Equipment document searching method and device, electronic equipment and storage medium

Abstract

The invention discloses an equipment document searching method and device, electronic equipment and a storage medium, and relates to the technical field of document data processing. The method comprises the following steps: acquiring equipment document query information of an equipment document; analyzing the equipment document query information to obtain a query keyword; searching the equipment knowledge graph according to the query keyword to obtain a target equipment body, a target equipment document entity, a target document content entity and a target association relationship among the target equipment body, the target equipment document entity and the target document content entity; and generating and displaying a target device document knowledge graph according to the target device body, the target device document entity, the target document content entity and a target association relationship among the target device body, the target device document entity and the target document content entity. According to the technical scheme provided by the embodiment of the invention, the difficulty and complexity of acquiring the equipment document information are reduced, and the intuition of acquiring the equipment document information is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of document data processing, and in particular to a device document search method, device, electronic device and storage medium. Background Art

[0002] In the field of nuclear power technology, the rapid development of new information technologies represented by the Internet, the Internet of Things, perception networks and social networks has promoted the scale and low cost of equipment document data acquisition, causing the scale of equipment document data to grow explosively. While bringing convenience to data acquisition, it has also brought difficulty and complexity to the acquisition of equipment document information. Summary of the invention

[0003] The present invention provides a device document search method, apparatus, electronic device and storage medium, which reduce the difficulty and complexity of obtaining device document information and improve the intuitiveness of obtaining device document information.

[0004] According to one aspect of the present invention, a device document search method is provided, the method comprising:

[0005] Get device document query information of device document;

[0006] Parsing the device document query information to obtain query keywords;

[0007] According to the query keyword, the device knowledge graph is searched to obtain a target device entity, a target device document entity, a target document content entity, and a target association relationship between the target device entity, the target device document entity, and the target document content entity;

[0008] A target device document knowledge graph is generated and displayed according to the target device ontology, the target device document entity, the target document content entity, and the target association relationship between the target device ontology, the target device document entity and the target document content entity.

[0009] According to another aspect of the present invention, a device document search apparatus is provided, the apparatus comprising:

[0010] A query information acquisition module, used to acquire device document query information of a device document;

[0011] A query information parsing module, used to parse the device document query information to obtain query keywords;

[0012] A target association relationship search module is used to search the device knowledge graph according to the query keyword to obtain a target device entity, a target device document entity, a target document content entity, and a target association relationship between the target device entity, the target device document entity and the target document content entity;

[0013] The device document knowledge graph generation module is used to generate and display the target device document knowledge graph based on the target device entity, the target device document entity, the target document content entity, and the target association relationship between the target device entity, the target device document entity and the target document content entity.

[0014] According to another aspect of the present invention, there is provided an electronic device, the electronic device comprising:

[0015] at least one processor; and

[0016] a memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program executable 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 device document search method described in any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the device document search method described in any embodiment of the present invention when executed.

[0019] According to another aspect of the present invention, a computer program product is provided. The computer program product includes a computer program. When the computer program is executed by a processor, the device document search method according to any embodiment of the present invention is implemented.

[0020] The technical solution of the embodiment of the present invention parses the device document query information to obtain query keywords, searches the device knowledge graph according to the query keywords, obtains the target device entity, the target device document entity, the target document content entity and the target association relationship between the target device entity, the target device document entity and the target document content entity, generates and displays the target device document knowledge graph according to the target device entity, the target device document entity, the target document content entity and the target association relationship between the target device entity, the target device document entity and the target document content entity, and realizes rapid query of the device document content through the device knowledge graph. By generating the device document knowledge graph, the intuitiveness and readability of the device document content are improved, and the association relationship between the device document content and the device document and the device is reflected, which facilitates the subsequent analysis and processing of the device document content.

[0021] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 is a flowchart of a device document search method provided according to Embodiment 1 of the present invention;

[0024] Figure 2 is a flow chart of a device document search method provided according to Embodiment 2 of the present invention;

[0025] Figure 3 is a flow chart of a device document search method provided according to Embodiment 2 of the present invention;

[0026] Figure 4 is a schematic diagram of the structure of a device knowledge graph provided according to Embodiment 2 of the present invention;

[0027] Figure 5 is a structural diagram of a device document search apparatus provided according to Embodiment 3 of the present invention;

[0028] Figure 6 It is a structural schematic diagram of an electronic device for implementing the device document search method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0031] Embodiment 1

[0032] Figure 1 A flowchart of a device document search method provided in Embodiment 1 of the present invention. The embodiment of the present invention is applicable to the case of searching for device documents in the nuclear power field. The method can be performed by a device document search device, which can be implemented in the form of hardware and / or software. The device document search device can be configured in an electronic device that carries a device document search function, such as a client or a server.

[0033] See also Figure 1 The device document search method shown includes:

[0034] S110. Obtain device document query information of the device document.

[0035] The equipment document can be used to record the information of nuclear power equipment. Exemplarily, the equipment document may include overall equipment, main material equipment and auxiliary material equipment, etc. The equipment document query information may be input information when querying the equipment document. The equipment document query information may be used to characterize the query intention of the equipment document query party. Exemplarily, the equipment document query information may be text information, picture information or voice information, etc. Optionally, the equipment document query information may be issued by the equipment document query party. Optionally, the device may have a corresponding front-end page. The equipment document query party may enter the equipment document query information in the search box of the front-end page.

[0036] In an optional embodiment of the present invention, the equipment documents include equipment production documents, equipment operation documents and equipment maintenance documents.

[0037] Equipment production documents can be used to indicate the use of equipment in the production process. Exemplarily, equipment production documents can be the installation manual of the equipment. Equipment operation documents can be used to indicate how to operate the equipment. Exemplarily, equipment operation documents can be the operation manual of the equipment. Equipment maintenance documents can be used to record the equipment maintenance process. Exemplarily, equipment maintenance documents can include the maintenance manual and maintenance work order of the equipment.

[0038] This solution concretizes equipment documents into equipment production documents, equipment operation documents and equipment maintenance documents, selects typical equipment documents, and facilitates the search and processing of equipment documents, further reducing the difficulty and complexity of obtaining equipment document information in the nuclear power field, and further improving the intuitiveness of obtaining equipment document information in the nuclear power field.

[0039] Specifically, the device document query information of the device document input by the device document query party may be obtained.

[0040] S120: Parse the device document query information to obtain query keywords.

[0041] The query keyword can be used to represent the key information of the device document query information.

[0042] Specifically, natural language processing technology may be used to parse the device document query information to obtain query keywords corresponding to the device document information.

[0043] S130. Search the device knowledge graph according to the query keywords to obtain the target device entity, the target device document entity, the target document content entity, and the target association relationship among the target device entity, the target device document entity and the target document content entity.

[0044] The equipment knowledge graph can be used to record and query equipment document information. The equipment knowledge graph can be pre-generated and stored in the device. In the field of nuclear power technology, there are many types of equipment documents involved in the production process. The equipment document information is stored comprehensively in the form of the equipment knowledge graph, which improves the intuitiveness and readability of the equipment document information search. The equipment knowledge graph can include a large number of devices. The target device ontology can represent the target device in the equipment knowledge graph. The target device document entity can represent the target device document of the target device in the equipment knowledge graph. The target document content entity can represent the document content of the target device document in the equipment knowledge graph. The target device can correspond to at least one target device document. The target device document can correspond to at least one target document content. The target association relationship can be used to represent the association relationship between the target device and the target device document in the equipment knowledge graph, or the position relationship between the target device document and the target document content.

[0045] Specifically, according to the query keywords, the device knowledge graph can be searched for entities to obtain the target device entity, the target device document entity, and the target document content entity. The device knowledge graph can be explored for paths to obtain the target association relationship between the target device entity, the target device document entity, and the target document content entity.

[0046] S140. Generate and display a target device document knowledge graph based on the target device ontology, the target device document entity, the target document content entity, and the target association relationship between the target device ontology, the target device document entity, and the target document content entity.

[0047] The target device document knowledge graph may be a knowledge graph corresponding to the target document content of the target device document displayed based on the device document query information. Compared with directly displaying the target document content, displaying the target document content in the form of a knowledge graph makes the target document content more intuitive and more readable. At the same time, it can more clearly display the correlation between the target device, the target device document and the target document content, which facilitates subsequent analysis and processing of the target document content.

[0048] Specifically, the target device ontology, the target device document view and the target document content entity can be generated and displayed. Based on the target association relationship between the target device ontology, the target device document entity and the target document content entity, the target device ontology, the target device document entity and the target document content entity can be connected to generate a target device document knowledge graph and display it.

[0049] In an optional embodiment of the present invention, a target device document knowledge graph is generated and displayed based on a target device entity, a target device document entity, a target document content entity, and a target association relationship between the target device entity, the target device document entity, and the target document content entity, including: obtaining a preset entity display number; filtering the target document content entities according to the preset entity display number to obtain a target display document content entity; generating and displaying a target device document knowledge graph based on the target device entity, the target device document entity, the target display document content entity, and the target association relationship between the target device entity, the target device document entity, and the target display document content entity.

[0050] The preset entity display number can be the number of entities displayed in the preset target device knowledge graph. The preset entity display number can be set and adjusted by the technician according to the display effect. The target display document content entity can be the target document content entity that needs to be displayed. The number of target display document content entities can be the same as or different from the number of target document content entities. The number of target display document content entities can be the preset entity display number. That is, for the best display effect.

[0051] Specifically, a predetermined preset entity display number can be obtained. The target document content entity can be screened according to the preset entity display number. When the number of target document content entities is the preset entity display number, the target document content entity can be directly used as the target display document content entity; when the number of target document content entities is greater than the preset entity display number, the target document content entity is screened according to the degree of association between the target document content entity and the query keyword to obtain the target display document content entity; when the number of target document content entities is less than the preset entity display number, other document content entities are screened according to the degree of association between other document content entities and the query keyword, the number of views, the preset order or a random method, and the screened other document content entities and the target document content entity are used as the target display document content entity; the target device entity, the target device document entity and the target display document content entity can be connected according to the target association relationship between the target device entity, the target device document entity and the target display document content entity to generate a target device document knowledge graph.

[0052] Optionally, the target device document knowledge graph may be displayed while the target device document knowledge graph is being generated.

[0053] Optionally, the target device entity, the target device document entity and the target display document content entity may be displayed first, and then the target device document knowledge graph may be displayed.

[0054] This solution introduces a preset number of entity displays to optimize the display effect.

[0055] The technical solution of the embodiment of the present invention parses the device document query information to obtain query keywords, searches the device knowledge graph according to the query keywords, obtains the target device entity, the target device document entity, the target document content entity and the target association relationship between the target device entity, the target device document entity and the target document content entity, generates and displays the target device document knowledge graph according to the target device entity, the target device document entity, the target document content entity and the target association relationship between the target device entity, the target device document entity and the target document content entity, and realizes rapid query of the device document content through the device knowledge graph. By generating the device document knowledge graph, the intuitiveness and readability of the device document content are improved, and the association relationship between the device document content and the device document and the device is reflected, which facilitates the subsequent analysis and processing of the device document content.

[0056] Embodiment 2

[0057] Figure 2 A flowchart of a device document search method provided for the second embodiment of the present invention. Based on the above embodiments, the present embodiment of the present invention specifies "searching the device knowledge graph according to the query keywords to obtain the target device entity, the target device document entity, the target document content entity, and the target association relationship between the target device entity, the target device document entity and the target document content entity" as "querying each entity in the device knowledge graph according to the query keywords to obtain the target device entity, the target device document entity and the first target document content entity; wherein the first target document content entity corresponds to the query keyword; performing path exploration on the device knowledge graph according to the target device entity, the target device document entity and the first target document content entity; The target device ontology, the target device document entity, the target association relationship between the first target document content entity and the second target document content entity are obtained by searching. By first locating the target device ontology, the target device document entity and the first target document content entity, and then locating the second target document content entity and the target device ontology, the target device document entity, the target document content entity and the target association relationship between the second target document content entity, the accuracy of the target device ontology, the target device document entity, the target document content entity and the target association relationship can be improved, thereby improving the accuracy of the generated target device document knowledge graph. It should be noted that for the parts not described in detail in the embodiments of the present invention, reference can be made to the description of other embodiments.

[0058] See also Figure 2 The device document search method shown includes:

[0059] S210: Obtain device document query information.

[0060] S220: Parse the device document query information to obtain query keywords.

[0061] S230. According to the query keywords, query each entity in the device knowledge graph to obtain the target device entity, the target device document entity and the first target document content entity.

[0062] The first target document content entity can be used to represent the target document content entity directly associated with the query keyword. The first target document content entity corresponds to the query keyword. Based on the query keyword, the first target document content entity can be directly queried.

[0063] Specifically, each entity in the device knowledge graph can be queried based on the query keywords to obtain the target device entity, the target device document entity and the first target document content entity.

[0064] For example, the device document query information may be "the work order content of the backwater valve"; the query keywords may be "backwater valve", "work order" and "work order content". Based on the query keywords, the names of the entities in the device knowledge graph may be retrieved, and the entity named "backwater valve" may be determined as the target device entity; the entity named "work order" may be determined as the target device document entity; and the entity named "work order content" may be determined as the target document content entity.

[0065] In an optional embodiment of the present invention, each entity in the device knowledge graph is queried according to the query keyword to obtain the target device entity, the target device document entity and the first target document content entity, including: searching each device entity in the device knowledge graph according to the device identification contained in the query keyword to obtain the target device entity; searching each device document entity in the device knowledge graph according to the device identification and device document identification contained in the query keyword to obtain the target device document entity; searching each document content entity in the device knowledge graph according to the device identification, device document identification and document content identification contained in the query keyword to obtain the first target document content entity.

[0066] The query keywords may include at least one of a device identifier, a device document identifier, and a document content identifier. The device identifier may be used to uniquely identify the target device. For a device knowledge graph, a large number of devices may be included. The device identifier may be used to locate the target device entity, as well as the device document entity and document content entity associated with the target device. The device document identifier may be used to uniquely identify the target device document. The device document identifier may be used to locate the target device document entity and document content entity associated with the target device document. The document content identifier may be used to uniquely identify the target document content. The document content identifier may be used to locate the target document content entity.

[0067] Optionally, when the device identifier, device document identifier and document content identifier are included in the query keyword, the tag content of each device entity in the device knowledge graph can be searched according to the device identifier included in the query keyword, and the device entity containing the device identifier in the tag content can be determined as the target device entity. The tag content of each device document entity in the device knowledge graph can be searched, and the device document entity containing the device identifier in the tag content can be determined as the device document entity corresponding to the scope to be queried. The tag content of each device document entity corresponding to the scope to be queried in the device knowledge graph can be searched according to the device document identifier included in the query keyword, and the device document entity containing the device document identifier in the tag content can be determined as the target device document entity. The tag content of each device document entity in the device knowledge graph can be searched, and the document content entity containing the device identifier and the device document identifier in the tag content can be determined as the document content entity corresponding to the scope to be queried. The tag content of each document content entity corresponding to the scope to be queried in the device knowledge graph can be searched according to the document content identifier included in the query keyword, and the document content entity containing the document content identifier in the tag content can be determined as the first target document content entity.

[0068] Optionally, when querying for device identification and device document identification contained in the keyword, the label content of each device entity in the device knowledge graph can be searched based on the device identification contained in the query keyword, and the device entity containing the device identification in the label content can be determined as the target device entity. The label content of each device document entity in the device knowledge graph can be searched, and the device document entity containing the device identification in the label content can be determined as the device document entity corresponding to the scope to be queried. The label content of each device document entity corresponding to the scope to be queried in the device knowledge graph can be searched based on the device document identification contained in the query keyword, and the device document entity containing the device document identification in the label content can be determined as the target device document entity.

[0069] Optionally, when querying the device identifier and device document identifier contained in the keyword, the label content of each device entity in the device knowledge graph can be searched according to the device identifier contained in the query keyword, and the device entity containing the device identifier in the label content can be determined as the target device entity.

[0070] This solution introduces a device identifier, a device document identifier and a document content identifier, determines the target device entity, the target device document entity and the first target document content entity, and can improve the detection efficiency of the target device entity, the target device document entity and the first target document content entity.

[0071] S240. Perform path exploration on the device knowledge graph according to the target device ontology, the target device document entity and the first target document content entity to obtain the target association relationship between the second target document content entity and the target device ontology, the target device document entity, the first target document content entity and the second target document content entity.

[0072] The second target document content entity may be a document content entity obtained after performing a path search on the device knowledge graph. In comparison, the first target document content entity is a document content entity directly obtained based on the query keyword; while the second target document content entity is not a document content entity directly obtained based on the query keyword, but a document content entity obtained after performing a path exploration on the device knowledge graph based on the target device ontology, the target device document entity and the first target document content entity that have been obtained.

[0073] Specifically, based on the device knowledge graph, the association relationship between the target device ontology, the target device document entity and the first target document content entity can be searched, and other entities that have an association relationship with the target device ontology, the target device document entity and the first target document content entity can be detected. At the same time, the path of the device knowledge graph starting from the target device ontology, passing through the target device document entity, and finally reaching the first target document content entity in the device knowledge graph is explored to obtain other document content entities passed by the path, obtain the second document content entity, and the target association relationship between the target device ontology, the target device document entity, the first target document content entity and the second document content entity.

[0074] In an optional embodiment of the present invention, a path exploration is performed on the device knowledge graph according to the target device ontology, the target device document entity and the first target document content entity to obtain a target association relationship between the second target document content entity and the target device ontology, the target device document entity, the first target document content entity and the second target document content entity, including: based on the device knowledge graph, other document content entities that have direct and indirect association relationships with the target device ontology, the target device document entity and the first target document content entity are screened; based on the direct and indirect association relationships between the target device ontology, the target device document entity, the target document content entity and other document content entities, a path exploration is performed between the target device ontology, the target device document entity and the target document content entity, and other document content entities are screened to obtain a second target document content entity that passes through a path between the target device ontology, the target device document entity and the first target document content entity; based on the device knowledge graph, the target association relationship between the target device ontology, the target device document entity, the first target document content entity and the second target document content entity is obtained.

[0075] Other document content entities may be document content entities that have an association relationship with the target device entity, the target device document entity, or the first target document content entity. A direct association relationship may be a relationship that is directly connected to the first target document content entity. An indirect association relationship may be a relationship that is indirectly connected to the first target document content entity. The second target document content entity may be a content document entity that has a direct association relationship and an indirect association relationship with the target device entity, the target device document entity, and the first target document content entity, and has the same path.

[0076] Specifically, based on the device knowledge graph, other document content entities that have direct and indirect associations with the target device ontology, the target device document entity, and the first target document content entity can be screened. Based on the direct and indirect associations between the target device ontology, the target device document entity, the target document content entity, and the other document content entities, a path exploration can be performed between the target device ontology, the target device document entity, and the target document content entity, and other document content entities can be screened to obtain a second target document content entity that passes through the path between the target device ontology, the target device document entity, and the first target document content entity. Based on the device knowledge graph, the target association relationship between the target device ontology, the target device document entity, the first target document content entity, and the second target document content entity is obtained.

[0077] This solution introduces a pre-screening of the direct and indirect association relationships between the target device entity, the target device document entity and the first target document content entity to obtain other document content entities, and then searches for the second document content entity according to the path of the device knowledge graph, thereby determining the target association relationship between the target device entity, the target device document entity, the first target document content entity and the second document content entity, which can improve the determination efficiency between the second target document content entity and the target association relationship.

[0078] S250. Generate and display a target device document knowledge graph based on the target device ontology, the target device document entity, the target document content entity, and the target association relationship between the target device ontology, the target device document entity, and the target document content entity.

[0079] The technical solution of the embodiment of the present invention queries each entity in the device knowledge graph according to the query keyword to obtain the target device entity, the target device document entity and the first target document content entity, and performs path exploration on the device knowledge graph according to the target device entity, the target device document entity and the first target document content entity to obtain the second target document content entity and the target device entity, the target device document entity, the first target document content entity and the target association relationship between the second target document content entity, and first locate the target device entity, the target device document entity and the first target document content entity, and then locate the second target document content entity and the target association relationship between the target device entity, the target device document entity, the first target document content entity and the second target document content entity, so as to improve the accuracy of the target device entity, the target device document entity, the target document content entity and the target association relationship, thereby improving the accuracy of the generated target device document knowledge graph.

[0080] Figure 3 This is a preferred embodiment of a device document search method provided in Embodiment 2 of the present invention.

[0081] See also Figure 3 The device document search method shown includes:

[0082] S1: Knowledge recommendation.

[0083] The system can recommend the displayed entry knowledge content based on the current user's browsing habits. The entry knowledge content will be displayed in the form of pictures. Click the middle part to enter the entry details page. It also displays the knowledge contained in the current entry. The recommended entry knowledge content will scroll in a loop. During the loop, you can select the recommended entry by clicking the point below, or you can rotate to the right through the small part on the right or click the middle area on both sides to turn the page left and right.

[0084] S2: Popular terms.

[0085] On the knowledge recommendation side, you can display popular terms in the library in the form of pictures. When the search frequency for the knowledge under the term is high, you can display the current term. The display picture will be updated according to the real-time search volume. After the user clicks on the term on the display picture, he will enter the library search overview page.

[0086] S3: Added new knowledge points.

[0087] Users with knowledge addition permissions can add knowledge points and entries to the encyclopedia. Knowledge relationships can be established between different knowledge points through manual settings or automatic system recommendations. Click "Add knowledge" to start adding knowledge, and the newly added knowledge points will also appear in the knowledge recommendations.

[0088] S4: Knowledge search.

[0089] After conducting a knowledge search (i.e., device document search), the system will integrate the retrieved results, associate each piece of knowledge (i.e., device entity, device document entity, and document content entity), and obtain a device document knowledge graph, which will then be presented to the user in the form of a picture, providing the user with a graphical and structured knowledge map, allowing the user to easily query knowledge content.

[0090] S5: Graph visualization.

[0091] Multiple knowledge points associated with the same device can be brought together by the entry as the convergence point, and finally form a device document knowledge graph centered on the device. In the graph visualization interface, you can complete operations such as search, filter, path exploration, view graphs, view recommended content, view hot content, and graph interaction (click to expand nodes). You can also configure the number of entities displayed under the graph (i.e. the preset number of displayed entities).

[0092] S6: Graph search.

[0093] Graph search is mainly a practical application of the device knowledge graph. After the device knowledge graph is established, it can provide search services for users. Graph search searches the content of the first graph by default. You can select different graphs for content search through the filter box. The filtered content will be displayed in the form of a knowledge graph in a tree diagram. The image content will change according to the filter object (i.e., device document query information).

[0094] S7: Path exploration.

[0095] There are path lines between entities (i.e. keywords corresponding to entities) on the tree diagram. You can explore related content by clicking on the path line. Selecting one of the paths will allow you to view the path details, which will help users explore the relationship between entities in the device knowledge graph and assist users in making decisions. During the path exploration process, you can easily query the relationship between two different entities or entities.

[0096] S8: Image export.

[0097] Image export can support the export of images of the content displayed on the graph visualization when users search, explore paths, view recommended content, view hot searches, and view graphs. The exported images can be saved locally to provide materials for users to analyze graph information.

[0098] The present invention also provides a device document search system, including a personal center module, a data statistics module, a picture generation module, a knowledge acquisition module, a data construction module, a graph application module, a graph search module, a node interaction module and a download management module. Among them, the personal center module will record the focus area selected by the user base when logging in, and automatically generate a user attribute entry library. During the user's use, the personal center module will record the user's search habits and further expand the user attribute entry library. After the user logs in, the personal center module will search the cloud library and encyclopedia library based on the generated user attribute entry library, select the knowledge entries that the user is interested in, and generate a scrollable broadcast picture on the homepage through the picture generation module. The data statistics module will count the popular entries in the library and encyclopedia library, and then generate the corresponding popular entry pictures through the picture generation module. The data construction module allows users with knowledge addition permissions to add knowledge points and entries in the encyclopedia library, and the newly added knowledge points will also appear in the knowledge recommendation. When users search, the knowledge acquisition module will automatically extract relevant content from the encyclopedia and library based on the terms entered by the users. In this process, the data construction module will associate and integrate the various knowledge points. The graph application module will bring together multiple knowledge points and form a graph network centered on the terms, so that these knowledge points can be displayed in the form of a graph, forming a graph visualization interface, such as Figure 4 As shown. After the graph is generated, you can use the graph search module to perform advanced search. You can select different graphs through the filter box to search for content, and the filtered content will be directly displayed in the form of a graph. The node interaction module will set jump links between each knowledge point in the graph, and users can explore the graph by clicking on the connecting lines between knowledge points. The download management module can download the generated pictures and graphs to the local storage, which is convenient for users to provide materials for analyzing graph information.

[0099] In the field of nuclear power technology, the rapid development of new information technologies represented by the Internet, the Internet of Things, perception networks and social networks has promoted the scale and low cost of equipment document data acquisition, causing the explosive growth of equipment document data. While bringing convenience to data acquisition, it also brings difficulty and complexity to equipment document information acquisition. This solution reduces the difficulty and complexity of equipment document information acquisition and improves the intuitiveness of equipment document information acquisition.

[0100] Embodiment 3

[0101] Figure 5 A schematic diagram of the structure of a device document search apparatus provided in Embodiment 3 of the present invention. The embodiment of the present invention can be applied to the case of searching for device documents in the nuclear power field, the apparatus can execute a device document search method, the apparatus can be implemented in the form of hardware and / or software, and the apparatus can be configured in an electronic device carrying a device document search function, such as a client or a server.

[0102] See also Figure 5 The device document search apparatus shown includes: a query information acquisition module 510, a query information parsing module 520, a target association relationship search module 530 and a device document knowledge graph generation module 540. The query information acquisition module 510 is used to acquire device document query information of a device document; the query information parsing module 520 is used to parse the device document query information to obtain query keywords; the target association relationship search module 530 is used to search the device knowledge graph according to the query keywords to obtain the target device entity, the target device document entity, the target document content entity and the target association relationship between the target device entity, the target device document entity and the target document content entity; the device document knowledge graph generation module 540 is used to generate and display the target device document knowledge graph according to the target device entity, the target device document entity, the target document content entity and the target association relationship between the target device entity, the target device document entity and the target document content entity.

[0103] The technical solution of the embodiment of the present invention parses the device document query information to obtain query keywords, searches the device knowledge graph according to the query keywords, obtains the target device entity, the target device document entity, the target document content entity and the target association relationship between the target device entity, the target device document entity and the target document content entity, generates and displays the target device document knowledge graph according to the target device entity, the target device document entity, the target document content entity and the target association relationship between the target device entity, the target device document entity and the target document content entity, and realizes rapid query of the device document content through the device knowledge graph. By generating the device document knowledge graph, the intuitiveness and readability of the device document content are improved, and the association relationship between the device document content and the device document and the device is reflected, which facilitates the subsequent analysis and processing of the device document content.

[0104] In an optional embodiment of the present invention, the target association relationship search module 530 includes: a first target document content view determination unit, which is used to query each entity in the device knowledge graph according to the query keyword to obtain a target device entity, a target device document entity and a first target document content entity; wherein the first target document content entity corresponds to the query keyword; a target association relationship search unit, which is used to perform path exploration on the device knowledge graph according to the target device entity, the target device document entity and the first target document content entity to obtain the target association relationship between the second target document content entity and the target device entity, the target device document entity, the first target document content entity and the second target document content entity.

[0105] In an optional embodiment of the present invention, the first target document content view determination unit includes: a target device ontology search subunit, used to search each device ontology in the device knowledge graph according to the device identification contained in the query keyword to obtain the target device ontology; a target device document entity search subunit, used to search each device document entity in the device knowledge graph according to the device identification and the device document identification contained in the query keyword to obtain the target device document entity; a first target document content view determination subunit, used to search each document content entity in the device knowledge graph according to the device identification, the device document identification and the document content identification contained in the query keyword to obtain the first target document content entity.

[0106] In an optional embodiment of the present invention, the target association relationship search unit includes: other document content entity screening subunit, which is used to screen other document content entities that have direct and indirect association relationships with the target device entity, the target device document entity and the first target document content entity based on the device knowledge graph; a second target document content entity screening subunit, which is used to perform path exploration between the target device entity, the target device document entity and the target document content entity based on the target device entity, the target device document entity, the direct and indirect association relationships between the target document content entity and the other document content entities, and screen the other document content entities to obtain a second target document content entity that passes through the path between the target device entity, the target device document entity and the first target document content entity; a target association relationship search subunit, which is used to obtain a target association relationship between the target device entity, the target device document entity, the first target document content entity and the second target document content entity based on the device knowledge graph.

[0107] In an optional embodiment of the present invention, the device document knowledge graph generation module 540 includes: a preset entity display quantity acquisition unit, used to obtain the preset entity display quantity; a target display document content entity screening unit, used to screen the target document content entity according to the preset entity display quantity to obtain the target display document content entity; a device document knowledge graph generation unit, used to generate and display the target device document knowledge graph according to the target device body, the target device document entity, the target display document content entity and the target association relationship between the target device body, the target device document entity and the target display document content entity.

[0108] In an optional embodiment of the present invention, the equipment documents include equipment production documents, equipment operation documents and equipment maintenance documents.

[0109] The device document search apparatus provided in the embodiment of the present invention can execute the device document search method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0110] In the technical solution of the embodiment of the present invention, the acquisition, storage and application of the device document query information and preset entity display quantity of the device documents involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0111] Embodiment 4

[0112] Figure 6A schematic diagram of the structure of an electronic device 600 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0113] like Figure 6 As shown, the electronic device 600 includes at least one processor 601, and a memory connected to the at least one processor 601, such as a read-only memory (ROM) 602, a random access memory (RAM) 603, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 601 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 602 or the computer program loaded from the storage unit 608 to the random access memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the electronic device 600 can also be stored. The processor 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0114] Multiple components in the electronic device 600 are connected to the I / O interface 605, including: an input unit 606, such as a keyboard, a mouse, etc.; an output unit 607, such as various types of displays, speakers, etc.; a storage unit 608, such as a disk, an optical disk, etc.; and a communication unit 609, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 609 allows the electronic device 600 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0115] The processor 601 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The processor 601 executes the various methods and processes described above, such as the device document search method.

[0116] In some embodiments, the device document search method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 608. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 600 via the ROM 602 and / or the communication unit 609. When the computer program is loaded into the RAM 603 and executed by the processor 601, one or more steps of the device document search method described above may be performed. Alternatively, in other embodiments, the processor 601 may be configured to perform the device document search method in any other appropriate manner (e.g., by means of firmware).

[0117] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0118] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0119] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0120] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0121] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0122] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS (Virtual Private Server) services.

[0123] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0124] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A device document search method, characterized in that: The method comprises: Get device document query information of device document; Parsing the device document query information to obtain query keywords; According to the query keyword, the device knowledge graph is searched to obtain a target device entity, a target device document entity, a target document content entity, and a target association relationship between the target device entity, the target device document entity, and the target document content entity; A target device document knowledge graph is generated and displayed according to the target device ontology, the target device document entity, the target document content entity, and the target association relationship between the target device ontology, the target device document entity and the target document content entity.

2. The method according to claim 1, characterized in that The device knowledge graph is searched according to the query keyword to obtain a target device entity, a target device document entity, a target document content entity, and a target association relationship between the target device entity, the target device document entity, and the target document content entity, including: According to the query keyword, query each entity in the device knowledge graph to obtain a target device entity, a target device document entity and a first target document content entity; wherein the first target document content entity corresponds to the query keyword; According to the target device ontology, the target device document entity and the first target document content entity, the device knowledge graph is path explored to obtain the target association relationship between the second target document content entity and the target device ontology, the target device document entity, the first target document content entity and the second target document content entity.

3. The method according to claim 2, characterized in that The querying of each entity in the device knowledge graph according to the query keyword to obtain the target device entity, the target device document entity and the first target document content entity includes: According to the device identifier contained in the query keyword, each device ontology in the device knowledge graph is searched to obtain the target device ontology; Search each device document entity in the device knowledge graph according to the device identifier and the device document identifier contained in the query keyword to obtain a target device document entity; According to the device identifier, the device document identifier and the document content identifier contained in the query keyword, each document content entity in the device knowledge graph is searched to obtain a first target document content entity.

4. The method according to claim 2, characterized in that: The performing path exploration on the device knowledge graph according to the target device ontology, the target device document entity and the first target document content entity to obtain a target association relationship between the second target document content entity and the target device ontology, the target device document entity, the first target document content entity and the second target document content entity includes: Based on the device knowledge graph, other document content entities having direct and indirect association relationships with the target device entity, the target device document entity, and the first target document content entity are screened; Based on the direct association relationship and indirect association relationship among the target device entity, the target device document entity, the target document content entity and the other document content entities, a path exploration is performed among the target device entity, the target device document entity and the target document content entity, and the other document content entities are screened to obtain a second target document content entity passing through the path among the target device entity, the target device document entity and the first target document content entity; Based on the device knowledge graph, a target association relationship among the target device entity, the target device document entity, the first target document content entity and the second target document content entity is obtained.

5. The method according to claim 1, characterized in that The generating and displaying a target device document knowledge graph according to the target device ontology, the target device document entity, the target document content entity, and the target association relationship between the target device ontology, the target device document entity, and the target document content entity includes: Get the preset entity display quantity; According to the preset entity display quantity, the target document content entity is screened to obtain a target display document content entity; A target device document knowledge graph is generated and displayed according to the target device ontology, the target device document entity, the target display document content entity, and the target association relationship between the target device ontology, the target device document entity and the target display document content entity.

6. The method according to claim 1, characterized in that The equipment documents include equipment production documents, equipment operation documents and equipment maintenance documents.

7. A device document search apparatus, characterized in that: The device comprises: A query information acquisition module, used to acquire device document query information of a device document; A query information parsing module, used to parse the device document query information to obtain query keywords; A target association relationship search module is used to search the device knowledge graph according to the query keyword to obtain a target device entity, a target device document entity, a target document content entity, and a target association relationship between the target device entity, the target device document entity and the target document content entity; The device document knowledge graph generation module is used to generate and display the target device document knowledge graph based on the target device entity, the target device document entity, the target document content entity, and the target association relationship between the target device entity, the target device document entity and the target document content entity.

8. 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 executable 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 device document search method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the device document search method according to any one of claims 1 to 6 when executed.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the computer program implements the device document search method according to any one of claims 1 to 6.

Images