Target information acquisition method based on ontology representation, storage medium and electronic equipment

Abstract

The embodiment of the invention provides an ontology representation-based target information acquisition method. The method comprises the following steps of: acquiring multiple pieces of mapping relationship information among elements in ontology representation; the multiple pieces of mapping relation information are divided into multiple pieces of first mapping relation information and multiple pieces of second mapping relation information according to the query frequency, and the multiple pieces of first mapping relation information and the multiple pieces of second mapping relation information are different from each other; and storing the plurality of pieces of first mapping relation information in a first lookup table, and storing the plurality of pieces of second mapping relation information in a second lookup table. The embodiment of the invention further provides a computer readable storage medium and electronic equipment.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method for acquiring knowledge expression in a high-order artificial intelligence (AI) language, and more specifically to a method, storage medium, and electronic device for acquiring target information based on ontology representation. Background Art

[0002] With the rise of AI, developing a high-level AI language that supports artificial general intelligence (AGI) is one of the key topics in AGI engineering. As a form of knowledge expression about the real world or one of its components, ontology has applications in areas including, but not limited to, artificial intelligence, the semantic web, software engineering, biomedical informatics, library science, and information architecture. As one of the fundamental submodules of high-level AI languages, ontology representation (i.e., the representation of ontological knowledge) is responsible for bridging the gap between data knowledge and internal cognitive reasoning and external event interactions. In computer science and information science, ontological knowledge includes representing, formally naming, and defining concepts, data, categories, attributes, and relationships between entities. Ontologies often store data and connections between data in the form of knowledge graphs, making them one of the most common data storage formats.

[0003] In the process of realizing the concept of the present invention, the inventors found that there are at least the following problems in the related art: there are many types of implementations based on the Ontology Knowledge Language (OWL) in the related art, each targeting different special scenarios, and the corresponding syntax is also different. It is difficult for users or AI agents to quickly and accurately obtain target information through ontology representation.

[0004] Those skilled in the art urgently need to develop a method for quickly and accurately acquiring target information based on ontology representation, so as to quickly and accurately acquire target information. Summary of the Invention

[0005] In view of this, the technical problem to be solved by the present invention is to provide a target information acquisition method, storage medium and electronic device based on ontology representation, which solves the problem in related technologies that it is difficult for users or AI agents to quickly and accurately obtain target information through ontology representation.

[0006] In order to solve the above technical problems, a specific embodiment of the present invention provides a target information acquisition method based on ontology representation, including: obtaining multiple mapping relationship information between elements in the ontology representation; dividing the multiple mapping relationship information into multiple first mapping relationship information and multiple second mapping relationship information according to the query frequency, wherein the multiple first mapping relationship information and the multiple second mapping relationship information are different from each other; and storing the multiple first mapping relationship information in a first query table, and storing the multiple second mapping relationship information in a second query table.

[0007] Optionally, after storing multiple first mapping relationship information in a first query table and multiple second mapping relationship information in a second query table, the target information acquisition method based on ontology representation also includes: querying target information in the first query table according to input information; if the target information is not found in the first query table; and querying target information in the second query table.

[0008] Optionally, after querying the target information in the second query table, the target information acquisition method based on ontology representation also includes: if the target information is queried in the second query table; updating the first query frequency of the second mapping relationship information corresponding to the target information; if the first query frequency is greater than the first set value; and storing the second mapping relationship information corresponding to the target information in the first query table.

[0009] Optionally, if the target information is found in the second query table, the target information acquisition method based on ontology representation also includes: outputting readable information of the target information, wherein the target information includes readable information and non-readable information, and the readable information and the non-readable information are separated by special symbols.

[0010] Optionally, after storing the second mapping relationship information corresponding to the target information in the first query table, the target information acquisition method based on ontology representation further includes: deleting the second mapping relationship information corresponding to the target information from the second query table.

[0011] Optionally, after updating the first query frequency of the second mapping relationship information corresponding to the target information, the target information acquisition method based on ontology representation also includes: modifying the target information to obtain first modified target information, wherein the first modified target information corresponds to the first query frequency after the second mapping relationship information is updated; if the first query frequency is greater than the first set value; and storing the second mapping relationship information corresponding to the first modified target information in the first query table.

[0012] Optionally, after querying the target information in the first query table according to the input information, the target information acquisition method based on ontology representation also includes: if the target information is queried in the first query table; updating the second query frequency of the first mapping relationship information corresponding to the target information; if the second query frequency is greater than the second set value; and storing the first mapping relationship information corresponding to the target information in the third query table.

[0013] Optionally, after updating the second query frequency of the first mapping relationship information corresponding to the target information, the target information acquisition method based on ontology representation also includes: modifying the target information to obtain second modified target information, wherein the second modified target information corresponds to the second query frequency after the first mapping relationship information is updated; if the second query frequency is greater than the second set value; and storing the first mapping relationship information corresponding to the second modified target information in a third query table.

[0014] Optionally, before querying the target information in the first query table according to the input information, the method for acquiring target information based on ontology representation further includes: querying the target information in the third query table according to the input information.

[0015] Optionally, after storing the first mapping relationship information corresponding to the target information in the third query table, the target information acquisition method based on ontology representation further includes: deleting the first mapping relationship information corresponding to the target information from the first query table.

[0016] Optionally, the input information includes at least one of letters, numbers and common symbols.

[0017] Another aspect of an embodiment of the present invention provides an electronic device, including one or more processors and a storage device, wherein the storage device is used to store executable instructions, and when the executable instructions are executed by the processor, the method of the embodiment of the present invention is implemented.

[0018] Another aspect of an embodiment of the present invention provides a computer-readable storage medium storing computer-executable instructions, which are used to implement the method of the embodiment of the present invention when executed by a processor.

[0019] Another aspect of an embodiment of the present invention provides a computer program, which includes computer-executable instructions. When the instructions are executed, they are used to implement the method of the embodiment of the present invention.

[0020] According to the above-mentioned embodiment of the present invention, an exclusive table of the correspondence between classes, individuals and attributes is established, and frequently queried information is stored in a commonly used exclusive table. This can at least partially solve the problem in related technologies that it is difficult for users or AI agents to quickly and accurately obtain target information through ontology representation, and thus achieve the technical effect of quickly and accurately obtaining target information using ontology representation.

[0021] It should be understood that the foregoing general description and the following detailed description are merely exemplary and illustrative and are not intended to limit the scope of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The accompanying drawings, which are part of the specification of the present invention, illustrate exemplary embodiments of the present invention and, together with the description, serve to explain the principles of the present invention.

[0023] Figure 1 This is a first schematic flow chart of a method for acquiring target information based on ontology representation provided in a specific embodiment of the present invention.

[0024] Figure 2 A schematic diagram of the mapping relationship between elements in an ontology representation provided in a specific embodiment of the present invention.

[0025] Figure 3 This is a second schematic flow chart of a method for acquiring target information based on ontology representation provided in a specific embodiment of the present invention.

[0026] Figure 4 This is a third schematic flow chart of a method for acquiring target information based on ontology representation provided in a specific embodiment of the present invention.

[0027] Figure 5 This is a fourth schematic flow chart of a method for acquiring target information based on ontology representation provided in a specific embodiment of the present invention.

[0028] Figure 6 A schematic diagram of the composition of target information provided by a specific embodiment of the present invention.

[0029] Figure 7 This is a fifth schematic flow chart of a method for acquiring target information based on ontology representation provided in a specific embodiment of the present invention.

[0030] Figure 8 This is a sixth schematic flow chart of a method for acquiring target information based on ontology representation provided in a specific embodiment of the present invention.

[0031] Figure 9 This is a seventh schematic flow chart of a method for acquiring target information based on ontology representation provided in a specific embodiment of the present invention.

[0032] Figure 10 This is an eighth schematic flow chart of a method for acquiring target information based on ontology representation provided in a specific embodiment of the present invention.

[0033] Figure 11 This is a ninth schematic flow chart of a method for acquiring target information based on ontology representation provided in a specific embodiment of the present invention.

[0034] Figure 12 A schematic diagram of another mapping relationship between elements in an ontology representation provided in a specific embodiment of the present invention.

[0035] Figure 13The tenth schematic flow chart of a method for acquiring target information based on ontology representation provided in a specific embodiment of the present invention. DETAILED DESCRIPTION

[0036] In order to make the objectives, technical solutions and advantages of the embodiments of the present invention more clearly understood, the spirit of the contents disclosed in the present invention will be clearly illustrated with the accompanying drawings and detailed descriptions below. After understanding the embodiments of the contents of the present invention, any technician in the relevant technical field can change and modify the contents of the present invention based on the techniques taught by the contents of the present invention without departing from the spirit and scope of the contents of the present invention.

[0037] The exemplary embodiments of the present invention and their description are used to explain the present invention, but are not intended to limit the present invention. In addition, elements / components with the same or similar reference numerals used in the drawings and embodiments are used to represent the same or similar parts.

[0038] The terms “first,” “second,” etc. used herein do not particularly refer to an order or sequence, nor are they intended to limit the present invention. They are merely used to distinguish elements or operations described with the same technical terms.

[0039] The directional terms used herein, such as up, down, left, right, front, or back, are only used to refer to the directions in the accompanying drawings. Therefore, the directional terms used are used to illustrate and not to limit the present invention.

[0040] The words “include,” “including,” “have,” “contain,” etc. used in this document are open-ended terms, meaning including but not limited to.

[0041] As used herein, "and / or" includes any and all combinations of the items mentioned.

[0042] Regarding "plurality" herein, "plurality" includes "two" and "more than two"; regarding "plurality groups" herein, "plurality groups" includes "two groups" and "more than two groups".

[0043] As used herein, the terms "substantially" and "approximately" are used to modify any quantity or error that may vary slightly, but such variation or error does not alter the essence of the quantity. Generally speaking, the range of such variation or error modified by such terms may be 20% in some embodiments, 10% in some embodiments, 5% in some embodiments, or other values. Those skilled in the art will appreciate that the aforementioned values ​​may be adjusted based on actual needs and are not intended to be limiting.

[0044] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0045] When expressions such as “at least one of A, B, and C, etc.” are used, they should generally be interpreted in accordance with the meaning commonly understood by those skilled in the art (e.g., “a system having at least one of A, B, and C” should include but is not limited to systems having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, and C, etc.). When expressions such as “at least one of A, B, or C, etc.” are used, they should generally be interpreted in accordance with the meaning commonly understood by those skilled in the art (e.g., “a system having at least one of A, B, or C” should include but is not limited to systems having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, and C, etc.). Those skilled in the art should also understand that any transitional conjunctions and / or phrases that essentially represent two or more optional items, whether in the specification, claims, or drawings, should be understood to provide the possibility of including one, either, or both of these items. For example, the phrase "A or B" should be understood to include the possibilities of "A" or "B", or "A and B".

[0046] In computer science and information science, ontology is used to describe the world as a set of classes (object types or concepts), attributes, and relationship types. Ontologies often store data and the connections between them in the form of knowledge graphs and are a common data storage format. Ontologies primarily consist of three elements: individuals, classes (i.e., categories), and attributes. Individuals are instances of categories; categories inherit from and are subclasses of each other; and attributes represent the characteristics of individuals and categories.

[0047] Figure 1 This is a first schematic flow chart of a method for acquiring target information based on ontology representation provided in a specific embodiment of the present invention. Figure 2 A schematic diagram of the mapping relationship between elements in an ontology representation provided in a specific embodiment of the present invention.

[0048] In the embodiment of the present invention, Figure 1 、 Figure 2 As shown, the target information acquisition method based on ontology representation may include the following operations S101 to S103:

[0049] In operation S101 : a plurality of mapping relationship information between elements in the ontology representation is obtained.

[0050] In embodiments of the present invention, elements in an ontology representation may include classes, individuals, and attributes. Mapping relationship information may include mapping information from classes to individuals, mapping information from individuals to attributes, and mapping information from attributes to individuals. For example, a black cat is an individual, belongs to the family Felidae, and has whiskers. The mapping from cat to black cat is from class to individual, from black cat to long whiskers is from individual to attribute, and from long whiskers to individual is from attribute to individual.

[0051] Next, in operation S102 : the plurality of mapping relationship information are divided into a plurality of first mapping relationship information and a plurality of second mapping relationship information according to query frequency, wherein the plurality of first mapping relationship information and the plurality of second mapping relationship information are different from each other.

[0052] In an embodiment of the present invention, the first mapping relationship information may represent mapping information that is frequently queried, and the second mapping relationship information may represent mapping information that is less frequently queried. For example, people often query whether bears include pandas, but rarely query whether bears include ring-tailed cats. Therefore, the mapping information from bears to pandas can be assigned to the first mapping relationship information, and the mapping information from bears to ring-tailed cats can be assigned to the second mapping relationship information.

[0053] Then, in operation S103 : a plurality of the first mapping relationship information is stored in a first lookup table, and a plurality of the second mapping relationship information is stored in a second lookup table.

[0054] In an embodiment of the present invention, the first query table and the second query table may include a dictionary database, etc. The first query table is used to store a plurality of the first mapping relationship information, and the second query table is used to store a plurality of the second mapping relationship information. The information stored in the first query table and the second query table is different from each other.

[0055] In the embodiment of the present invention, Figure 2 As shown, multiple mapping relationship information are classified according to query frequency and stored in different query tables. The first query table stores frequently queried mapping relationship information, and the second query table stores infrequently queried mapping relationship information. The query is first performed in the first query table and then in the second query table. The ontology representation can be used to quickly and accurately obtain the target information.

[0056] Figure 3 This is a second schematic flow chart of a method for acquiring target information based on ontology representation provided in a specific embodiment of the present invention.

[0057] In the embodiment of the present invention, Figure 3As shown, after storing the plurality of first mapping relationship information in the first query table and storing the plurality of second mapping relationship information in the second query table in operation S103, the target information acquisition method based on ontology representation may further include the following operations S104 to S106:

[0058] In operation S104 : searching the first query table for target information according to the input information.

[0059] In an embodiment of the present invention, the input information may include at least one of letters, numbers, and common symbols. For example, the input information may be English letters, numbers, or common symbols; the input information may also be a combination of English letters and numbers, a combination of English letters and common symbols, or a combination of numbers and common symbols. Common symbols may include an equal sign, a plus sign, a question mark, a greater than sign, a less than sign, etc. Uncommon symbols may include "#", "*", "&", "@", etc. The first query table stores frequently queried mapping relationship information, and querying the target information in the first query table first can improve query efficiency.

[0060] Next, in operation S105: if the target information is not found in the first query table.

[0061] In the embodiment of the present invention, if the target information is not found in the first query table, it means that the target information to be queried is not frequently queried information.

[0062] Then, in operation S106 : searching the second query table for target information.

[0063] In an embodiment of the present invention, the second query table stores mapping relationship information that is not frequently queried. If the target information is not found in the first query table, it means that the target information to be queried is not frequently queried information, and the target information can be queried in the second query table.

[0064] In an embodiment of the present invention, the first query table stores frequently queried mapping relationship information, and the second query table stores infrequently queried mapping relationship information. The target information is first queried in the first query table. If the target information cannot be found, the target information is queried in the second query table. This allows for rapid and accurate acquisition of the target information, thereby increasing the response speed and accuracy of the intelligent agent and enabling efficient interaction between the user and the intelligent force.

[0065] Figure 4 This is a third schematic flow chart of a method for acquiring target information based on ontology representation provided in a specific embodiment of the present invention.

[0066] In the embodiment of the present invention, Figure 4As shown, after operation S106 searches the second query table for target information, the method for acquiring target information based on ontology representation may further include the following operations S107 to S110:

[0067] In operation S107: if target information is found in the second query table.

[0068] In the embodiment of the present invention, the second query table stores mapping relationship information that is not frequently queried. If target information is found in the second query table, it means that the information to be queried may be frequently queried information.

[0069] Next, in operation S108 : the first query frequency of the second mapping relationship information corresponding to the target information is updated.

[0070] In an embodiment of the present invention, if the target information is found in the second query table, it indicates that the information being queried may be frequently queried information, and the query frequency of the second mapping relationship information corresponding to the target information is updated. The first query frequency may include the number of queries per day, the number of queries per week, the number of queries per month, the number of queries per quarter, or the number of queries per year.

[0071] Then, in operation S109: if the first query frequency is greater than a first set value.

[0072] In an embodiment of the present invention, if the first query frequency is greater than the first set value, it means that the information to be queried is frequently queried information, and it is not appropriate to store the second mapping relationship information corresponding to the target information in the second query table. The second mapping relationship information corresponding to the target information needs to be transferred to the first query table.

[0073] Next, in operation S110 : second mapping relationship information corresponding to the target information is stored in the first lookup table.

[0074] In the embodiment of the present invention, since the information to be queried is frequently queried information, it is not appropriate to store the second mapping relationship information corresponding to the target information in the second query table. The second mapping relationship information corresponding to the target information needs to be transferred to the first query table.

[0075] In an embodiment of the present invention, the first query table stores frequently queried mapping relationship information, while the second query table stores less frequently queried mapping relationship information. If frequently queried mapping relationship information is stored in the second query table, it is necessary to transfer this mapping relationship information to the first query table. This allows for rapid and accurate acquisition of target information, increases the speed and accuracy of the intelligent agent's response, and enables efficient interaction between the user and the intelligent agent.

[0076] Figure 5This is a fourth schematic flow chart of a method for acquiring target information based on ontology representation provided in a specific embodiment of the present invention. Figure 6 A schematic diagram of the composition of target information provided by a specific embodiment of the present invention.

[0077] In the embodiment of the present invention, Figure 5 、 Figure 6 As shown, after operation S106 searches the second query table for target information, the method for acquiring target information based on ontology representation may further include the following operation S111:

[0078] In operation S111 : outputting readable information of the target information, wherein the target information includes readable information and non-readable information, and the readable information and the non-readable information are separated by special symbols.

[0079] In the embodiment of the present invention, the target information includes readable information and non-readable information, and the readable information and the non-readable information are separated by special symbols, and the readable information is generally located after the special symbols. Figure 6 As shown, the special symbols in target information A, B, C, and D are all "#". The readable information is behind the "#". For target information A, the readable information is "bread"; for target information B, the readable information is "isFront=true"; for target information C, the readable information is "Drug"; and for target information D, the readable information is "anti-cold drug".

[0080] In this embodiment of the present invention, when inputting information, only at least one of letters, numbers, and common symbols is required; when outputting information, only readable information is required. This facilitates input and improves the readability of output information, further increasing the speed and accuracy of the intelligent agent's response, and achieving efficient interaction between users and intelligent capabilities.

[0081] Figure 7 This is a fifth schematic flow chart of a method for acquiring target information based on ontology representation provided in a specific embodiment of the present invention.

[0082] In the embodiment of the present invention, Figure 7 As shown, after operation S110 stores the second mapping relationship information corresponding to the target information in the first query table, the method for acquiring target information based on ontology representation may further include the following operation S112:

[0083] In operation S112: deleting the second mapping relationship information corresponding to the target information from the second lookup table.

[0084] In an embodiment of the present invention, after the second mapping relationship information corresponding to the target information is transferred to the first query table, the second mapping relationship information corresponding to the target information is deleted from the second query table. This saves storage space in the second query table, reduces the amount of mapping relationship information in the second query table, and improves the efficiency of searching for target information in the second query table.

[0085] In an embodiment of the present invention, redundant mapping relationship information is deleted from the second query table, saving storage space of the second query table and reducing the amount of mapping relationship information in the second query table, thereby improving the efficiency of searching for target information in the second query table, further increasing the response speed and response accuracy of the intelligent agent, and realizing efficient interaction between the user and the intelligent force.

[0086] Figure 8 This is a sixth schematic flow chart of a method for acquiring target information based on ontology representation provided in a specific embodiment of the present invention.

[0087] In the embodiment of the present invention, Figure 8 As shown, after operation S108 updates the first query frequency of the second mapping relationship information corresponding to the target information, the method for acquiring target information based on ontology representation may further include the following operations:

[0088] In operation S119 : the target information is modified to obtain first modified target information, wherein the first modified target information corresponds to the first query frequency after the second mapping relationship information is updated.

[0089] In embodiments of the present invention, target information can be modified, with the modified target information being the first modified target information. When the target information is modified, the mapping relationship may also be modified simultaneously. After the target information is modified, a copy of the target information prior to the modification is retained. The first modified target information inherits the first query frequency of the second mapping relationship information corresponding to the target information prior to the modification. When the target information and the first modified target information are subsequently queried, each updates its own query frequency.

[0090] Then, in operation S109 ′: if the first query frequency is greater than a first set value.

[0091] In the embodiment of the present invention, the first query frequency corresponds to the first modified target information. The first modified target information is queried once, and the first query frequency of the first modified target information corresponding to the second mapping relationship information is updated once.

[0092] Next, in operation S110 ′: second mapping relationship information corresponding to the first modification target information is stored in the first query table.

[0093] In an embodiment of the present invention, if the updated first query frequency of the second mapping relationship information corresponding to the first modified target information is greater than the first set value, the second mapping relationship information corresponding to the first modified target information may be stored in the first query table.

[0094] In an embodiment of the present invention, the target information is modified, and the mapping relationship corresponding to the target information may also be modified. The query frequency corresponding to the modified target information inherits the query frequency corresponding to the target information before the modification. When the query frequency corresponding to the modified target information is greater than the set value, the second mapping relationship information corresponding to the first modified target information is stored in the first query table, so as to facilitate fast, efficient and accurate query of the modified target information.

[0095] Figure 9 This is a seventh schematic flow chart of a method for acquiring target information based on ontology representation provided in a specific embodiment of the present invention.

[0096] In the embodiment of the present invention, Figure 9 As shown, after operation S104 searches the first query table for target information according to the input information, the method for acquiring target information based on ontology representation may further include the following operations S113 to S116:

[0097] Operation S113: If the target information is found in the first query table.

[0098] In an embodiment of the present invention, the first query table stores frequently queried mapping relationship information. If target information is found in the first query table, it means that the information is frequently queried.

[0099] Operation S114: updating the second query frequency of the first mapping relationship information corresponding to the target information.

[0100] In an embodiment of the present invention, after the target information is queried, the second query frequency of the first mapping relationship information corresponding to the target information is updated. The second query frequency may include the number of queries per day, the number of queries per week, the number of queries per month, the number of queries per quarter, or the number of queries per year.

[0101] Operation S115: If the second query frequency is greater than a second set value.

[0102] In an embodiment of the present invention, if the second query frequency is greater than the second set value, it means that the frequency of querying the information to be queried is particularly high. In order to further improve the query speed, a third query table can be constructed to store mapping relationship information with particularly high query frequency.

[0103] Operation S116: storing the first mapping relationship information corresponding to the target information in a third lookup table.

[0104] In an embodiment of the present invention, if the second query frequency of the first mapping relationship information corresponding to the target information is greater than the second set value, the first mapping relationship information corresponding to the target information is transferred to the third query table. Because the third query table stores mapping relationship information with a particularly high query frequency, when querying the target information, the third query table can be queried first.

[0105] In this embodiment of the present invention, the first query table stores frequently queried mapping relationship information, the second query table stores less frequently queried mapping relationship information, and the third query table stores mapping relationship information with particularly high frequency of query. When searching for target information, the third query table can be searched first; if the target information is not found in the third query table, the first query table is searched; if the target information is not found in the first query table, the second query table is searched. This further improves the speed and accuracy of acquiring target information, increases the speed and accuracy of the intelligent agent's response, and enables efficient interaction between users and intelligent capabilities.

[0106] Figure 10 This is an eighth schematic flow chart of a method for acquiring target information based on ontology representation provided in a specific embodiment of the present invention.

[0107] In the embodiment of the present invention, Figure 10 As shown, after operation S114 updates the second query frequency of the first mapping relationship information corresponding to the target information, the target information acquisition method based on ontology representation may further include the following operations S120 to S116':

[0108] In operation S120 : the target information is modified to obtain second modified target information, wherein the second modified target information corresponds to the second query frequency after the first mapping relationship information is updated.

[0109] In embodiments of the present invention, target information can be modified, and the modified target information can be used to generate second modified target information. When the target information is modified, the mapping relationship may also be modified simultaneously. After the target information is modified, a copy of the target information prior to the modification is retained. The second modified target information inherits the second query frequency of the first mapping relationship information corresponding to the target information prior to the modification. When the target information and the second modified target information are subsequently queried, each updates its own query frequency.

[0110] Then, in operation S115 ′: if the second query frequency is greater than a second set value.

[0111] In the embodiment of the present invention, the second query frequency corresponds to the second modified target information. The second modified target information is queried once, and the second modified target information is updated once corresponding to the second query frequency of the first mapping relationship information.

[0112] Next, in operation S116 ′: the first mapping relationship information corresponding to the second modification target information is stored in a third lookup table.

[0113] In an embodiment of the present invention, if the updated second query frequency of the first mapping relationship information corresponding to the second modified target information is greater than the second set value, the first mapping relationship information corresponding to the second modified target information may be stored in the third query table.

[0114] In an embodiment of the present invention, the target information is modified, and the mapping relationship corresponding to the target information may also be modified. The query frequency corresponding to the modified target information inherits the query frequency corresponding to the target information before the modification. When the query frequency corresponding to the modified target information is greater than the set value, the first mapping relationship information corresponding to the second modified target information is stored in the third query table, so as to facilitate fast, efficient and accurate query of the modified target information.

[0115] Figure 11 This is a ninth schematic flow chart of a method for acquiring target information based on ontology representation provided in a specific embodiment of the present invention. Figure 12 A schematic diagram of another mapping relationship between elements in an ontology representation provided in a specific embodiment of the present invention.

[0116] In the embodiment of the present invention, Figure 11 、 Figure 12 As shown, before operation S104 searches the first query table for target information according to input information, the method for acquiring target information based on ontology representation may further include the following operation S117:

[0117] In operation S117 , target information is searched in the third query table according to the input information.

[0118] In an embodiment of the present invention, the input information may include at least one of letters, numbers, and common symbols. For example, the input information may be English letters, numbers, or common symbols; the input information may also be a combination of English letters and numbers, a combination of English letters and common symbols, or a combination of numbers and common symbols. Common symbols may include an equal sign, a plus sign, a question mark, a greater than sign, a less than sign, etc. Uncommon symbols may include "#", "*", "&", "@", etc. See Figure 12 The first query table stores frequently queried mapping relationship information, the second query table stores infrequently queried mapping relationship information, and the third query table stores mapping relationship information with particularly high frequency of query. When searching for target information, the third query table can be searched based on the input information first; if the third query table does not find the target information, the first query table is searched again; if the first query table still does not find the target information, the second query table is searched again.

[0119] In an embodiment of the present invention, when a user or an intelligent agent (including an AI intelligent agent) inputs information for query, the third query table, the first query table and the second query table are queried in sequence until the target information is found, and readable information of the target information is quickly output to the user or intelligent agent. The target information can be obtained quickly and accurately, the reaction speed and reaction accuracy of the intelligent agent are increased, and efficient interaction between the user and the intelligent force is achieved.

[0120] Figure 13 The tenth schematic flow chart of a method for acquiring target information based on ontology representation provided in a specific embodiment of the present invention.

[0121] In the embodiment of the present invention, Figure 13 The method for obtaining target information based on ontology representation is characterized in that after operation S116 stores the first mapping relationship information corresponding to the target information in the third query table, the method for obtaining target information based on ontology representation may further include the following operation S118:

[0122] Operation S118: deleting the first mapping relationship information corresponding to the target information from the first query table.

[0123] In an embodiment of the present invention, the first mapping relationship information corresponding to the target information is transferred to the third query table and deleted from the first query table. This saves storage space in the first query table, reduces the amount of mapping relationship information in the first query table, and improves the efficiency of searching for target information in the first query table.

[0124] In an embodiment of the present invention, redundant mapping relationship information is deleted from the first query table, saving storage space of the first query table and reducing the amount of mapping relationship information in the first query table, thereby improving the efficiency of searching for target information in the first query table and further increasing the reaction speed and reaction accuracy of the intelligent agent, so that users and intelligent forces can interact efficiently.

[0125] According to an embodiment of the present invention, the method flow according to an embodiment of the present invention can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program includes program code for executing the method shown in the flowchart. According to an embodiment of the present invention, the electronic devices, devices, apparatuses, modules, units, etc. described above can be implemented by computer program modules.

[0126] The present invention also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments, or may exist independently and not incorporated into the device / apparatus / system. The computer-readable storage medium carries one or more programs, which, when executed, implement the method according to the embodiments of the present invention.

[0127] According to an embodiment of the present invention, a computer-readable storage medium may be a non-volatile computer-readable storage medium, such as, but not limited to, 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), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0128] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the above-mentioned module, program segment, or a part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0129] Those skilled in the art will appreciate that various combinations and / or combinations of features described in the various embodiments and / or claims of the present invention may be made, even if such combinations and / or combinations are not explicitly described in the present invention. In particular, various combinations and / or combinations of features described in the various embodiments and / or claims of the present invention may be made, without departing from the spirit and teachings of the present invention. All such combinations and / or combinations fall within the scope of the present invention.

[0130] The above describes embodiments of the present invention. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of the present invention. Although each embodiment has been described separately above, this does not mean that the measures in each embodiment cannot be advantageously used in combination. The scope of the present invention is defined by the appended claims and their equivalents. Without departing from the scope of the present invention, those skilled in the art may make various substitutions and modifications, which are intended to fall within the scope of the present invention.

Claims

1. A method for acquiring target information based on ontology representation, characterized in that: The method includes: Obtain multiple mapping relationship information between elements in the ontology representation; dividing the plurality of mapping relationship information into a plurality of first mapping relationship information and a plurality of second mapping relationship information according to query frequency, wherein the plurality of first mapping relationship information and the plurality of second mapping relationship information are different from each other; and The plurality of first mapping relationship information are stored in a first query table, and the plurality of second mapping relationship information are stored in a second query table.

2. The target information acquisition method based on ontology representation according to claim 1 is characterized in that: After storing the plurality of first mapping relationship information in a first query table and storing the plurality of second mapping relationship information in a second query table, the method further includes: Querying target information in the first query table according to input information; If the target information is not found in the first query table; and The target information is searched in the second query table.

3. The target information acquisition method based on ontology representation according to claim 2 is characterized in that: After searching the second query table for target information, the method further includes: If the target information is found in the second query table; Updating a first query frequency of second mapping relationship information corresponding to the target information; If the first query frequency is greater than a first set value; and The second mapping relationship information corresponding to the target information is stored in the first query table.

4. The target information acquisition method based on ontology representation according to claim 3 is characterized in that: If the target information is found in the second query table, the method further includes: Outputting readable information of the target information, wherein the target information includes readable information and non-readable information, and the readable information and the non-readable information are separated by special symbols.

5. The target information acquisition method based on ontology representation according to claim 3 is characterized in that: After storing the second mapping relationship information corresponding to the target information in the first query table, the method further includes: The second mapping relationship information corresponding to the target information is deleted from the second query table.

6. The method for acquiring target information based on ontology representation according to claim 3, characterized in that: After updating the first query frequency of the second mapping relationship information corresponding to the target information, the method further includes: Modifying the target information to obtain first modified target information, wherein the first modified target information corresponds to the first query frequency after the second mapping relationship information is updated; If the first query frequency is greater than a first set value; and The second mapping relationship information corresponding to the first modification target information is stored in the first query table.

7. The target information acquisition method based on ontology representation according to claim 2 is characterized in that: After searching the first query table for target information according to the input information, the method further includes: If the target information is found in the first query table; Updating a second query frequency of the first mapping relationship information corresponding to the target information; If the second query frequency is greater than a second set value; and The first mapping relationship information corresponding to the target information is stored in a third query table.

8. The method for acquiring target information based on ontology representation according to claim 7, characterized in that: After updating the second query frequency of the first mapping relationship information corresponding to the target information, the method further includes: Modifying the target information to obtain second modified target information, wherein the second modified target information corresponds to the second query frequency after the first mapping relationship information is updated; If the second query frequency is greater than a second set value; and The first mapping relationship information corresponding to the second modification target information is stored in a third query table.

9. The method for acquiring target information based on ontology representation according to claim 7, characterized in that: Before searching the first query table for target information according to the input information, the method further includes: The target information is searched in the third query table according to the input information.

10. The method for acquiring target information based on ontology representation according to claim 7, characterized in that: After storing the first mapping relationship information corresponding to the target information in the third query table, the method further includes: The first mapping relationship information corresponding to the target information is deleted from the first query table.

11. The method for acquiring target information based on ontology representation according to claim 2, characterized in that: The input information includes at least one of letters, numbers and common symbols.

12. A computer-readable storage medium having executable instructions stored thereon, wherein the instructions are executed by a processor to implement the method according to any one of claims 1 to 11.

13. An electronic device comprising: one or more processors; A storage device is used to store executable instructions, and when the executable instructions are executed by the processor, the method according to any one of claims 1 to 11 is implemented.

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