Intelligent question and answer method and system based on information security protection

Abstract

The invention discloses an intelligent question answering method and system based on information security protection, and the method comprises the following steps: judging whether external knowledge needs to be called for replying when a user question is received; if it is judged that external knowledge needs to be called for replying, whether the user question meets a question layering condition or not is judged; if it is judged that the user question meets the question layering condition, a corresponding layering strategy is adopted to disassemble the user question into a plurality of sub-questions; respectively judging whether each sub-problem contains confidential information or not; if it is judged that the sub-problems contain the confidential information, information leakage prevention processing is carried out on the sub-problems containing the confidential information; and replying the sub-questions not containing the confidential information and the sub-questions after the information leakage prevention processing. Therefore, not only is the reliability of question reply improved, but also the security of information in the question answering process is greatly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent question answering, and in particular to an intelligent question answering method and system based on information security protection. Background Art

[0002] In the related art, after receiving a question uploaded by a user, a reply is usually given to the question based on a pre-set answer database. There is often a risk of confidential information leakage during the question-and-answer process, and the reliability of the reply is low because the question is only replied based on the answer database. Summary of the invention

[0003] In order to solve the above technical problems, the present invention provides an intelligent question-answering method based on information security protection. When receiving a user question, the user question is answered by combining external knowledge, thereby improving the reliability of the question answering. Moreover, when answering the user question, the user question is first broken down, and then the answer is given only after ensuring that the broken down sub-questions do not contain confidential information, thereby greatly improving the security of information in the question-answering process.

[0004] The technical solution adopted by the present invention is as follows:

[0005] An intelligent question-answering method based on information security protection comprises the following steps: upon receiving a user question, determining whether it is necessary to call external knowledge for a reply; if it is determined that it is necessary to call external knowledge for a reply, determining whether the user question satisfies a question stratification condition; if it is determined that the user question satisfies the question stratification condition, using a corresponding stratification strategy to decompose the user question into a plurality of sub-questions; determining whether each of the sub-questions contains confidential information; if it is determined that the sub-question contains confidential information, performing information leakage prevention processing on the sub-question containing confidential information; and replying to the sub-questions that do not contain confidential information and the sub-questions that have been subjected to information leakage prevention processing.

[0006] In one embodiment of the present invention, determining whether it is necessary to call the external knowledge for reply specifically includes: determining whether the user question contains enterprise characteristic information; if the user question does not contain the enterprise characteristic information, determining that it is necessary to call the external knowledge for reply; if the user question contains the enterprise characteristic information, performing feature matching and confidentiality matching on the user question and the internal mechanism, calculating the reply confidence of the internal knowledge, and determining whether the reply confidence is less than a first preset value; if the match fails and the reply confidence is less than the first preset value, determining that it is necessary to call the external knowledge for reply.

[0007] In one embodiment of the present invention, determining whether the user question satisfies the question stratification condition specifically includes: determining whether the user question contains iconic keywords, or determining whether the user question contains question structure features, or determining whether the user question contains separators, or determining whether the user question contains multiple information types; if it is determined that the user question contains the iconic keywords, or the user question contains the question structure features, or the user question contains the separators, or the user question contains multiple information types, then it is determined that the user question satisfies the question stratification condition.

[0008] In one embodiment of the present invention, determining whether the sub-problem contains the confidential information specifically includes: obtaining a corresponding first confidential keyword database according to the field to which the sub-problem belongs; performing confidential keyword recognition on the document to be identified corresponding to the sub-problem according to the first confidential keyword database to obtain the first confidential keyword contained in the document to be identified; determining whether the first confidential keyword determined based on the first confidential keyword database has a single meaning in a preset language environment; if the first confidential keyword has a single meaning in the preset language environment, determining that the first confidential keyword is the confidential information in the sub-problem; if the first confidential keyword has multiple meanings in the preset language environment, determining whether the first confidential keyword is the confidential information in the sub-problem according to the document to be identified, a first meaning feature corresponding to the first confidential keyword, and a second meaning feature corresponding to the first confidential keyword.

[0009] In one embodiment of the present invention, the first confidential keyword database includes a first meaning feature and a second meaning feature corresponding to the confidential keyword, and determining whether the first confidential keyword is the confidential information in the sub-problem according to the document to be identified, the first meaning feature corresponding to the first confidential keyword, and the second meaning feature corresponding to the first confidential keyword specifically includes: obtaining the first meaning feature and the second meaning feature corresponding to the first confidential keyword from the first confidential keyword database according to the first confidential keyword; obtaining the third meaning feature of the first confidential keyword in the document to be identified; and determining whether the first confidential keyword is the confidential information in the sub-problem according to the first meaning feature, the second meaning feature, and the third meaning feature.

[0010] In one embodiment of the present invention, determining whether the first confidential keyword is the confidential information in the sub-problem based on the first meaning feature, the second meaning feature and the third meaning feature specifically includes: calculating a first Euclidean distance between the third meaning feature and the first meaning feature, and calculating a second Euclidean distance between the third meaning feature and the second meaning feature; and determining whether the first confidential keyword is the confidential information in the sub-problem based on the first Euclidean distance and the second Euclidean distance.

[0011] An intelligent question-answering system based on information security protection comprises: a first judgment module, the first judgment module is used to judge whether it is necessary to call external knowledge for replying when receiving a user question; a second judgment module, the second judgment module is used to judge whether the user question meets the question stratification condition when judging that the external knowledge needs to be called for replying; a question decomposition module, the question decomposition module is used to adopt the corresponding stratification strategy to decompose the user question into multiple sub-questions when judging that the user question meets the question stratification condition; a third judgment module, the third judgment module is used to judge whether each of the sub-questions contains confidential information; an information processing module, the information processing module is used to perform anti-violation processing on the sub-questions containing confidential information when judging that the sub-questions contain confidential information; a question reply module, the question reply module is used to reply to the sub-questions that do not contain confidential information and the sub-questions that have been processed for anti-violation.

[0012] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the above-mentioned intelligent question-answering method based on information security protection is implemented.

[0013] A non-temporary computer-readable storage medium stores a computer program, which, when executed by a processor, implements the above-mentioned intelligent question-answering method based on information security protection.

[0014] Beneficial effects of the present invention:

[0015] When receiving a user question, the present invention responds to the user question by combining external knowledge, thereby improving the reliability of the response to the question. Moreover, when responding to the user question, the user question is first decomposed, and then the response is made after ensuring that the decomposed sub-questions do not contain confidential information, thereby greatly improving the security of information in the question-answering process. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 The present invention is a flowchart of an intelligent question-answering method based on information security protection according to an embodiment of the present invention.

[0017] Figure 2Schematic diagram of a block diagram of an intelligent question-answering system based on information security protection according to an embodiment of the present invention. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] like Figure 1 As shown, the intelligent question-answering method based on information security protection of an embodiment of the present invention may include the following steps:

[0020] S1, when receiving a user question, determine whether it is necessary to call external knowledge to respond.

[0021] In one embodiment of the present invention, determining whether external knowledge needs to be called for reply specifically includes the following steps:

[0022] S11, determining whether the user's question contains enterprise feature information.

[0023] S12, if the user's question does not contain enterprise feature information, it is determined that external knowledge needs to be called for a response;

[0024] S13, if the user question contains enterprise feature information, feature matching and confidentiality matching are performed between the user question and the internal mechanism, and the reply confidence of the internal knowledge is calculated, and it is determined whether the reply confidence is less than a first preset value;

[0025] Specifically, if the user question does not contain information about related companies, it means that internal knowledge alone cannot support the response to the user question. Therefore, external knowledge needs to be called for a response. If the user question contains information about related companies, further feature matching and confidentiality level matching are performed, that is, internal feature conformity judgment is performed, and whether the confidentiality level of the user question matches the preset confidentiality level is judged. If the confidentiality level of the user question matches the preset confidentiality level, then this part of the user question can only be answered using internal knowledge. At the same time, the response confidence of the internal knowledge can also be calculated, and it can be judged whether the response confidence is less than the first preset value.

[0026] Specifically, first, you can query the historical records for similar questions (questions of the same type as the current user's question) that use internal knowledge to answer, and calculate the maximum similarity between each similar question and the current user's question, as well as obtain the keyword coverage of the internal knowledge relative to the current user's question, and obtain the probability value of the internal knowledge answering the current user's question based on the prediction model; then, calculate the confidence level of the internal knowledge response based on the maximum similarity between each similar question and the current user's question, the keyword coverage of the internal knowledge relative to the current user's question, and the probability value of the internal knowledge answering the current user's question based on the prediction model.

[0027] Among them, the response confidence can be calculated by the following formula:

[0028]

[0029] Among them, ZD is the reply confidence, M is the maximum similarity between each similar question and the current user question, f1 is the keyword coverage of internal knowledge relative to the current user question, g1 is the probability value, a1, a2 and K are all constants greater than 0, α is the adjustment factor, k1 is the first weight value, k2 is the second weight value, and k3 is the third weight value.

[0030] S14: If the match fails and the reply confidence is less than a first preset value, it is determined that external knowledge needs to be called for reply.

[0031] Among them, if the match fails and the response confidence is less than the first preset value, it is determined that external knowledge needs to be called for response; if the match is successful, or the response confidence is greater than the first preset value, it is determined that only internal knowledge is used to respond to the user's question.

[0032] Specifically, when it is determined that only internal knowledge is used to answer user questions, the internal knowledge stored internally can be called. At this time, it can be determined whether the internal knowledge acquisition authority is available. Among them, whether the internal knowledge acquisition authority is available can be determined by authenticating the user who inputs the user question. If it is determined that the internal knowledge acquisition authority is available, the internal response model is called for interaction, that is, the knowledge in the cache area or the answer hotspot record area is called for response; if it is determined that the internal knowledge acquisition authority is not available, a risk control audit is performed.

[0033] S2: If it is determined that external knowledge needs to be called for a response, then it is determined whether the user's question meets the question stratification conditions.

[0034] S3: If it is determined that the user problem meets the problem stratification conditions, the corresponding stratification strategy is used to decompose the user problem into multiple sub-problems.

[0035] In one embodiment of the present invention, it is possible to determine whether the user question contains iconic keywords, for example, whether it contains multiple logical relationship words, such as "and", "or", "because", etc., or determine whether the user question contains question structure features, such as a subject-predicate-object structure, or determine whether the user question contains separators, or determine whether the user question contains multiple information types, such as a cause analysis type and a competition situation type. If it is determined that the user question contains iconic keywords, or the user question contains question structure features, or the user question contains separators, or the user question contains multiple information types, then it is determined that the user question meets the question stratification conditions; otherwise, it is determined that the user question does not meet the question stratification conditions. When it is determined that the user question meets the question stratification conditions, a corresponding stratification strategy is used to decompose the user question into multiple sub-questions, that is, corresponding stratification strategies are adopted for different situations.

[0036] Therefore, by dividing the user's question into multiple sub-questions for answering, it is possible to effectively avoid the situation where the adopted question answering model recognizes the complete question, thereby improving information security.

[0037] S4, determine whether each sub-question contains confidential information.

[0038] In one embodiment of the present invention, determining whether a sub-question contains confidential information specifically includes the following steps:

[0039] S41, obtaining a corresponding first confidential keyword database according to the field to which the sub-question belongs.

[0040] The confidential keywords in the first confidential keyword database may be confidential keywords pre-set by the relevant enterprise. It is understandable that the confidential keywords are different for different fields.

[0041] S42, performing confidential keyword recognition on the document to be recognized corresponding to the sub-question according to the first confidential keyword database to obtain the first confidential keyword contained in the document to be recognized;

[0042] The document to be identified corresponding to the sub-question can be identified through the confidential keywords stored in the first confidential keyword database, and the identified words are used as the first confidential keywords of the document to be identified.

[0043] However, since the same word may have different meanings in different language environments, for example, for the confidential keyword "core", the meaning expressed in the language environment of "core technology" and "core data" can be regarded as confidential information, while the meaning expressed in the language environment of "enterprises should take employees as the core" should be non-confidential information. If the first confidential keyword is regarded as confidential information only in the above manner, the accuracy of confidential keyword recognition will be greatly reduced. Therefore, in the present invention, after the first confidential keyword contained in the document to be recognized is recognized in the above manner, step S43 is continued.

[0044] S43, judging whether the first confidential keyword determined based on the first confidential keyword database has a single meaning in a preset language environment.

[0045] S44: If the first confidential keyword has a single meaning in the preset language environment, the first confidential keyword is determined to be confidential information in the sub-question.

[0046] The preset language environment may be a language environment pre-set by the relevant enterprise according to the actual situation. For example, for the scenario where the enterprise is developing a new related product, the preset language environment may be the language environment in which the user learns about the product from the relevant enterprise. If the first confidential keyword has a single meaning in the preset language environment, for example, "the product is manufactured using a certain manufacturing process", where "a certain manufacturing process" has a single meaning in the preset language environment, it can be directly determined as confidential information in the sub-question.

[0047] S45, if the first confidential keyword has more than one meaning in the preset language environment, determine whether the first confidential keyword is confidential information in the sub-question according to the document to be identified, the first meaning feature corresponding to the first confidential keyword, and the second meaning feature corresponding to the first confidential keyword.

[0048] The first confidential keyword database includes a first meaning feature and a second meaning feature corresponding to the confidential keyword. Specifically, the first meaning feature may be a confidential information feature, and the second meaning feature may be a non-confidential information feature.

[0049] In one embodiment of the present invention, determining whether the first confidential keyword is confidential information in the sub-problem based on the document to be identified, the first meaning feature corresponding to the first confidential keyword, and the second meaning feature corresponding to the first confidential keyword specifically includes: obtaining the first meaning feature and the second meaning feature corresponding to the first confidential keyword from a first confidential keyword database based on the first confidential keyword; obtaining the third meaning feature of the first confidential keyword in the document to be identified; and determining whether the first confidential keyword is confidential information in the sub-problem based on the first meaning feature, the second meaning feature, and the third meaning feature.

[0050] In one embodiment of the present invention, determining whether the first confidential keyword is confidential information in a sub-problem according to the first meaning feature, the second meaning feature, and the third meaning feature specifically includes: calculating a first Euclidean distance between the third meaning feature and the first meaning feature, and calculating a second Euclidean distance between the third meaning feature and the second meaning feature; determining whether the first confidential keyword is confidential information in the sub-problem according to the first Euclidean distance and the second Euclidean distance.

[0051] Specifically, the first Euclidean distance between the third meaning feature and the first meaning feature of the document to be identified, and the second Euclidean distance between the third meaning feature and the second meaning feature of the first confidential keyword can be calculated respectively, and then the first Euclidean distance and the second Euclidean distance can be compared to determine whether the first confidential keyword is confidential information of the sub-problem according to the comparison result. Among them, if the first Euclidean distance is less than the second Euclidean distance, it means that the third meaning feature is closer to the first meaning feature, so it can be determined that the first confidential keyword is confidential information of the sub-problem; if the first Euclidean distance is greater than the second Euclidean distance, it means that the third meaning feature is closer to the second meaning feature, so it can be determined that the first confidential keyword is not confidential information of the sub-problem. It can be understood that in actual application, the situation where the first Euclidean distance is equal to the second Euclidean distance will not occur.

[0052] In this way, it is possible to more accurately identify whether a sub-question contains confidential information.

[0053] S5: If it is determined that the sub-problem contains confidential information, information leakage prevention processing is performed on the sub-problem containing the confidential information.

[0054] Specifically, for different types of confidential information, different means can be used to prevent confidential information from leakage. Specifically, numerical noise can be added to numerical information, for example, floating values ​​within a reasonable range can be added before and after specific numbers; time information can be fuzzified. In addition, semantic association can be used for processing, for example, "sales" can be replaced with "value A", "customer segmentation" can be replaced with "market segmentation", and coding can be used for processing, for example, the company name can be replaced with a code or code name.

[0055] It should be noted that after step S1, it can also be determined whether each user question contains confidential information, and according to actual needs, user questions containing confidential information can also be processed to prevent information leakage. For details, please refer to the above embodiment.

[0056] S6, respond to sub-questions that do not contain confidential information and sub-questions that have been processed to prevent information leakage.

[0057] Specifically, for sub-questions that do not contain confidential information and sub-questions that have been processed to prevent information leakage, pre-trained models can be used to respond. Among them, multi-engine search and multi-model question-and-answer methods can be used to respond. In the response process, the above methods can also be used to identify confidential information and prevent confidential information from being leaked. Correction judgments and answer aggregation are performed on the answers output by each model. Among them, answer aggregation specifically includes answer consistency verification, answer accuracy verification, answer security verification, internal answer priority mechanism, and answer reorganization mechanism.

[0058] In summary, according to the intelligent question-answering method based on information security protection of an embodiment of the present invention, when receiving a user question, it is determined whether it is necessary to call external knowledge for reply; if it is determined that external knowledge is needed for reply, it is determined whether the user question meets the question stratification condition; if it is determined that the user question meets the question stratification condition, the corresponding stratification strategy is adopted to decompose the user question into multiple sub-questions; it is determined whether each sub-question contains confidential information; if it is determined that the sub-question contains confidential information, the sub-question containing confidential information is processed for information leakage prevention; and the sub-questions that do not contain confidential information and the sub-questions that have been processed for information leakage prevention are replied. Therefore, when receiving a user question, the reliability of the question reply is improved by replying to the user question in combination with external knowledge, and when replying to the user question, the user question is first disassembled, and then the reply is made after ensuring that the disassembled sub-questions do not contain confidential information, thereby greatly improving the security of information in the question-answering process.

[0059] Corresponding to the intelligent question-answering method based on information security protection of the above-mentioned embodiment, the present invention also proposes an intelligent question-answering system based on information security protection.

[0060] like Figure 2 As shown, the intelligent question-answering system based on information security protection of an embodiment of the present invention may include: a first judgment module 100, a second judgment module 200, a question decomposition module 300, a third judgment module 400, an information processing module 500 and a question reply module 600.

[0061] Among them, the first judgment module 100 is used to determine whether it is necessary to call external knowledge for reply when receiving a user question; the second judgment module 200 is used to determine whether the user question meets the question stratification conditions when it is determined that external knowledge needs to be called for reply; the question decomposition module 300 is used to use the corresponding stratification strategy to decompose the user question into multiple sub-questions when it is determined that the user question meets the question stratification conditions; the third judgment module 400 is used to determine whether each sub-question contains confidential information; the information processing module 500 is used to perform anti-violation processing on the sub-question containing confidential information when it is determined that the sub-question contains confidential information; the question reply module 600 is used to reply to sub-questions that do not contain confidential information and sub-questions that have been processed for anti-violation.

[0062] In one embodiment of the present invention, the first judgment module 100 is specifically used to: judge whether it is necessary to call external knowledge for reply, which specifically includes: judging whether the user question contains enterprise characteristic information; if the user question does not contain enterprise characteristic information, judging that external knowledge needs to be called for reply; if the user question contains enterprise characteristic information, performing feature matching and confidentiality matching, and calculating the reply confidence of the internal knowledge, and judging whether the reply confidence is less than a first preset value; if the match is successful and the reply confidence is less than the first preset value, judging that external knowledge needs to be called for reply.

[0063] In one embodiment of the present invention, the second judgment module 200 is specifically used to: judge whether the user question contains iconic keywords, or judge whether the user question contains question structure features, or judge whether the user question contains separators, or judge whether the user question contains multiple information types; if it is judged that the user question contains iconic keywords, or the user question contains question structure features, or the user question contains separators, or the user question contains multiple information types, then it is judged that the user question meets the question stratification conditions.

[0064] In one embodiment of the present invention, the third judgment module 400 is specifically used to: obtain a corresponding first confidential keyword database according to the field to which the sub-problem belongs; perform confidential keyword recognition on the document to be identified corresponding to the sub-problem according to the first confidential keyword database to obtain the first confidential keyword contained in the document to be identified; determine whether the first confidential keyword determined based on the first confidential keyword database has a single meaning in a preset language environment; if the first confidential keyword has a single meaning in the preset language environment, determine that the first confidential keyword is confidential information in the sub-problem; if the first confidential keyword has a multiple meaning in the preset language environment, determine whether the first confidential keyword is confidential information in the sub-problem according to the document to be identified, the first meaning feature corresponding to the first confidential keyword, and the second meaning feature corresponding to the first confidential keyword.

[0065] In one embodiment of the present invention, the first confidential keyword database includes a first meaning feature and a second meaning feature corresponding to the confidential keyword, and the third judgment module 400 is specifically used to: obtain the first meaning feature and the second meaning feature corresponding to the first confidential keyword from the first confidential keyword database according to the first confidential keyword; obtain the third meaning feature of the first confidential keyword in the document to be identified; determine whether the first confidential keyword is confidential information in the sub-problem according to the first meaning feature, the second meaning feature and the third meaning feature.

[0066] In one embodiment of the present invention, the third judgment module 400 is specifically used to: calculate the first Euclidean distance between the third meaning feature and the first meaning feature, and calculate the second Euclidean distance between the third meaning feature and the second meaning feature; determine whether the first confidential keyword is confidential information of the sub-problem based on the first Euclidean distance and the second Euclidean distance.

[0067] It should be noted that for details not disclosed in the intelligent question and answer system based on information security protection in an embodiment of the present invention, please refer to the details disclosed in the intelligent question and answer method based on information security protection in an embodiment of the present invention, and the specific details will not be described here.

[0068] According to the intelligent question-answering system based on information security protection of the embodiment of the present invention, when receiving the user question, the first judgment module determines whether it is necessary to call external knowledge for reply, and when judging that it is necessary to call external knowledge for reply, the second judgment module determines whether the user question meets the question stratification condition, and when judging that the user question meets the question stratification condition, the question decomposition module adopts the corresponding stratification strategy to decompose the user question into multiple sub-questions, and the third judgment module respectively determines whether each sub-question contains confidential information, and when judging that the sub-question contains confidential information, the information processing module performs anti-violation processing on the sub-question containing confidential information, and the question reply module replies to the sub-question that does not contain confidential information and the sub-question that has been processed for anti-violation. Therefore, when receiving the user question, the user question is replied by combining external knowledge, which improves the reliability of the question reply, and when replying to the user question, the user question is first decomposed, and then the reply is made after ensuring that the decomposed sub-questions do not contain confidential information, thereby greatly improving the security of information in the question-answering process.

[0069] Corresponding to the above embodiment, the present invention also provides a computer device.

[0070] The computer device of an embodiment of the present invention includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the intelligent question-answering method based on information security protection of the above embodiment is implemented.

[0071] According to the computer device of the embodiment of the present invention, when receiving a user question, the computer device responds to the user question by combining external knowledge, thereby improving the reliability of the response to the question. Moreover, when responding to the user question, the computer device first decomposes the user question and then responds after ensuring that the decomposed sub-questions do not contain confidential information, thereby greatly improving the security of information during the question-and-answer process.

[0072] Corresponding to the above embodiment, the present invention also proposes a non-transitory computer-readable storage medium.

[0073] The non-temporary computer-readable storage medium of an embodiment of the present invention stores a computer program, which, when executed by a processor, implements the above-mentioned intelligent question-answering method based on information security protection.

[0074] According to the non-temporary computer-readable storage medium of an embodiment of the present invention, when a user question is received, the user question is replied to in combination with external knowledge, thereby improving the reliability of the question reply. Moreover, when replying to the user question, the user question is first decomposed, and then the reply is made after ensuring that the decomposed sub-questions do not contain confidential information, thereby greatly improving the security of information in the question-and-answer process.

[0075] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. "Multiple" means two or more, unless otherwise clearly and specifically defined.

[0076] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0077] In the present invention, unless otherwise clearly specified and limited, a first feature being "above" or "below" a second feature may mean that the first and second features are in direct contact, or the first and second features are in indirect contact through an intermediate medium. Moreover, a first feature being "above", "above" or "above" a second feature may mean that the first feature is directly above or obliquely above the second feature, or simply means that the first feature is higher in level than the second feature. A first feature being "below", "below" or "below" a second feature may mean that the first feature is directly below or obliquely below the second feature, or simply means that the first feature is lower in level than the second feature.

[0078] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are contradictory.

[0079] In addition, each functional unit in each embodiment of the present invention may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0080] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. An intelligent question-answering method based on information security protection, characterized in that: The following steps are involved: When receiving a user question, determine whether external knowledge needs to be called to respond; If it is determined that external knowledge needs to be called for a response, then whether the user question meets the question stratification conditions is determined; If it is determined that the user question meets the question stratification condition, the user question is decomposed into multiple sub-questions using a corresponding stratification strategy; Determine whether each of the sub-questions contains confidential information; If it is determined that the sub-question contains confidential information, then information leakage prevention processing is performed on the sub-question containing the confidential information; Respond to sub-questions that do not contain confidential information and to sub-questions that have been processed to prevent information leakage.

2. The intelligent question-answering method based on information security protection according to claim 1 is characterized in that: Determining whether it is necessary to call the external knowledge for reply specifically includes: Determining whether the user question contains enterprise feature information; If the user question does not contain the enterprise characteristic information, it is determined that the external knowledge needs to be called for reply; If the user question contains the enterprise characteristic information, the user question is matched with the internal mechanism for characteristics and confidentiality, and the response confidence of the internal knowledge is calculated, and it is determined whether the response confidence is less than a first preset value; If the match fails and the response confidence is less than the first preset value, it is determined that the external knowledge needs to be called for response.

3. The intelligent question-answering method based on information security protection according to claim 1 is characterized in that: Determining whether the user question satisfies the question stratification condition specifically includes: Determine whether the user question contains a signature keyword, or whether the user question contains a question structure feature, or whether the user question contains a separator, or whether the user question contains multiple information types; If it is determined that the user question contains the iconic keyword, or the user question contains the question structure feature, or the user question contains the separator, or the user question contains multiple information types, then it is determined that the user question meets the question stratification condition.

4. The intelligent question-answering method based on information security protection according to claim 1 is characterized in that: Determining whether the sub-question contains the confidential information specifically includes: Acquire a corresponding first confidential keyword database according to the field to which the sub-question belongs; Perform confidential keyword recognition on the document to be recognized corresponding to the sub-question according to the first confidential keyword database to obtain a first confidential keyword contained in the document to be recognized; determining whether the first confidential keyword determined based on the first confidential keyword database has a single meaning in a preset language environment; If the first confidential keyword has a single meaning in the preset language environment, determining that the first confidential keyword is the confidential information in the sub-question; If the first confidential keyword has more than one meaning in the preset language environment, whether the first confidential keyword is the confidential information in the sub-question is determined based on the document to be identified, the first meaning feature corresponding to the first confidential keyword, and the second meaning feature corresponding to the first confidential keyword.

5. The intelligent question-answering method based on information security protection according to claim 4 is characterized in that: The first confidential keyword database includes a first meaning feature and a second meaning feature corresponding to the confidential keyword, and determining whether the first confidential keyword is the confidential information in the sub-question according to the document to be identified, the first meaning feature corresponding to the first confidential keyword, and the second meaning feature corresponding to the first confidential keyword specifically includes: Acquire a first meaning feature and a second meaning feature corresponding to the first confidential keyword from the first confidential keyword database according to the first confidential keyword; Acquire a third meaning feature of the first confidential keyword in the document to be identified; It is determined whether the first confidential keyword is the confidential information in the sub-question according to the first meaning feature, the second meaning feature and the third meaning feature.

6. The intelligent question-answering method based on information security protection according to claim 5 is characterized in that: Determining whether the first confidential keyword is the confidential information in the sub-question according to the first meaning feature, the second meaning feature, and the third meaning feature specifically includes: Calculating a first Euclidean distance between the third meaning feature and the first meaning feature, and calculating a second Euclidean distance between the third meaning feature and the second meaning feature; It is determined whether the first confidential keyword is the confidential information of the sub-problem according to the first Euclidean distance and the second Euclidean distance.

7. An intelligent question-answering system based on information security protection, characterized in that: include: A first judgment module, which is used to judge whether it is necessary to call external knowledge to reply when receiving a user question; A second judgment module, the second judgment module is used to judge whether the user question meets the question stratification condition when judging that external knowledge needs to be called for reply; A problem decomposition module, which is used to decompose the user problem into multiple sub-problems by adopting a corresponding stratification strategy when judging that the user problem meets the problem stratification condition; A third judgment module, the third judgment module is used to judge whether each of the sub-questions contains confidential information; An information processing module, the information processing module is used to perform anti-violation processing on the sub-question containing confidential information when it is determined that the sub-question contains confidential information; The question reply module is used to reply to sub-questions that do not contain confidential information and sub-questions that have been processed to prevent violations.

8. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the intelligent question-answering method based on information security protection according to any one of claims 1-6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, an intelligent question-answering method based on information security protection according to any one of claims 1 to 6 is implemented.

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