on the first knowledge element in the first knowledge base to obtain a semantic analysis result includes:

[0077] Extracting bag-of-words data of service information from the first knowledge element;

[0078] Performing TF-IDF conversion on the bag-of-words data to obtain a feature vector corresponding to the first knowledge element;

[0079] The similarities between the first knowledge elements are determined based on the feature vectors of the first knowledge elements, and the semantic analysis result includes the similarities between the first knowledge elements.

[0080] The service information specifically includes the conceptual information, relationship information and problem information of the corresponding service. Furthermore, the conceptual information includes the item code, item type and item name of the corresponding service; the relationship information includes the basis for exercising the corresponding service, the basis for charging, the acceptance conditions and the commitment period; the problem information includes the processing department, application materials, service forms and standard documents of the corresponding service; when performing semantic analysis on the first knowledge element, semantic analysis is performed on all the above information.

[0081] Specifically, the service information is corpus cleaned, and the bag-of-words data of the above-mentioned information is extracted. The bag-of-words data is specifically a bag-of-words model. In the bag-of-words model, the text is recorded in the form of a bag of words, and the frequency of occurrence of various words in the above-mentioned information is recorded. Furthermore, the bag-of-words data is subjected to a TF-IDF transformation, which is equivalent to extracting the features of the bag-of-words model. The extracted features are the feature vectors corresponding to the first knowledge elements. For the feature vectors corresponding to each first knowledge element, the similarity of each two first knowledge element feature vectors is compared respectively. The method for comparing the similarity can be to calculate the cosine similarity, and the similarity between the feature vectors is determined by the specific value of the cosine similarity, thereby characterizing the similarity between the first knowledge elements.

[0082] Through the specific bag-of-words model, TF-IDF transformation and similarity calculation between feature vectors, specific semantic analysis of the first knowledge element is achieved, the similarity of different first knowledge elements in the semantic direction is numerically compared, and the accuracy of associating the first knowledge element with the second knowledge element is improved, thereby improving the accuracy of service classification.

[0083] Furthermore, in this embodiment, the step of associating the first knowledge elements corresponding to the service items belonging to the same service category in the first knowledge base as corresponding second knowledge elements according to the semantic analysis result includes:

[0084] Determine that the first knowledge element whose similarity is greater than or equal to a preset threshold is the first knowledge element corresponding to the service item belonging to the same service category, and associate the corresponding first knowledge element as the corresponding second knowledge element.

[0085] A preset threshold is set for the similarity between the feature vectors of the first knowledge elements as an indicator for evaluating the similarity. When the similarity between the feature vectors of two first knowledge elements is greater than or equal to the preset threshold, the two first knowledge elements are determined to belong to the same service category and should be associated as corresponding second knowledge elements. For ease of explanation, the association condition is defined as a similarity greater than or equal to the preset threshold.

[0086] It should be noted that the analysis of the similarity between the characteristic vectors of the first knowledge elements is based on every two first knowledge elements. Therefore, a first knowledge element may simultaneously meet the association conditions with more than or equal to two other first knowledge elements, but the other first knowledge elements do not meet the association conditions with each other. In this case, since the other first knowledge elements can meet the association conditions with the first knowledge element, they can still be judged as belonging to the same service category and associated as corresponding second knowledge elements; for example, there are first knowledge elements A, B, and C, the similarity between A and B meets the association conditions, the similarity between B and C meets the association conditions, but the similarity between A and C does not meet the association conditions, then A, B, and C can still be judged to belong to the same service category and associated as a second knowledge element D including the service information of A, B, and C.

[0087] By evaluating the similarity between first knowledge elements according to a preset threshold, the accuracy of semantically analyzing similar first knowledge elements is improved, and the accuracy of associating first knowledge elements as second knowledge elements is improved, thereby improving the accuracy of service classification.

[0088] Furthermore, based on the above embodiment, another embodiment of the service association method for e-government of this application is proposed. Figure 4 The step of extracting a plurality of first knowledge elements corresponding to a plurality of the service items and generating a first knowledge base of the plurality of the first knowledge elements includes:

[0089] Step S21, extracting service information of each service item, wherein the service information includes concept information, relationship information, and problem information;

[0090] In this embodiment, when generating the first knowledge element and the first knowledge base, an association relationship between the first knowledge elements can be simultaneously established. This association relationship is determined based on the service information of each first knowledge element. Optionally, when generating the corresponding first knowledge element based on the service item, the service information of the service item is first extracted, including the aforementioned concept information, relationship information, and question information.

[0091] Step S22, generating the first knowledge element according to the concept information, the relationship information and the question information;

[0092] In a knowledge element, generally, five aspects of content may be included: name, content, field, source, and link. In this embodiment, each first knowledge element includes concept information, relationship information, and question information. The specific content of the concept information, relationship information, and question information may refer to the above embodiment. The specific content may correspond to the above five aspects: name, content, field, source, and link. Thus, the first knowledge element corresponding to the service item is generated according to the service information. Figure 6 .

[0093] Step S23, determining an association relationship between the plurality of first knowledge elements according to a preset rule, wherein the preset rule includes that at least two of the first knowledge elements having an association relationship have at least one of the same concept information, relationship information, and question information;

[0094] Furthermore, after generating the first knowledge elements, the association relationship between the first knowledge elements is determined based on the conceptual information, relationship information and problem information of each first knowledge element. Since the purpose of associating the first knowledge elements is still to generate the second knowledge element, that is, to associate the first knowledge elements that have inconsistent expressions but still belong to the same category, therefore, we can first directly compare whether the conceptual information, relationship information and problem information between the first knowledge elements are the same. When at least one of them is the same, it can be determined that the corresponding two first knowledge elements have an association relationship.

[0095] In addition, further judgment rules can be set on how to determine whether the conceptual information, relationship information and problem information of two first knowledge elements are the same, and whether they are the same is determined according to the first rule corresponding to the conceptual information, whether they are the same is determined according to the second rule corresponding to the relationship information, and whether they are the same is determined according to the third rule corresponding to the problem information; exemplarily, the first rule includes that when the matter codes, matter types and matter names of the two first knowledge elements are the same, their conceptual information can be determined to be the same; the second rule includes that when the exercise basis, charging basis and acceptance conditions of the two first knowledge elements are the same, but the commitment periods are different, their relationship information can also be determined to be the same.

[0096] Step S24, generating the first knowledge base according to the association relationship between the first knowledge element and the first knowledge element;

[0097] Optionally, when generating the first knowledge element based on the first knowledge element, the association relationship between each first knowledge element and other first knowledge elements can also be stored as an attribute of the first knowledge element, so that the association relationship is also recorded to generate a first knowledge base including the association relationship between the first knowledge element and the first knowledge element; Figure 7 , Figure 7 In the example, the first knowledge element a has an association relationship with the first knowledge elements b and d, and the first knowledge element f has an association relationship with the first knowledge elements c and e.

[0098] By determining the association relationship between the first knowledge elements, it is helpful to understand the connection between various service items based on the first knowledge base, thereby improving the accuracy of further associating the second knowledge element based on the first knowledge element.

[0099] Furthermore, in this embodiment, the first knowledge base includes a plurality of first knowledge elements and association relationships between the first knowledge elements. The step of associating the first knowledge elements corresponding to service items belonging to the same service category in the first knowledge base as second knowledge elements and generating a second knowledge base of the plurality of second knowledge elements includes:

[0100] Performing semantic analysis on the first knowledge element in the first knowledge base to obtain a semantic analysis result;

[0101] Associating the first knowledge elements corresponding to service items belonging to the same service category in the first knowledge base into corresponding second knowledge elements according to the semantic analysis result and the association relationship;

[0102] Determine the association relationship between the corresponding second knowledge element and other second knowledge elements according to the association relationship;

[0103] The second knowledge base is generated according to the association relationship between the second knowledge element and the second knowledge element.

[0104] Specifically, a semantic analysis is performed on the first knowledge elements to determine the semantic analysis results of the similarity between the first knowledge elements. The semantic analysis method for the first knowledge elements can refer to the above embodiment and will not be described in detail here. The similarity of the feature vectors between the first knowledge elements with associated relationships is preferentially compared. After the comparison is completed based on the associated relationship, the first knowledge elements with other non-associated first knowledge elements are compared based on the comparison results to determine the first knowledge elements belonging to the same service category, and then the corresponding second knowledge elements are generated.

[0105] It should be noted that the first knowledge element with an association relationship described in this embodiment and the association of the first knowledge element to generate the second knowledge element are two different associations. The association relationship of the first knowledge element only refers to the relationship established between the first knowledge elements because at least one of the concept information, relationship information and problem information is the same. Among the multiple first knowledge elements associated as the second knowledge element, not necessarily each first knowledge element has an association relationship.

[0106] Furthermore, the association relationship between the second knowledge element and other second knowledge elements is determined based on the association relationship between the first knowledge element corresponding to the second knowledge element and other first knowledge elements. For example, there is a second knowledge element A, which corresponds to first knowledge elements a and b, and there is an association relationship between first knowledge element a and first knowledge element c, and first knowledge element c corresponds to another second knowledge element B, but does not correspond to second knowledge element A, then it can be determined that second knowledge elements A and B have an association relationship. Then, based on the association relationship between the second knowledge element and the second knowledge element, a second knowledge base is generated. The method for generating the first knowledge base in this embodiment can be referred to and will not be elaborated here; refer to Figure 8 , Figure 8 by Figure 7 The first knowledge base shown is used as a basis to generate a corresponding second knowledge base. Figure 8 The second knowledge base includes second knowledge elements A and B, which respectively include first knowledge elements a, b, d and first knowledge elements c, e, f.

[0107] By determining the first knowledge element belonging to the same service category based on the association relationship, the processing efficiency of generating the second knowledge element based on the first knowledge element is improved, and the second knowledge element generated still has the corresponding association relationship. The service category corresponding to the second knowledge element with the association relationship can be used as a service category of a similar type. When processing the consultation instruction, it can be determined according to the consultation instruction whether to output the information of the service corresponding to the target service identifier or the information of the service of a similar type, thereby improving the integrity of the service guidance information feedback by the intelligent customer service.

[0108] In addition, the embodiment of the present invention also proposes a service association device, referring to Figure 5 The service association device includes: an acquisition module 100, a processing module 200 and a consulting module 300, wherein:

[0109] An acquisition module 100 is used to acquire multiple service items corresponding to different business systems;

[0110] Processing module 200 is configured to extract a plurality of first knowledge elements corresponding to a plurality of the service items and generate a first knowledge base of the plurality of the first knowledge elements; associate the first knowledge elements corresponding to the service items belonging to the same service category in the first knowledge base as second knowledge elements and generate a second knowledge base of the plurality of the second knowledge elements;

[0111] The consultation module 300 is configured to output service guidance information corresponding to the consultation instruction according to the second knowledge base when a consultation instruction is received.

[0112] In addition, an embodiment of the present invention further proposes a storage medium on which a service association program for e-government is stored. When the service association program for e-government is executed by a processor, the relevant steps of any embodiment of the above service association method for e-government are implemented.

[0113] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or system comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or system. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or system comprising the element.

[0114] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0115] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better embodiment. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in each embodiment of the present invention.

[0116] The above are only preferred embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A service association method for e-government, characterized in that: The service association method comprises the following steps: Obtain multiple service items corresponding to different business systems; extracting a plurality of first knowledge elements corresponding to a plurality of the service items, and generating a first knowledge base of the plurality of the first knowledge elements; Associating the first knowledge elements corresponding to service items belonging to the same service category in the first knowledge base as second knowledge elements, and generating a second knowledge base of multiple second knowledge elements; When a consultation instruction is received, service guidance information corresponding to the consultation instruction is output according to the second knowledge base.

2. The service association method for e-government according to claim 1, characterized in that: The step of associating the first knowledge element corresponding to the service items belonging to the same service category in the first knowledge base as a second knowledge element includes: Performing semantic analysis on the first knowledge element in the first knowledge base to obtain a semantic analysis result; According to the semantic analysis result, the first knowledge elements corresponding to the service items belonging to the same service category in the first knowledge base are associated as corresponding second knowledge elements.

3. The service association method for e-government as claimed in claim 2, characterized in that: The first knowledge element includes service information corresponding to a service item, and the step of performing semantic analysis on the first knowledge element in the first knowledge base to obtain a semantic analysis result includes: Extracting bag-of-words data of service information from the first knowledge element; Performing TF-IDF conversion on the bag-of-words data to obtain a feature vector corresponding to the first knowledge element; The similarities between the first knowledge elements are determined based on the feature vectors of the first knowledge elements, and the semantic analysis result includes the similarities between the first knowledge elements.

4. The service association method for e-government as claimed in claim 3, characterized in that: The step of associating the first knowledge elements corresponding to service items belonging to the same service category in the first knowledge base into corresponding second knowledge elements according to the semantic analysis result includes: Determine that the first knowledge element whose similarity is greater than or equal to a preset threshold is the first knowledge element corresponding to the service item belonging to the same service category, and associate the corresponding first knowledge element as the corresponding second knowledge element.

5. The service association method for e-government as claimed in claim 1, characterized in that: The step of extracting a plurality of first knowledge elements corresponding to a plurality of the service items and generating a first knowledge base of the plurality of the first knowledge elements includes: Extracting service information of each service item, wherein the service information includes concept information, relationship information, and problem information; generating the first knowledge element corresponding to the concept information, the relationship information, and the question information; Determine the association relationship between the plurality of first knowledge elements according to a preset rule; generating the first knowledge base according to the association relationship between the first knowledge element and the first knowledge element; The preset rule includes that at least one of the concept information, relationship information and question information of at least two of the first knowledge elements having an associated relationship is the same.

6. The service association method for e-government as claimed in claim 1, characterized in that: The first knowledge base includes a plurality of first knowledge elements and association relationships between the first knowledge elements. The step of associating the first knowledge elements corresponding to service items belonging to the same service category in the first knowledge base as second knowledge elements and generating a second knowledge base of the plurality of second knowledge elements includes: Performing semantic analysis on the first knowledge element in the first knowledge base to obtain a semantic analysis result; Associating the first knowledge elements corresponding to service items belonging to the same service category in the first knowledge base into corresponding second knowledge elements according to the semantic analysis result and the association relationship; Determine the association relationship between the corresponding second knowledge element and other second knowledge elements according to the association relationship; The second knowledge base is generated according to the association relationship between the second knowledge element and the second knowledge element.

7. The e-government service association method according to any one of claims 1 to 6, characterized in that: The step of outputting service guidance information corresponding to the consultation instruction according to the second knowledge base upon receiving the consultation instruction includes: Determine the target service identifier according to the consultation instruction; Determine that the second knowledge element associated with the target service identifier in the second knowledge base is the target knowledge element, and generate an introduction page and an introduction page link based on the service information of the service item corresponding to the target knowledge element, and the service guidance information includes the introduction page and the introduction page link.

8. A service association device, characterized in that: The service association device includes: The acquisition module is used to obtain multiple service items corresponding to different business systems; a processing module configured to extract a plurality of first knowledge elements corresponding to the plurality of service items and generate a first knowledge base of the plurality of first knowledge elements; associate the first knowledge elements corresponding to service items belonging to the same service category in the first knowledge base as second knowledge elements and generate a second knowledge base of the plurality of second knowledge elements; The consultation module is used to output service guidance information corresponding to the consultation instruction according to the second knowledge base when a consultation instruction is received.

9. A service-related device, characterized in that: The service association device includes: a memory, a processor, and an e-government-oriented service association program stored in the memory and executable on the processor, wherein the e-government-oriented service association program is configured to implement the steps of the e-government-oriented service association method as described in any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium stores an e-government-oriented service association program, which, when executed by a processor, implements the steps of the e-government-oriented service association method according to any one of claims 1 to 7.

Images