CN112632335A

CN112632335A - Apparatus, electronic device and computer readable medium for assisting invention

Info

Publication number: CN112632335A
Application number: CN202011105797.3A
Authority: CN
Inventors: 王楠; 蔡月; 王洪宇; 赵宏宇; 蔡洁; 李树超; 蔡利亚
Original assignee: Beijing Ruyitang Technology Co ltd
Current assignee: Beijing Ruyitang Technology Co ltd
Priority date: 2020-10-15
Filing date: 2020-10-15
Publication date: 2021-04-09

Abstract

The invention provides an auxiliary invention device, electronic equipment and a computer storage medium. The problem analysis module performs invention intention classification by analyzing input problems (pictures, texts, voice and the like) so as to obtain an innovative knowledge retrieval formula. Furthermore, in a knowledge mining module, a knowledge characteristic selection is utilized to search and mine an innovative scheme. And finally, a scheme generation module is used for realizing candidate function element screening and problem iterative updating. The invention provides a feasible tool for precise innovation, technical improvement and auxiliary industry upgrading.

Description

Apparatus, electronic device and computer readable medium for assisting invention

Technical Field

The present disclosure relates to the field of artificial intelligence, and more particularly, to the field of auxiliary innovation intelligence.

Background

The traditional auxiliary innovation method comprises methods of experience investigation, brainstorming and the like, and since 1946, a former Soviet Union team extracts a universal problem solving tool of a cross-industry technical system, namely a classic TRIZ innovation methodology from 40 thousands of patents, and comprises abstract descriptions of system analysis, a contradiction matrix, an object field model and the like, and invention information of 40 invention principles, four separation methods, 76 object field standard solutions, a scientific effect knowledge base and the like. But the classical TRIZ semantic relationship is not interpretable. For the problems, the modern TRIZ genre deepens the cognition of the evolutionary trend, the functions and the attributes, but the modern TRIZ method is difficult to retrieve the knowledge matched with the input description, and the semantic disjunction exists between the modern TRIZ method and the actual problem processing.

At present, people urgently need to explore an invention scheme which can be used for explainably fusing the existing invention information, technical documents and the like and generating feasible invention schemes in an auxiliary mode through searching and recommending.

Disclosure of Invention

In order to solve the problems, the invention provides an auxiliary invention device which generates an auxiliary invention retrieval formula based on problem input and analysis, further generates a problem solution feasibility scheme and generates an auxiliary innovation scheme through knowledge mining.

A first aspect of the present invention provides an apparatus for assisting the invention, characterized in that: the system comprises a problem analysis module, a knowledge mining module and a scheme generation module;

the problem analysis module identifies the invention intention by performing functional element analysis on the problem system and generates an auxiliary invention knowledge retrieval formula.

The function element comprises a function operation and a combination unit of at least one of an object and a parameter;

in some embodiments, the function element may be "function + object", "function + parameter", "function + object + parameter"

The functional operation is a hierarchical concept system and a relation of the functional operation and the operation object through induction and refinement;

in some embodiments, the functional operations include verbs and their multi-level conceptual structures, such as first level functions "add", second level functions "throttle";

the objects, also referred to as streams, include, but are not limited to, substances, energy, information;

in some embodiments, the substance includes objects in different forms of the solid-liquid-gas powder field, and the concept system and relationship of the objects;

the parameters comprise attributes, attribute parameters, constraint conditions, variables or characteristic parameters;

in some embodiments, the concept hierarchy comprises an ontology-level concept, a concept instance, a co-located word, a relation between upper and lower level words, and an item description explanation text of each concept; the relationship is a relationship concept and a relationship instance between elements in the ontology. For example, there exists a relationship concept "parity", "upper and lower bits" between concepts, and there also exists a relationship instance "include", "belong to", "co-occur", and the like.

The intention of the invention is to match the problem system into the functional element;

in some embodiments, the matching to the function element is to calculate a similarity between the input problem and the function element and a combination of the function elements under a certain weight policy, where the combination of the function elements may be a cluster division of related function elements according to a cluster, an association rule or a policy.

The generation of the search formula is to expand part or all of the constituent elements of the functional elements according to a concept system and then combine the elements to form a Boolean search formula;

in some embodiments, the boolean search expression is subjected to parity, upper AND lower bit expansion according to concepts of elements in functions, objects AND parameters, AND further spliced into the boolean search expression by "AND", "OR", "NOT" operators.

In some embodiments, the extension, in particular, includes a concept, instance, upper and lower voxel extension of a function, object, attribute, parameter, hierarchical relationship;

optionally, the element expansion may be synonym expansion, object or parameter replacement, etc.;

in some embodiments, the expanding further comprises designing a boolean logic rule to obtain an expanded search;

the knowledge mining module is characterized in that the knowledge comprises scientific and technological documents such as patents, thesis, technical reports and the like, and TRIZ innovation knowledge;

in some embodiments, the knowledge may be a paper abstract, patent claims, specification, or the like;

the knowledge mining comprises knowledge retrieval, recommendation, generation, question answering and reasoning, and matching scheme recall and improvement are realized.

The matching is a similarity calculation depending on the functional elements or the functional element combination;

in some embodiments, the calculation method comprises distance calculation, latent semantic model calculation, depth semantic calculation;

in some embodiments, the retrieval is based on a boolean search for matching recalls of indexed results, recommendations may be matched recalls by recommendation algorithms based on feature selection;

in some embodiments, the searching is performed by searching various knowledge by using an expanded search mode, and one or a combination of texts in recalled knowledge is matched;

in some embodiments, the recall ranking is performed by configuring a weight policy according to relevant resources, systems and component characteristics, relevant fields and selection preference constraints of the problem to be innovated;

in some embodiments, the filtering recommends one or a combination of knowledge from the ranked results according to a weighting strategy;

in some embodiments, the recommendation, including a text matching or text classification method, is iteratively optimized;

in some embodiments, the classification method may select a rule, a cluster, a classification method.

The scheme generation module carries out problem system updating through TRIZ technology trend rule screening and function element selection.

In some embodiments, the screening is to count, analyze and judge the mined candidate schemes through various technical evolution trend rules of TRIZ, and the schemes meeting the requirements of the evolution rules are screened and reserved;

in some embodiments, the filtering further comprises searching, recalling and sorting target texts from the inventions and reference text knowledge of the hierarchical index;

in some embodiments, the function element selection includes selecting a new function element, a similar function element in a different field or a different function element with similar effect, or cutting and replacing part elements of the existing function elements;

and the problem system updating is the iterative solution of the system problem after the function element selection.

The function element selection comprises selecting new function elements, similar function elements in different fields or different function elements with similar effects, and cutting and replacing part of elements of the function elements with problems

In some embodiments, existing problem function elements are represented and replaced by a series of function elements, such as "function- (description) attributes" and "function-objects".

In some embodiments, the abstract extraction is to extract a subject description sentence from a target text according to a text rule or a model to generate a text abstract;

in some embodiments, the problem system solution is generated by editing in conjunction with the invention knowledge base.

A second aspect of the invention provides an electronic device comprising one or more storage devices and a processor; storage means for storing one or more programs; when executed by the one or more processors, cause the one or more processors to implement any of the methods described above.

A third aspect of the invention provides a computer-readable storage medium having stored thereon computer-executable instructions operable, when executed by a computing device, to perform any of the methods described above.

The technical scheme of the invention has the following beneficial technical effects: a set of auxiliary invention devices are set up, from a problem system, the acquisition of functional elements is realized by inputting natural inquiry contents, the invention knowledge is further searched, and the automatic generation of the invention scheme is realized;

a set of invention scheme mining flow is designed, and auxiliary innovation schemes of problem-oriented systems are screened through semantic understanding of functional elements.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention, as claimed.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings used in the description of the embodiments will be briefly introduced below. Other features, objects, and advantages of the present disclosure will become more apparent from the following detailed description of non-limiting embodiments when taken in conjunction with the accompanying drawings. It is obvious that the drawings in the following description are only some embodiments of the application, and that it is also possible for a person skilled in the art to apply the application to other similar scenarios without inventive effort on the basis of these drawings. Unless otherwise apparent from the context of language or otherwise indicated, like reference numerals in the figures refer to like structures and operations.

The attached drawings are as follows:

FIG. 1 shows a block diagram of an inventive device for aiding in the design of a vehicle according to an embodiment of the present disclosure;

FIG. 2 illustrates a work flow diagram of module S102 according to the embodiment shown in FIG. 1;

FIG. 3 shows an implementable effect diagram of the module S102 according to the implementation shown in FIG. 1;

FIG. 4 illustrates a work flow diagram of module S104 according to the embodiment shown in FIG. 1;

FIG. 5 illustrates a work flow diagram of module S106 according to the embodiment shown in FIG. 1;

FIG. 6 shows a block diagram of an electronic device according to an embodiment of the present disclosure;

fig. 7 shows a schematic diagram of a storable medium structure suitable for implementing an auxiliary inventive apparatus electronic device according to an embodiment of the present disclosure.

Detailed Description

In the following detailed description, numerous specific details of the present application are set forth by way of examples in order to provide a thorough understanding of the relevant disclosure. It will be apparent, however, to one skilled in the art that the present application may be practiced without these specific details. It should be understood that the use of the terms "system," "apparatus," "unit" and/or "module" herein is a method for distinguishing between different components, elements, portions or assemblies at different levels of sequential arrangement. However, these terms may be replaced by other expressions if they can achieve the same purpose.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of the present application. As used in the specification and claims of this application, the terms "a", "an", and/or "the" are not intended to be inclusive in the singular, but rather are intended to be inclusive in the plural, unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" are intended to cover only the explicitly identified features, integers, steps, operations, elements, and/or components, but not to constitute an exclusive list of such features, integers, steps, operations, elements, and/or components.

The protection scope of this application is subject to the claims. Hereinafter, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily implement them. Also, for the sake of clarity, parts not relevant to the description of the exemplary embodiments are omitted in the drawings.

In the present disclosure, it is to be understood that terms such as "including" or "having," etc., are intended to indicate the presence of the disclosed features, numbers, steps, behaviors, components, parts, or combinations thereof, and are not intended to preclude the possibility that one or more other features, numbers, steps, behaviors, components, parts, or combinations thereof may be present or added. It should be further noted that the embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.

The technical scheme of the invention can be applied to the innovation aspects in a plurality of fields of auxiliary industrial design, intelligent manufacturing, product research and development and the like. Specifically, the technical solution of the present invention is mainly explored for a feasible device for assisting the invention.

A first aspect of the present invention provides an apparatus for assisting the invention, including the steps of:

the specific implementation mode is as follows:

fig. 1 shows a structure of an apparatus for assisting the invention according to an embodiment of the present disclosure, the apparatus including the following modules S102 to S106:

in the problem analysis module S102, the intention of the invention is identified and an auxiliary invention knowledge retrieval formula is generated by performing functional element analysis on a problem system;

in the knowledge mining module S104, knowledge retrieval, recommendation, generation, question answering and reasoning are carried out;

in the scenario generation module S106, the problem system is updated through TRIZ technology trend rule screening and function element selection.

in some embodiments, a function element may be "function + object", "function + parameter", "function + object + parameter";

in some embodiments, the functional elements, specifically, for example, the primary concept of functional operation "add", the instance "pile up", the object concept may be "solid", and the object instance may be "component". A set of function object concepts and instances, such as "brightness up", "temperature up", "fuel pile up", "mineral pile up", etc., can be obtained by abstracted function-object combinations;

in some embodiments, based on the TRIZ theory or other innovative theories, in combination with system analysis, functional models and functional analysis, abstracted hierarchical concepts and relationships of functional operations, such as "add" for a primary function and "throttle" for a secondary function;

in some embodiments, the substance may be an object existing in different forms of a "solid-liquid-gas powder field", and a conceptual system and relationship of the object. For example, a "solid state" computer system includes the following components: keyboard, mouse, display, power supply, etc.;

in some embodiments, parameter concepts include parameters or combinations of parameters related to the invention, generalizing the hierarchical concepts and relationships associated with the parameters. Specifically, for example, the parameter concept "field", the secondary parameter is "physical quantity", the parameter example may be "weight", and the abstract function-parameter combination may be used;

In some embodiments, the relationship includes "upper and lower", "same position", "same sense", "similar sense", "antisense", and the like, for example, the "physical quantity" is a generic concept of "weight", so that the "physical quantity" includes the example of "weight", and the "physical quantity" and "weight" are "including" relationship, which is equivalent to the "upper and lower" relationship.

Fig. 2 shows a specific work flow of the problem analysis module S102:

in step S202, the system analyzes, inputs a question;

the system analysis is based on the practical problems of innovation, industrial design, product research and development and production and the like, and various systems to be solved or innovated are summarized according to the system analysis, the resource analysis, the cause and effect analysis and the final ideal solution. In the component model of the problem system, the least-effort unit (or least-effort system) is abstracted. Further, problems are induced from the various minimum action units, the problems are input into a problem analysis module S102, problem function elements are matched through the module, semantic features of the elements of the function elements are abstracted and summarized, and the semantic features are used for marking, indexing and retrieving existing knowledge;

in step S204, the problem intention is identified and classified, namely the problem system is matched into the function element;

the problem intention classification is to match a problem system into a function element or a function element combination;

in some embodiments, the matching to the function element is to calculate the similarity between the input question and the combination of the function element and the function element under a certain weighting strategy. The functional element combination may be cluster division of related functional elements according to a cluster, an association rule or a policy.

In step S206, a boolean search formula is generated and edited from the input question. The expansion element is used for performing element semantic expansion on the function element matched with the problem;

the search formula generation is to expand part or all of the constituent elements of the functional elements according to a concept system and then combine the elements to form a Boolean search formula;

in some embodiments, the semantic extensions include concept, instance, and episodic element extensions;

in some embodiments, the semantic extensions further include designing boolean logic rules including, but not limited to, boolean operators, classification of boolean logic;

in some embodiments, search recall, ranking, and filtering are performed in the indexed knowledge using an extended search formula;

fig. 3 shows the effect given by the question analysis module, first inputting the natural query content, and obtaining the functional elements by the intention classification. Such as "how to increase the lift of an aircraft wing? ", will decompose into" functions ": and improving the 'parameter': lift, "object": an airfoil.

In some embodiments, multi-modal content such as text, voice, image, video, etc. is input, such as the third sample in fig. 3, where the "display screen" is an image, as input, and then subsequent function element selection is driven;

in some embodiments, the elements in the functional element may be hierarchical concepts and instances;

in some embodiments, the question intent classification may be obtained automatically by a rule template or a machine learning method.

In some embodiments, knowledge indexing, storage issues have been addressed in advance, facilitating knowledge retrieval and generation for assisting the invention.

FIG. 4 illustrates the workflow of the knowledge mining module:

in step S402, feature selection of knowledge is performed;

in some embodiments, according to the function element condition corresponding to the input question, a suitable feature combination is screened by a feature selection method. Optionally, the feature selection method may be classification, clustering, graph computation, association rule mining, and recommendation algorithm. Such as logistic regression, GBDT, decision trees, random forests, deep neural network models, etc.

The knowledge, including but not limited to patent, scientific literature, TRIZ innovation knowledge;

in step S404, recall ranking is retrieved;

the retrieval recall is to search various knowledge by using an expanded retrieval mode, deform and expand elements, retrieve in the characteristics selected by the knowledge by a text matching method and recall one or combined knowledge;

optionally, the text matching method can select a rule template and an intelligent algorithm model, and match characters or semantemes of the upper concept, the same position and the lower example of the element;

in some embodiments, the retrieving includes matching recalls for indexed results based on a boolean search, also including recommendation algorithm matching recalls;

in some embodiments, the input element-related features are referenced and ranked in combination with a weighting strategy;

in some embodiments, the weight policy includes different weight rule settings of the upper concept, the co-located instance, and the lower instance of the input element;

in some embodiments, the weighting policy further includes configuring weights according to resources, systems, component characteristics related to the problem to be created, and related fields, related users, and selection preference constraints;

optionally, the preference policy includes history, user selection weight, etc.;

in some embodiments, the screening target text recommends one text or a combined text of invention information and reference text from the sorting result according to a weight strategy;

in some embodiments, the filtering recommends knowledge from the ranked results according to a weighting policy;

in step S406, further performing scenario mining;

in the step S406 of project mining, knowledge retrieval, recommendation, generation, question answering, reasoning, matching project recall and improvement can be realized.

The matching is similarity calculation depending on functional elements or functional element combinations, and the calculation method comprises distance calculation, latent semantic model calculation and deep semantic calculation;

in some embodiments, the knowledge includes various items of inventive principles, flow improvement measures, standard solutions, scientific effect information in the TRIZ theory;

in some embodiments, the knowledge further comprises patent text, technical literature, technical reports;

in some embodiments, the mining method includes a grammatical feature, a rule template, or an algorithmic model;

in some embodiments, the recall scheme is ranked and filtered,

in some embodiments, the ordering may select rules, clustering, classification, etc., and iteratively optimize.

FIG. 5 illustrates the workflow of the scenario generation module:

in step S502, trend analysis is performed;

in some embodiments, problem system updates are performed under constraints via TRIZ technology trend rule screening and function element selection.

in step S504, selecting a function element, including selecting a new function element, a similar function element in a different field, or a different function element with a similar effect, or cutting or replacing a part of elements of an existing function element;

in some embodiments, for example, the function element with the problem is a new function element selected from "part-speed regulation", and may be "gear-coupling-rotating speed"

In some embodiments, selecting a different domain similar function element, such as "gear-speed" in the mechanical domain, and "motor-increase-frequency" in the electrical domain, is a similar result from a different domain;

in some embodiments, different function elements with similar effects are selected, such as "gear-speed regulation", if the similar speed regulation effect is to be achieved, "gear-transmission force-increase" and "gear-torque-increase" can be selected, so that the thinking of the selection of the problem function elements can be converted, and the function element replacement and cutting can be realized.

In step S506, the problem system is updated, and the system problem is iteratively solved after the function element is selected.

In some embodiments, the "motor-up-frequency" in the electrical domain may be selected for replacement by a series of function elements, such as "function- (description) attributes" and "function-object" representing and replacing existing problem function elements, such as "gear-speed" in the mechanical domain.

In some embodiments, a subject description sentence is extracted from a target text according to a text rule or a model to generate a text abstract;

in some embodiments, the problem system solution is generated by editing in conjunction with the invention knowledge base. For example, after the gear-speed regulation in the mechanical field is replaced by the motor-increasing-frequency regulation in the electrical field, the gear-speed regulation is cut, added or replaced in the existing problem system according to the technical scheme of the motor-increasing-frequency regulation to form a solution;

optionally, in the solution generating process, reference may be made to comprehensive resource analysis, system analysis, and clipping analysis, or reference may be made to an existing technical solution, such as patent invention content, technical process of scientific and technical literature, and the like.

Also disclosed is an electronic device, fig. 6 shows a block diagram 1500 of the electronic device according to an embodiment of the disclosure, the electronic device 1500 comprising a memory 1510 and a processor 1520;

wherein the memory 1510 is configured to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor 1520 to implement the method steps of the artificial intelligence assisted innovation method of the above-described embodiments.

As shown in the schematic structural diagram of the electronic apparatus shown in fig. 7, the electronic apparatus 1600 includes a Central Processing Unit (CPU)1601 that can execute various processes in the above-described embodiment shown in fig. 1 according to a program stored in a Read Only Memory (ROM)1602 or a program loaded from a storage section 1610 into a Random Access Memory (RAM) 1603. In the RAM1603, various programs and data necessary for the operation of the electronic apparatus 1600 are also stored. The CPU1601, ROM1602, and RAM1603 are connected to each other via a bus 1604. An input/output (I/O) interface 1605 is also connected to the bus 1604.

The following components are connected to the I/O interface 1605: the drive 1606 is connected to the I/O interface 1605 as necessary; removable media 1607 such as magnetic disks, optical disks, magneto-optical disks, semiconductor memories, and the like; an input portion 1608 including a keyboard, a mouse, and the like, installed on the driver 1606 as needed; an output portion 1609 including a display device such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and a speaker; a storage portion 1610 including a hard disk and the like; a computer program for facilitating reading is installed into the storage portion 1610 as necessary; a communication section 1611 of a network interface card such as a LAN card, modem, or the like. The communication section 1611 performs communication processing via a network such as the internet.

As another aspect, the present disclosure also provides a computer-readable storage medium. The computer-readable storage medium may be the computer-readable storage medium included in the apparatus described in the above embodiment; or it may be a separate computer readable storage medium not incorporated into the device. The computer readable storage medium stores one or more programs for use by one or more processors in performing the methods described in the present disclosure.

In particular, according to embodiments of the present disclosure, the method described above with reference to fig. 1 may be implemented as a computer software program. For example, embodiments of the present disclosure include a computer program product comprising a computer program tangibly embodied on a medium readable thereby, the computer program comprising program code for performing the method of fig. 1. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 1611, and/or installed from the removable medium 1607.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowcharts or block diagrams may represent a module, a program segment, or a portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units or modules described in the embodiments of the present disclosure may be implemented by software or hardware. The units or modules described may also be provided in a processor, and the names of the units or modules do not in some cases constitute a limitation of the units or modules themselves.

Thus, a computer-readable medium may take many forms, including but not limited to, a tangible storage medium, a carrier wave medium, or a physical transmission medium. The stable storage medium comprises: optical or magnetic disks, and other computer or similar devices, capable of implementing the system components described in the figures. Volatile storage media include dynamic memory, such as the main memory of a computer platform. Tangible transmission media include coaxial cables, copper cables, and fiber optics, including the wires that form a bus within a computer system. Carrier wave transmission media may convey electrical, electromagnetic, acoustic, or light wave signals, which may be generated by radio frequency or infrared data communication methods. Common computer-readable media include hard disks, floppy disks, magnetic tape, any other magnetic medium; CD-ROM, DVD-ROM, any other optical medium; punch cards, any other physical storage medium containing a pattern of holes; RAM, PROM, EPROM, FLASH-EPROM, any other memory chip or cartridge; a carrier wave transmitting data or instructions, a cable or connection transmitting a carrier wave, any other program code and/or data which can be read by a computer. These computer-readable media may take many forms, and include any type of program code for causing a processor to perform instructions, communicate one or more results, and/or the like.

Computer program code required for the operation of various portions of the present application may be written in any one or more programming languages for execution as a complete software package on a user's computer, as a stand-alone software package on a user's computer, as a partial software package on a remote computer, or as a complete software package on a remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any network, such as a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet), or in a cloud computing environment, or as a service, such as a software as a service (SaaS).

Those skilled in the art will appreciate that various modifications and improvements may be made to the disclosure herein. For example, the different system components described above are implemented by hardware devices, but may also be implemented by software solutions only. For example: the system is installed on an existing server. Further, the location information disclosed herein may be provided via a firmware, firmware/software combination, firmware/hardware combination, or hardware/firmware/software combination.

The foregoing describes the present application and/or some other examples. It is to be understood that the above-described embodiments of the present invention are merely illustrative of or explaining the principles of the invention and are not to be construed as limiting the invention. The subject matter disclosed herein can be implemented in various forms and examples, and the present application can be applied to a wide variety of applications. All applications, modifications and variations that are claimed are within the scope of the application.

Claims

1. The invention is assisted by a device which is characterized by comprising a problem analysis module, a knowledge mining module and a scheme generation module;

the problem analysis module identifies the problem intention by performing functional element analysis on the problem system, and generates a knowledge retrieval formula for assisting the invention.

2. The apparatus of claim 1, wherein the function element comprises a combination unit of a function operation and at least one of an object and a parameter;

the functional operation is an abstracted functional operation concept system;

the object comprises a substance, energy, information concept system and a relation combination;

the parameters are obtained by inducing respective concept systems of refined attributes, attribute parameters, engineering parameters, constraint variables, feature labels and the like.

3. The apparatus of claim 2, wherein the concept hierarchy comprises a hierarchical label of a concept, a concept relationship, a concept instance, an instance relationship, and an item description interpretation text;

the relationship includes the concept of the same position, upper position and lower position, and the similar sense antisense relationship between elements, and also includes the relationship example.

4. The apparatus of claim 1, wherein the identifying the question intent is establishing a matching relationship between the input question and the function element;

the generation of the search formula is to expand the matched functional elements according to respective concept systems of the constituent elements of the functional elements and then combine the functional elements to form the Boolean search formula.

5. The apparatus of claim 1, wherein the knowledge mining module is configured to perform knowledge retrieval, recommendation, generation, question answering, reasoning;

the knowledge includes scientific documents such as patents, treatises, technical reports and the like, and TRIZ related knowledge.

6. The apparatus according to claims 3-4, wherein the matching relies on similarity calculations of functional elements or combinations of functional elements;

and the similarity calculation comprises distance calculation, latent semantic model calculation and deep semantic calculation.

7. The apparatus of claim 1, wherein the scenario generation module performs problem system update by TRIZ technology trend rule filtering and function element selection.

8. The apparatus according to claim 7, wherein the function element selection comprises selecting a new function element, a similar function element in a different field or a different function element with a similar effect, and further comprises cutting and replacing part elements of existing problem function elements;

and the problem system updating is to add the selected functional elements into the problem system for comprehensive analysis and iterative optimization.

9. An inventive electronic device, comprising one or more storage means and a processor, wherein the storage means is adapted to store one or more programs, which when executed by the one or more processors, cause the one or more processors to perform the method of any one of claims 1 to 8 of the inventive device.

10. A computer readable storage medium storing computer instructions, wherein the computer instructions, when read by a computer, perform the method of any one of claims 1 to 9 when the instructions are executed by the computer, the instructions operable to perform any one of the methods.