Knowledge simplification and display method, device, electronic device and readable medium

Abstract

The present disclosure relates to a method, device, electronic device and computer-readable medium for simplifying and displaying knowledge. The method comprises: obtaining knowledge points under a target question, wherein the knowledge points include knowledge point values; determining a discrete degree index of the knowledge points under the target question according to the knowledge point values ​​of the knowledge points; dividing the knowledge points under the target question into multiple levels according to the discrete degree index of the knowledge points under the target question; constructing a tree structure according to the multiple levels; and displaying the target question according to the tree structure. The method, device, electronic device and computer-readable medium for simplifying and displaying knowledge involved in the present disclosure can simplify the display method of knowledge and reduce the overall complexity of question filling.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular to a method, device, electronic device and computer-readable medium for simplifying and displaying knowledge. Background Art

[0002] The design of information filled in by users on the Internet is generally based on the knowledge content to be collected, such as: policyholder information, insured information, product purchase information, motor vehicle information, health information, etc. These contents are either implemented in blocks on one page or on multiple pages. However, no matter how they are arranged, if the expression of "knowledge" is not changed and the items to be filled in or selected are not simplified, it is difficult to reduce the overall complexity.

[0003] Therefore, a new method, device, electronic device and computer-readable medium for simplifying and displaying knowledge is needed.

[0004] The above information disclosed in this background section is only for enhancement of understanding of the background of the present disclosure and therefore it may include information that does not constitute the relevant technology that is already known to one of ordinary skill in the art. Summary of the invention

[0005] In view of this, the embodiments of the present disclosure provide a method, device, electronic device and computer-readable medium for simplifying and displaying knowledge, which can simplify the display of knowledge and reduce the overall complexity of question filling.

[0006] Other features and advantages of the present disclosure will become apparent from the following detailed description, or may be learned in part by the practice of the present disclosure.

[0007] According to one aspect of the present disclosure, a method for simplifying and displaying knowledge is proposed, the method comprising: obtaining knowledge points under a target problem, the knowledge points comprising knowledge point values; determining a discrete degree index of the knowledge points under the target problem according to the knowledge point values ​​of the knowledge points; dividing the knowledge points under the target problem into multiple levels according to the discrete degree index of the knowledge points under the target problem; constructing a tree structure according to the multiple levels; and displaying the target problem according to the tree structure.

[0008] In an exemplary embodiment of the present disclosure, determining the discrete degree index of the knowledge point under the target problem according to the knowledge point value of the knowledge point includes: calculating the discrete coefficient of the knowledge point under the target problem according to the knowledge point value of the knowledge point; if the discrete coefficient is greater than the discrete coefficient threshold, calculating the deviation value of the knowledge point under the target problem from the median according to the knowledge point value of the knowledge point; if there is a deviation knowledge point under the target problem whose deviation value from the median is less than the deviation threshold, determining the limit value of the target problem; if the knowledge point value of the deviation knowledge point exceeds the limit value of the target problem, determining that the discrete degree index of the knowledge point under the target problem is a high discrete degree.

[0009] In an exemplary embodiment of the present disclosure, dividing the knowledge points under the target question into multiple levels according to the discrete degree index of the knowledge points under the target question includes:

[0010] If the discrete degree index of the knowledge points under the target problem is a high discrete degree, determine the first deviation knowledge point in the deviation knowledge points that is greater than the upper limit value in the limit value of the target problem, and the second deviation knowledge point that is less than the lower limit value in the limit value of the target problem; divide the first deviation knowledge point into a first interval; divide the second deviation knowledge point into a second interval; divide the remaining knowledge points under the target problem except the first deviation knowledge point and the second deviation knowledge point into a third interval; add an upper-level node for each interval between the knowledge points under each interval and the target problem; use the newly added upper-level node in each interval as a child node under the target problem, and the knowledge points under each interval as child nodes of the upper-level node of each interval, to generate multiple levels under the target problem.

[0011] In an exemplary embodiment of the present disclosure, constructing a tree structure according to multiple levels includes: generating key value information according to the upper nodes and child nodes newly added in each interval, the key of the upper node includes the identifier of the upper node and the level of the upper node in the tree structure, and the value of the upper node includes the identifier of the child node of the upper node; or generating memory block information according to the upper nodes and child nodes newly added in each interval, the memory block information of the upper node includes the digital number of the upper node, the level of the upper node in the tree structure, and the digital number of the child node of the upper node.

[0012] In an exemplary embodiment of the present disclosure, displaying the target question according to the tree structure includes: acquiring and displaying the content of the child nodes of the node corresponding to the target question; and displaying the content of the child nodes of the child nodes according to a click operation on the content of the child nodes of the node corresponding to the target question.

[0013] In an exemplary embodiment of the present disclosure, the method further includes: determining a target subnode in the tree structure based on an operation on the displayed target question; determining a selection result of the target question based on the median of knowledge points in the interval where the target subnode is located; and generating conclusion information based on the selection result of the target question.

[0014] In an exemplary embodiment of the present disclosure, displaying the target question according to the tree structure includes: obtaining and displaying the question to be input; processing input information of the question to be input and determining the target question according to the processing result; and displaying the target question according to the tree structure.

[0015] According to one aspect of the present disclosure, a device for simplifying and displaying knowledge is proposed, and the device includes: a knowledge point acquisition module, used to acquire knowledge points under a target problem, wherein the knowledge points include knowledge point values; a discrete degree calculation module, used to determine a discrete degree index of the knowledge points under the target problem according to the knowledge point values ​​of the knowledge points; a hierarchical division module, used to divide the knowledge points under the target problem into multiple hierarchies according to the discrete degree index of the knowledge points under the target problem; a tree structure construction module, used to construct a tree structure according to the multiple hierarchies; and a knowledge point display module, used to display the target problem according to the tree structure.

[0016] According to one aspect of the present disclosure, an electronic device is proposed, which includes: one or more processors; a storage device for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the method described above.

[0017] According to one aspect of the present disclosure, a computer-readable medium is provided, on which a computer program is stored. When the program is executed by a processor, the method described above is implemented.

[0018] According to the knowledge simplification and display method, device, electronic device and computer-readable medium provided by some embodiments of the present disclosure, for the knowledge points under the target question, the discrete degree index of the knowledge points under the target question is determined according to the knowledge point value of the knowledge point; and then the knowledge points under the target question are divided into multiple levels according to the discrete degree index, so that the knowledge can be simplified. A tree structure is constructed according to the multiple levels of the division; the knowledge points under the target question can be displayed layer by layer based on the tree structure, so that the tree structure can be quickly searched, and the display method of knowledge is simplified, reducing the overall complexity of filling in the question.

[0019] It is to be understood that the foregoing general description and the following detailed description are exemplary only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The above and other objects, features and advantages of the present disclosure will become more apparent by describing in detail its exemplary embodiments with reference to the accompanying drawings. The accompanying drawings described below are only some embodiments of the present disclosure, and it is clear to a person skilled in the art that other accompanying drawings can be obtained from these accompanying drawings without creative work.

[0021] Figure 1 It is a flowchart of a method for simplifying and displaying knowledge according to an exemplary embodiment.

[0022] Figure 2 It is a flowchart of a method for simplifying and displaying knowledge according to another exemplary embodiment.

[0023] Figure 3 is a flowchart of a method for simplifying and displaying knowledge according to yet another exemplary embodiment.

[0024] Figure 4 The figure is a distribution diagram of occupational levels in the service industry according to an exemplary embodiment.

[0025] Figure 5 is a schematic diagram of a tree structure according to an exemplary embodiment.

[0026] Figure 6 The figure is a display effect diagram of a tree structure according to an exemplary embodiment.

[0027] Figure 7 The figure is a display effect diagram of a tree structure according to an exemplary embodiment.

[0028] Figure 8 The figure is a display effect diagram of a tree structure according to an exemplary embodiment.

[0029] Fig. 9 The figure is a display effect diagram of a tree structure according to an exemplary embodiment.

[0030] Fig.10 The figure is a display effect diagram of a tree structure according to an exemplary embodiment.

[0031] Fig.11 The figure is a display effect diagram of a tree structure according to an exemplary embodiment.

[0032] Fig.12 It is a system architecture diagram showing the simplification and presentation of knowledge according to an exemplary embodiment.

[0033] Fig.13 It is a block diagram of a knowledge simplification and display device according to an exemplary embodiment.

[0034] Fig.14 A block diagram schematically shows an electronic device in an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0035] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be comprehensive and complete and will fully convey the concepts of the example embodiments to those skilled in the art. The same reference numerals in the figures represent the same or similar parts, and thus their repeated description will be omitted.

[0036] In addition, the described features, structures or characteristics may be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. may be adopted. In other cases, known methods, devices, implementations or operations are not shown or described in detail to avoid blurring the various aspects of the present disclosure.

[0037] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0038] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0039] It should be understood that although the terms first, second, third, etc. may be used herein to describe various components, these components should not be limited by these terms. These terms are used to distinguish one component from another component. Therefore, the first component discussed below can be referred to as the second component without departing from the teachings of the disclosed concepts. As used herein, the term "and / or" includes any one of the associated listed items and all combinations of one or more.

[0040] Those skilled in the art will appreciate that the drawings are merely schematic diagrams of example embodiments, and the modules or processes in the drawings are not necessarily necessary for implementing the present disclosure, and therefore cannot be used to limit the protection scope of the present disclosure.

[0041] Figure 1 It is a flowchart of a method for simplifying and displaying knowledge according to an exemplary embodiment. The method for simplifying and displaying knowledge provided in the embodiment of the present disclosure can be executed by any electronic device with computing and processing capabilities, such as a user terminal and / or a server. In the following embodiments, the method is illustrated by taking the server executing the method as an example, but the present disclosure is not limited to this. The method for simplifying and displaying knowledge 10 provided in the embodiment of the present disclosure may include steps S102 to S110.

[0042] like Figure 1 As shown, in step S102, knowledge points under the target question are obtained, and the knowledge points include knowledge point values.

[0043] Among them, the knowledge points under the target question can be, for example, the knowledge points of the same type at the bottom layer of a knowledge system. The "bottom layer" can be determined according to the implementation scenario, for example, it can be a set of occupations that the user needs to select, the reasons for hospitalization that the user needs to select, hobbies that the user needs to fill in, etc. Each knowledge point can be given a specific value: the knowledge point value. For example, an occupation can be given an occupation level of 1-6 to represent the risk from small to large, the reasons for hospitalization can be given a risk level of 1-6 to represent the health level, and the user's preferences can be given an insurance demand of 1-6 to represent the size of the potential insurance demand, etc.

[0044] In step S104, the discrete degree index of the knowledge point under the target question is determined according to the knowledge point value of the knowledge point.

[0045] In the disclosed embodiment, the discrete degree index of the knowledge points under the target problem can be determined according to the discrete coefficient, median, restriction, etc.

[0046] In step S106, the knowledge points under the target question are divided into multiple levels according to the discrete degree index of the knowledge points under the target question.

[0047] In the disclosed embodiment, if the discreteness index of the knowledge points under the target question is a low discreteness, the knowledge points under the target question can be attributed to the same type of knowledge without further division into multiple levels. If the discreteness index of the knowledge points under the target question is a high discreteness, it is considered that the knowledge points under the target question cannot be attributed to the same type of knowledge and need to be further divided into multiple levels.

[0048] When divided into multiple levels, the knowledge points under the target problem can be divided into multiple sets, each set includes one or more knowledge points, and the historical discreteness index of one or more knowledge points in each set is a low discreteness.

[0049] In step S108, a tree structure is constructed according to the multiple levels.

[0050] In the disclosed embodiment, the tree structure is, for example, a B+ tree structure. The B+ tree is evolved from the B-tree and the index sequential access method. The B+ tree is a balanced search tree designed for disks or other direct access auxiliary devices. In the B+ tree, all record nodes are stored in the leaf nodes of the same layer in the order of the size of the key value, and the leaf node pointers are connected.

[0051] When constructing a tree structure according to multiple levels, the knowledge system to which the target problem belongs can be formed into a complete tree structure, and a tree structure can be constructed by combining multiple levels into which knowledge points under the target problem are divided.

[0052] In step S110, the target question is displayed according to the tree structure.

[0053] In the disclosed embodiment, multiple levels under the target question can be displayed layer by layer based on the tree structure. Further, when a user selects or clicks a node in a certain level, the knowledge points of the leaf nodes under the node are further displayed based on the selection or click operation.

[0054] According to the knowledge simplification and display method provided by the embodiment of the present disclosure, for the knowledge points under the target question, the discrete degree index of the knowledge points under the target question is determined according to the knowledge point value of the knowledge point; and then the knowledge points under the target question are divided into multiple levels according to the discrete degree index, so that the knowledge simplification can be achieved. A tree structure is constructed according to the multiple levels of the division; the knowledge points under the target question can be displayed layer by layer based on the tree structure, so that the tree structure can be quickly searched, and the display method of knowledge is simplified, reducing the overall complexity of filling in the question.

[0055] It should be clearly understood that the present disclosure describes how to form and use specific examples, but the principles of the present disclosure are not limited to any details of these examples. On the contrary, based on the teachings of the contents disclosed in the present disclosure, these principles can be applied to many other embodiments.

[0056] Figure 2 It is a flowchart of a method for simplifying and displaying knowledge according to another exemplary embodiment.

[0057] like Figure 2 As shown, in the embodiment of the present invention, the above step S104 may further include the following steps.

[0058] In step S202, the discrete coefficient of the knowledge point under the target problem is calculated according to the knowledge point value of the knowledge point.

[0059] Among them, the coefficient of dispersion is also called the coefficient of variation. It is a normalized measure of the degree of dispersion of the probability distribution, which is defined as the ratio of the standard deviation to the mean. The coefficient of variation C·V = (standard deviation SD / mean value Mean) × 100%. The calculation formula of the standard deviation is: the difference between each number and the mean, squared and added one by one (equivalent to the accumulation of squared errors), then divided by the number n, and then squared. The standard deviation can be understood as the average value of the deviation amplitude, and the coefficient of variation is based on this and then divided by the mean, reflecting the degree of data deviation.

[0060] In the disclosed embodiment, a set of data is given: {3,3,3,3,3,3,3,3,3,2,2,2,2,2,2,2,2,2,2}, representing the occupational levels of 19 types of work under "cultural and sports goods production" {pencil production workers, fitness equipment production workers, piano\keyboard instrument production workers, violin production workers, wind instrument production workers, string\plucked instrument production workers, wind instrument production workers, percussion instrument production workers, electroacoustic instrument production workers, fountain pen production workers, ballpoint pen production workers, ink production workers, ball production workers, racket\net production workers, ink production workers, ink\ink production workers, drawing instrument production workers, copier consumables (ink cartridges, etc.) production workers, brush production workers}, calculated using the above formula, the dispersion coefficient is 20.7%, and the mean is 2.47. In statistics, usually 0-15% is small variation, 16% to 35% is medium variation, and greater than 36% is high variation. The present application may use 36% as a reference value to determine whether a set of data is low-dispersion data, that is, 36% is the dispersion coefficient threshold.

[0061] In step S204, if the dispersion coefficient is greater than the dispersion coefficient threshold, the deviation value between the knowledge point under the target question and the median is calculated according to the knowledge point value of the knowledge point.

[0062] Among them, if the dispersion coefficient is less than or equal to the dispersion coefficient threshold, it is confirmed that the dispersion degree index of the knowledge point under the target problem is a low dispersion degree.

[0063] If the coefficient of dispersion is greater than the threshold value of the coefficient of dispersion, the degree of dispersion can be further judged based on the median. The median is the number in the middle of a set of values ​​arranged in order. The median represents the representative value of the set of numbers and is not affected by the maximum and minimum values. It is very intuitive to use it to evaluate the balance of a set of numbers in this application. The median algorithm is used to evaluate a set of data X1...X n If the value n is an odd number, then the median m = X (n+1) / 2 ; If the value n is an even number, then the median m = (X n / 2 +X n / 2+1) / 2. Continuing to evaluate the previous set of example data, 19 values ​​are single numbers, and the median is the occupation level 2. The maximum value is 3 and the minimum value is 2. Assuming the deviation threshold is 2, it can be confirmed that the discrete degree index of the knowledge point under the target problem is low discrete degree.

[0064] In step S206, if there are knowledge points under the target problem whose deviation value from the median is less than the deviation threshold, the limit value of the target problem is determined.

[0065] In step S208, if the knowledge point value of the deviation knowledge point exceeds the limit value of the target problem, the discrete degree index of the knowledge point under the target problem is determined to be a high discrete degree.

[0066] Among them, the limit value may include an upper limit value and a lower limit value. The upper limit value is greater than the lower limit value. The first two steps have been evaluated by statistical methods, and this step also uses the limit value to determine whether there is any data outside the limit value. For example, occupations with more than 5 representatives represent high-risk occupations, and the corresponding people are not suitable for purchasing insurance on the Internet. Diseases with a risk factor greater than 5 represent that the corresponding people are in poor health and are not suitable for insurance. If the data evaluated in the first two steps are balanced, and there is no data outside the limit value in this step, then the data is finally determined to have low dispersion; if there is data greater than the upper limit value and / or less than the lower limit value at the same time, the conclusion needs to be revised to high dispersion.

[0067] In this embodiment, knowledge points with a high degree of discreteness can be screened for the target question based on a statistical approach.

[0068] Figure 3 is a flowchart of a method for simplifying and displaying knowledge according to yet another exemplary embodiment.

[0069] like Figure 3 As shown, in the embodiment of the present invention, the above step S106 may include the following steps.

[0070] In step S302, if the discrete degree index of the knowledge point under the target problem is a high discrete degree, a first deviation knowledge point in the deviation knowledge point that is greater than the upper limit value in the limit value of the target problem and a second deviation knowledge point that is less than the lower limit value in the limit value of the target problem are determined.

[0071] In the embodiment of the present disclosure, Figure 4 For example. Figure 4 is a distribution diagram of occupational levels in the service industry according to an exemplary embodiment. Figure 4 As shown in the figure, the knowledge points can be arranged from large to small according to their values ​​and a scatter plot can be drawn. Figure 4Take the 112 types of work under the medium service industry as an example, where the highest data is 7 and the lowest is 1. Assume that the upper limit is 5 and the lower limit is 2. Then the knowledge points with a value greater than 5 are confirmed as the first deviation knowledge points, and the knowledge points with a value less than 2 are confirmed as the second deviation knowledge points.

[0072] In step S304, the first deviation knowledge point is divided into a first interval.

[0073] The first interval is, for example, Figure 4 The interval 401 where the knowledge point value is greater than 5.

[0074] In step S306, the second deviation knowledge point is divided into second intervals.

[0075] The second interval is, for example Figure 4 The interval 402 where the knowledge point value is less than 2.

[0076] In step S308, the remaining knowledge points under the target question except the first deviation knowledge point and the second deviation knowledge point are divided into a third interval.

[0077] The third interval is Figure 4 The interval 403 in .

[0078] In step S310, an upper node is added for each interval between the knowledge point in each interval and the target question.

[0079] In step S312, the upper-level nodes newly added in each interval are used as child nodes under the target problem, and the knowledge points under each interval are used as child nodes of the upper-level nodes of each interval, so as to generate multiple levels under the target problem.

[0080] Among them, adding a new upper node in each interval may have a problem, for example, Figure 4 In the middle interval 401, the question content of its upper node can be in the form of "Are you engaged in w1, w2, w3...wn work in the v industry". If the customer answers yes, a new job type "High-risk workers in the service industry" with a level of 6 (the median of the 403 interval) is added. If the customer answers no, answer the second question (the upper node corresponding to the interval 402), "Are you engaged in management personnel, general office staff, ticket seller, administrator, etc. in the service industry?". If the customer answers yes, a new job type "General office staff in the service industry" with a level of 1 (the median of the interval 402) is added. If the customer answers no, a new job type "On-site staff in the service industry" with a level of 3 (the median of the interval 403) is added.

[0081] Furthermore, the discreteness index of each interval can be further evaluated. If there is an interval with a high discreteness index, the interval can be further divided.

[0082] If the discreteness index of the knowledge point under the target problem is low, the data items can be directly merged into one item (i.e. the target problem item) and summarized into one name. For example, the 19 specific types of work in the previous step can be named as "Cultural and Sports Goods Manufacturing Practitioners", and the value is determined to be 3 based on the median. For another example, the government agency and the financial / legal industry can be merged to produce a "government financial and legal industry personnel", with a value of 2.

[0083] Furthermore, the knowledge points of the same level that have been simplified in the target problem can be further merged and simplified to form knowledge points of a higher level. Finally, a tree-shaped knowledge system (i.e., a tree structure) is formed. The tree structure can be, for example Figure 5 As shown. The number of knowledge points and questions (i.e., newly added upper-level nodes) under the knowledge root node (i.e., the target question) is uncertain. Such a design can be applied to the knowledge type system; the answer to a question can be a knowledge point or another question, and a multi-layer system can be constructed; a question can have two answers, which is suitable for questions such as "Do you...", or multiple answers, which is suitable for questions such as "Which one do you choose for the following questions?", and has strong applicability to various knowledge scenarios.

[0084] In this embodiment, constructing a tree structure according to multiple levels may include any of the following two methods:

[0085] The first one is to generate key value information based on the newly added upper nodes and child nodes in each interval, the key of the upper node includes the identifier of the upper node and the level of the upper node in the tree structure, and the value of the upper node includes the identifier of the child node of the upper node.

[0086] The second method is to generate memory block information based on the newly added upper nodes and child nodes in each interval, and the memory block information of the upper node includes the digital number of the upper node, the level of the upper node in the tree structure and the digital number of the child nodes of the upper node.

[0087] In the first method, the key cannot be repeated, and one key corresponds to one value. The specific design method can be shown in Table 1 below.

[0088] Table 1

[0089]

[0090] In this design, the left side is the "key" and the right side is the "value". Different "key / values" are strung together through the keys of the child nodes in the value, and the B+ tree is implemented without using pointers. The key design adopts a hierarchical + numbering design to ensure that the values ​​are not repeated and are easy to find. Each level is set to a 3-digit number, and the sequence number is used as the level number. For example: the root node is "001", the child nodes are 001001 / 001002 / 001003..., and the subordinate nodes of the second child node are 001002001 / 001002002 / 001002003... The "value" on the right side is designed with a json string. The json string design itself is a string, which reduces the requirements of the present invention on the use environment of the key value and is convenient for conversion into a high-level language "object" for use. Take the above schematic diagram as an example:

[0091] The key of the root node is "001" and the value is {'001',{'001','R',1,1,'root node',{'001001','001002','001003','001004','001005'}}}.

[0092] The first node at the next level is a question, with the key "001001" and the value {'001001',{'001001','Q',2,1,'Are you engaged in the service industry?①Zoo trainer, chimney sweep, keeper, boilerman, lifeguard, high-rise exterior cleaner②Service industry manager, general office staff, ticket seller, administrator③Other jobs in the service industry',{'001001001','001001002','001001003'}}}.

[0093] The first node at the next level is the result of answering the question ①, which is a knowledge point. The key is "001001001" and the value is {'001001001',{'001001001','K',3,1,'Service industry high-risk staff / 6',{}}}. The empty curly brackets at the end indicate that there are no child nodes, because this is a knowledge point, not a question.

[0094] For option ③ at the same level, you can continue to ask questions about "other jobs in the service industry" using a similar design method.

[0095] Summarize the advantages of this part of the technical design:

[0096] (1) Use multi-level key-value design. Make full use of the key-value system to search based on the "key" to achieve high speed and high performance.

[0097] (2) Use json strings to store keys instead of pointers, and realize flexible multi-level expansion of B+ trees.

[0098] (3) The amount of data on each node is small and the processing speed is fast.

[0099] (4) Whether it is a hash table or redis / Elasticsearch, the speed of querying "value" based on "key" is very fast.

[0100] The second method is similar to the "chain" of blockchain, but the difference is that blockchain is a "chain" while this design is a "tree". The memory block does not use the key-value method, but uses the method of direct memory operation, which is suitable for environments with tight computer storage resources and computing resources such as embedded devices. The design of the memory block needs to make appropriate agreements and restrictions on the content size.

[0101] The specific setting method of the second method can be shown in Table 2 below.

[0102] Table 2

[0103]

[0104] The above is a "block" of data, which can be designed to be 1024 bytes in size, which is more efficient in computer allocation. The content is limited to 600 bytes, and the number of child nodes per branch is limited to 30. Use digital numbers instead of the keys in the previous section, and you can get the memory address based on the digital numbers for high-speed search.

[0105] In this embodiment, displaying the target question according to the tree structure may include: obtaining and displaying the content of the child nodes of the node corresponding to the target question; and displaying the content of the child nodes of the child nodes according to a click operation on the content of the child nodes of the node corresponding to the target question.

[0106] Specifically, when the content of the child node of the node corresponding to the target question is obtained and displayed, different forms of display may be performed according to the number of answers to the child node. For example, when the number of answers to the child node is 1, the form of Figure 6 As shown. For the target question "Industry", all the child nodes under the root node of the tree structure are displayed by taking the "content" in the json string. These child nodes have "questions" and "knowledge points", but the customer does not know. If the user selects "organizations and groups / enterprises and institutions...", this is a knowledge point, not a question, and the knowledge point content "administrative office staff / sales field staff" is directly displayed. There is no next level, and the selection ends, as shown in the figure Figure 7 If you select "Postal...", this is a question, and a question will pop up for the customer to choose, as shown in the following figure. Figure 8 If you select No, the corresponding next-level node is still a question, as shown in Fig. 9If you select "Yes", the corresponding next-level node is a knowledge point, and the result is "High-voltage engineering implementation personnel", so select End.

[0107] Through the above front-end system, thousands of occupations are divided into multiple levels of selection and become one of more than twenty choices, and then one or two questions need to be answered. It is both simple and simplified according to statistical methods.

[0108] When the number of answers to this child node is greater than 1, it can be displayed as follows Fig.10 As shown. Fig.10 As shown, the first-level subnode content of the root node is displayed. If the customer selects "No", it is all knowledge points. If the customer selects "Yes", it is a question. The system obtains the subnode, and the interface will add a piece of content for the customer to choose. Fig.11 , Fig.11 Box 1110 is the content added after the user selects "yes", using HTML technology to dynamically add DOM nodes to the HTML content.

[0109] The above method can achieve that the content that the user wants to fill in does not appear all at once, but gradually appears through the content selected by the user, thereby reducing the overall complexity of filling in the question.

[0110] Optionally, displaying the target question according to the tree structure may include: obtaining and displaying the question to be input; processing the input information of the question to be input and determining the target question according to the processing result; and displaying the target question according to the tree structure.

[0111] When users are required to fill in height and weight or different questions appear based on multiple choice content. To deal with these situations, you can write complex logic based on the questions answered by the user to derive what the sub-node should be. The content needs to "dynamically" update the key / value or memory block, and return the sub-node to the front-end system. The existence of this module makes the entire system more complete, and it can deal with various complex knowledge without breaking away from the current framework and with scalability.

[0112] The questions to be input may be, for example, height, weight, age, gender, etc. For example, when the questions to be input are gender and age, and the user's input information is female and 60 years old, the input information may be processed, such as logical judgment processing, and when the gender is female and the age is greater than 55 years old, the judgment result is the target question. The target question may be, for example, an inquiry about common diseases of elderly women.

[0113] Optionally, the knowledge simplification and display method of this embodiment may also include: determining a target sub-node in the tree structure based on an operation on the displayed target problem; determining a selection result of the target problem based on the median of the knowledge points in the interval where the target sub-node is located; and generating conclusion information based on the selection result of the target problem.

[0114] This embodiment can make a judgment based on all the contents selected and filled in by the user to obtain the final conclusion information.

[0115] Among them, Figure 4 For example, when the target child node is Figure 4 A node in the middle interval 403, or an upper node corresponding to the interval, determines the occupational level to be 3 according to the median of the knowledge points in the interval. Then, the risk level of the user is concluded based on the occupational level 3, such as high-risk group, low-risk group, general risk group, etc.

[0116] Specifically, the system for simplifying and displaying knowledge in the embodiments of the present disclosure can be as follows: Fig.12 As shown. In which, the instruction formation and simplification system 1202 simplifies the original knowledge so that the knowledge points under the target problem are divided into multiple levels, and the data multi-layer processing system 1204 forms a tree structure such as a key / value form or a memory block form based on the multiple levels of each target problem. The front-end system 1206 can query the tree structure and display each target problem in a layer-by-layer manner.

[0117] In the knowledge analysis and summary system, further, the front-end system 1206 can obtain the question to be input and display it, and after the user answers, the answer (input information of the question to be input) is judged. The question processing module 1208 returns the knowledge point or subsequent question (i.e., determines the target question) according to the processing result, and the front-end system 1206 can search the tree structure according to the returned knowledge point or subsequent question to return multiple levels of subsequent questions.

[0118] Furthermore, the conclusion processing module 1210 may determine the selection result of the target question based on the question and answer selected by the user, and generate conclusion information according to the selection result.

[0119] The first application case of this application proposal is career choice. Before simplification, there were 39 categories and 1,541 types of work. After simplification, it became 19 categories and 42 types of work. The path and difficulty of customer selection were greatly shortened.

[0120] The second application case of this application proposal is the health notification application. As the scope of Internet sales products becomes larger and larger, the current health notification can only be passed with a standard body underwriting by selecting "no", which limits a large number of people who have some problems in the health notification but are still healthy. This solution is used to deepen the content of health notification and enter the demonstration and implementation stage.

[0121] This application proposal has the following technical effects.

[0122] 1. The knowledge simplification system provides a complete set of algorithms, processes and templates for the collection and filling of health, occupation, medical, hospitalization, financial and other information. It is an important manifestation of knowledge graph technology in corporate practice.

[0123] 2. Using key / value and memory block technologies, the B+ tree of the knowledge system is implemented in different scenarios, and fast query can be performed. These technologies have high reference value for the application of knowledge systems of different types and scenarios.

[0124] 3. The flexible front-end system provides question-answer and progressive presentation methods. Based on this, different types of input methods such as robots and wearable devices can also learn from this method.

[0125] 4. The complete knowledge analysis and summary system can "dynamically" calculate and adjust the content of the knowledge system, cope with different types of knowledge and front-end systems, and has good scalability and applicability.

[0126] Those skilled in the art will appreciate that all or part of the steps for implementing the above embodiments are implemented as a computer program executed by a CPU. When the computer program is executed by the CPU, the above functions defined by the above method provided by the present disclosure are performed. The program may be stored in a computer-readable storage medium, which may be a read-only memory, a disk, or an optical disk, etc.

[0127] In addition, it should be noted that the above figures are only schematic illustrations of the processes included in the method according to the exemplary embodiments of the present disclosure, and are not intended to be limiting. It is easy to understand that the processes shown in the above figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.

[0128] The following are embodiments of the device disclosed herein, which can be used to execute the method embodiments disclosed herein. For details not disclosed in the device embodiments disclosed herein, please refer to the method embodiments disclosed herein.

[0129] Fig.13 The block diagram of a knowledge simplification and display device according to an exemplary embodiment is shown. The knowledge simplification and display device 1300 provided in the embodiment of the present disclosure may include: a knowledge point acquisition module 1302, a discrete degree calculation module 1304, a hierarchical division module 1306, a tree structure construction module 1308 and a knowledge point display module 1310.

[0130] In the knowledge simplification and display device 1300, the knowledge point acquisition module 1302 can be used to acquire the knowledge points under the target question, and the knowledge points include knowledge point values.

[0131] The discrete degree calculation module 1304 may be used to determine the discrete degree index of the knowledge point under the target question according to the knowledge point value of the knowledge point.

[0132] The level division module 1306 may be used to divide the knowledge points under the target problem into multiple levels according to the discrete degree index of the knowledge points under the target problem.

[0133] The tree structure building module 1308 may be configured to build a tree structure according to the multiple levels.

[0134] The knowledge point display module 1310 may be used to display the target question according to the tree structure.

[0135] According to the knowledge simplification and display device provided by the embodiment of the present disclosure, for the knowledge points under the target question, the discrete degree index of the knowledge points under the target question is determined according to the knowledge point value of the knowledge point; and then the knowledge points under the target question are divided into multiple levels according to the discrete degree index, so that the knowledge simplification can be achieved. A tree structure is constructed according to the multiple levels of the division; the knowledge points under the target question can be displayed layer by layer based on the tree structure, so that the tree structure can be quickly searched, and the display method of knowledge is simplified, reducing the overall complexity of filling in the question.

[0136] In one embodiment, the discrete degree calculation module 1304 may include: a discrete coefficient calculation unit, which can be used to calculate the discrete coefficient of the knowledge point under the target problem according to the knowledge point value of the knowledge point; a deviation value calculation unit, which can be used to calculate the deviation value of the knowledge point under the target problem from the median according to the knowledge point value of the knowledge point if the discrete coefficient is greater than the discrete coefficient threshold; a deviation value comparison unit, which can be used to determine the limit value of the target problem if there is a deviation knowledge point under the target problem whose deviation value from the median is less than the deviation threshold; a limit value comparison unit, which can be used to determine that the discrete degree index of the knowledge point under the target problem is a high discrete degree if the knowledge point value of the deviation knowledge point exceeds the limit value of the target problem.

[0137] In one embodiment, the hierarchical division module 1306 may include: a knowledge point division unit, which can be used to determine, if the discrete degree index of the knowledge points under the target problem is a high discrete degree, a first deviation knowledge point in the deviation knowledge point that is greater than the upper limit value in the limit value of the target problem, and a second deviation knowledge point that is less than the lower limit value in the limit value of the target problem; a first interval unit, which can be used to divide the first deviation knowledge point into a first interval; a second interval unit, which can be used to divide the second deviation knowledge point into a second interval; a third interval unit, which can be used to divide the remaining knowledge points under the target problem except the first deviation knowledge point and the second deviation knowledge point into a third interval; an upper-level node addition unit, which can be used to add an upper-level node to each interval between the knowledge points under each interval and the target problem; a hierarchical construction unit, which can be used to use the upper-level node added to each interval as a child node under the target problem, and the knowledge points under each interval as child nodes of the upper-level node of each interval, to generate multiple levels under the target problem.

[0138] In one embodiment, the tree structure construction module 1308 may include: a key value construction unit, which can be used to generate key value information based on the upper nodes and child nodes newly added in each interval, the key of the upper node includes the identifier of the upper node and the level of the upper node in the tree structure, and the value of the upper node includes the identifier of the child node of the upper node; or a memory block construction unit, which can be used to generate memory block information based on the upper nodes and child nodes newly added in each interval, the memory block information of the upper node includes the digital number of the upper node, the level of the upper node in the tree structure and the digital number of the child node of the upper node.

[0139] In one embodiment, the knowledge point display module 1310 may include: a sub-node display unit, which obtains and displays the content of the sub-node of the node corresponding to the target question; and a layer-by-layer display unit, which can be used to display the content of the sub-node of the sub-node according to a click operation on the content of the sub-node of the node corresponding to the target question.

[0140] In one embodiment, the knowledge simplification and display device 1300 may also include: a target sub-node determination module, which can be used to determine the target sub-node in the tree structure according to the operation of the displayed target problem; a selection result determination module, which can be used to determine the selection result of the target problem according to the median of the knowledge points in the interval where the target sub-node is located; and a conclusion generation module, which can be used to generate conclusion information according to the selection result of the target problem.

[0141] In one embodiment, the knowledge point display module 1310 may include: a question-to-be-input display unit, which can be used to obtain and display the question to be input; a target question determination unit, which can be used to process the input information of the question to be input and determine the target question according to the processing result; and a target question display unit, which can be used to display the target question according to the tree structure.

[0142] Refer to the following Fig.14 14 to 15. The electronic device 1400 according to this embodiment of the present invention is described. Fig.14 The electronic device 1400 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0143] like Fig.14 As shown, the electronic device 1400 is in the form of a general computing device. The components of the electronic device 1400 may include but are not limited to: at least one processing unit 1410, at least one storage unit 1420, and a bus 1430 connecting different system components (including the storage unit 1420 and the processing unit 1410).

[0144] The storage unit stores program codes, which can be executed by the processing unit 1410, so that the processing unit 1410 performs the steps according to various exemplary embodiments of the present invention described in the above “Exemplary Method” section of this specification. For example, the processing unit 1410 can perform the following steps: Figure 1 or Figure 2 or Figure 3 Follow the steps shown in .

[0145] The storage unit 1420 may include a readable medium in the form of a volatile storage unit, such as a random access storage unit (RAM) 14201 and / or a cache storage unit 14202 , and may further include a read-only storage unit (ROM) 14203 .

[0146] The storage unit 1420 may also include a program / utility 14204 having a set (at least one) of program modules 14205, such program modules 14205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0147] Bus 1430 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0148] The electronic device 1400 may also communicate with one or more external devices 1500 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 1400, and / or communicate with any device that enables the electronic device 1400 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 1450. In addition, the electronic device 1400 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter 1460. As shown, the network adapter 1460 communicates with other modules of the electronic device 1400 via a bus 1430. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 1400, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0149] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0150] In an exemplary embodiment of the present disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the above method of the present specification is stored. In some possible implementations, various aspects of the present invention can also be implemented in the form of a program product, which includes a program code, and when the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps according to various exemplary embodiments of the present invention described in the above "Exemplary Method" section of the present specification.

[0151] The program product may use any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0152] Computer readable signal media may include data signals propagated in baseband or as part of a carrier wave, in which readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Readable signal media may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0153] The program code embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the foregoing.

[0154] Program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., through the Internet using an Internet service provider).

[0155] In addition, the above-mentioned figures are only schematic illustrations of the processes included in the method according to an exemplary embodiment of the present invention, and are not intended to be limiting. It is easy to understand that the processes shown in the above-mentioned figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.

[0156] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are to be considered exemplary only, and the true scope and concept of the present disclosure are indicated by the claims.

Claims

1. A method for simplifying and displaying knowledge, characterized in that: include: Obtaining knowledge points under a target question, wherein the knowledge points include knowledge point values; Determine a discrete degree index of the knowledge point under the target question according to the knowledge point value of the knowledge point; Dividing the knowledge points under the target problem into multiple levels according to the discrete degree index of the knowledge points under the target problem; constructing a tree structure according to the plurality of levels; Displaying the target problem according to the tree structure; Wherein, determining the discrete degree index of the knowledge point under the target problem according to the knowledge point value of the knowledge point includes: calculating the discrete coefficient of the knowledge point under the target problem according to the knowledge point value of the knowledge point; if the discrete coefficient is greater than the discrete coefficient threshold, calculating the deviation value of the knowledge point under the target problem from the median according to the knowledge point value of the knowledge point; if there is a deviation knowledge point under the target problem whose deviation value from the median is less than the deviation threshold, determining the limit value of the target problem; if the knowledge point value of the deviation knowledge point exceeds the limit value of the target problem, determining that the discrete degree index of the knowledge point under the target problem is a high discrete degree; Among them, dividing the knowledge points under the target problem into multiple levels according to the discrete degree index of the knowledge points under the target problem includes: if the discrete degree index of the knowledge points under the target problem is a high discrete degree, determining a first deviation knowledge point in the deviation knowledge points that is greater than the upper limit value in the limit value of the target problem, and a second deviation knowledge point that is less than the lower limit value in the limit value of the target problem; dividing the first deviation knowledge point into a first interval; dividing the second deviation knowledge point into a second interval; dividing the remaining knowledge points under the target problem except the first deviation knowledge point and the second deviation knowledge point into a third interval; adding an upper-level node for each interval between the knowledge points under each interval and the target problem; using the newly added upper-level node in each interval as a child node under the target problem, and the knowledge points under each interval as child nodes of the upper-level node of each interval, to generate multiple levels under the target problem.

2. The method according to claim 1, characterized in that Building a tree structure based on multiple levels includes: Generate key value information according to the upper nodes and child nodes newly added in each interval, wherein the key of the upper node includes the identifier of the upper node and the level of the upper node in the tree structure, and the value of the upper node includes the identifier of the child node of the upper node; or Memory block information is generated according to the newly added upper nodes and child nodes in each interval, and the memory block information of the upper node includes the digital number of the upper node, the level of the upper node in the tree structure and the digital number of the child node of the upper node.

3. The method according to claim 1, characterized in that Displaying the target problem according to the tree structure includes: Obtain and display the content of the child nodes of the node corresponding to the target question; The content of the sub-node of the node corresponding to the target question is displayed according to a click operation on the content of the sub-node of the sub-node.

4. The method according to claim 1, characterized in that Also includes: Determine a target subnode in the tree structure according to an operation on the displayed target problem; Determining a selection result of the target question according to the median of the knowledge points in the interval where the target subnode is located; The conclusion information is generated according to the selection result of the target question.

5. The method according to claim 1, characterized in that Displaying the target problem according to the tree structure includes: Get the question to be input and display it; Processing the input information of the question to be input, and determining the target question according to the processing result; The target question is displayed according to the tree structure.

6. A knowledge simplification and display device, characterized in that: include: A knowledge point acquisition module is used to acquire knowledge points under a target question, wherein the knowledge points include knowledge point values; A discrete degree calculation module, used to determine a discrete degree index of the knowledge point under the target question according to the knowledge point value of the knowledge point; A hierarchical division module, used to divide the knowledge points under the target problem into multiple hierarchies according to the discrete degree index of the knowledge points under the target problem; A tree structure building module, used to build a tree structure according to the multiple levels; A knowledge point display module, used for displaying the target question according to the tree structure; Among them, the discrete degree calculation module also includes: a discrete coefficient calculation unit, which is used to calculate the discrete coefficient of the knowledge point under the target problem according to the knowledge point value of the knowledge point; a deviation value calculation unit, which is used to calculate the deviation value of the knowledge point under the target problem from the median according to the knowledge point value of the knowledge point if the discrete coefficient is greater than the discrete coefficient threshold; a deviation value comparison unit, which is used to determine the limit value of the target problem if there is a deviation knowledge point under the target problem whose deviation value from the median is less than the deviation threshold; a limit value comparison unit, which is used to determine that the discrete degree index of the knowledge point under the target problem is a high discrete degree if the knowledge point value of the deviation knowledge point exceeds the limit value of the target problem; Among them, the hierarchical division module also includes: a knowledge point division unit, which is used to determine the first deviation knowledge point in the deviation knowledge point that is greater than the upper limit value in the limit value of the target problem, and the second deviation knowledge point that is less than the lower limit value in the limit value of the target problem if the discrete degree index of the knowledge point under the target problem is a high discrete degree; a first interval unit, which is used to divide the first deviation knowledge point into a first interval; a second interval unit, which is used to divide the second deviation knowledge point into a second interval; a third interval unit, which is used to divide the remaining knowledge points under the target problem except the first deviation knowledge point and the second deviation knowledge point into a third interval; an upper-level node adding unit, which is used to add an upper-level node to each interval between the knowledge points under each interval and the target problem; a hierarchical construction unit, which is used to use the upper-level node added to each interval as a child node under the target problem, and the knowledge points under each interval as child nodes of the upper-level node of each interval, to generate multiple levels under the target problem.

7. An electronic device, characterized in that: include: one or more processors; A storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 5.

8. A computer readable medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

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