CN114022292A - Damage assessment rule screening method, device, equipment and medium based on artificial intelligence - Google Patents
Damage assessment rule screening method, device, equipment and medium based on artificial intelligence Download PDFInfo
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Abstract
The invention relates to the technical field of artificial intelligence, and provides a damage assessment rule screening method, device, equipment and medium based on artificial intelligence. The method comprises the following steps: reading an item to be damaged from a database, and matching the item to be damaged with a damage assessment rule to obtain a triggered damage assessment rule set and an un-triggered damage assessment rule set; grading the triggered damage assessment rule and the triggerless damage assessment rule to obtain a grading value; feeding back the sorting result of the score values to the first user, receiving feedback information, selecting a triggered damage assessment rule as a first candidate rule set according to the feedback information, and selecting an un-triggered damage assessment rule as a second candidate rule set; and merging the first candidate rule set and the second candidate rule set to obtain a target damage assessment rule set, storing the target damage assessment rule set into a damage assessment rule engine and feeding back the target damage assessment rule set to a preset user. The invention also relates to the technical field of block chains, and the scoring value and the target damage assessment rule set can be stored in a node of a block chain.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to a loss assessment rule screening method, device, equipment and medium based on artificial intelligence.
Background
In the process of claim settlement and damage assessment operation, a damage assessment rule engine provides templates such as fields, factors, rules, scenes, authority groups and the like, enterprises can define various rules of different business scenes through the templates according to development requirements of the enterprises, and the enterprises also store a large number of damage assessment rules in the damage assessment rule engine in the process of long-term development.
Because the business scene is continuously developed and changed, the execution effect of some damage-assessment rules in the actual scene is increasingly poor, the hit matching rate is also increasingly low, managers of enterprises are difficult to judge and manage which damage-assessment rules have practicability and effectiveness, the damage-reduction effect in the damage-assessment operation process is reduced, and accordingly the policy and claim cost is increased.
Disclosure of Invention
In view of the above, the present invention provides a method, an apparatus, a device and a medium for selecting a damage assessment rule based on artificial intelligence, and aims to solve the technical problems in the prior art that the hit matching rate of the rule is lower and the computation load of the CPU is higher.
In order to achieve the purpose, the invention provides a damage assessment rule screening method based on artificial intelligence, which comprises the following steps:
reading an item to be damaged from a preset database, and matching the item to be damaged with a damage assessment rule in a preset damage assessment rule engine to obtain a triggered damage assessment rule set and an un-triggered damage assessment rule set of the item to be damaged; the triggered damage assessment rule set comprises at least one triggered damage assessment rule, and the triggerless damage assessment rule set comprises at least one triggerless damage assessment rule;
scoring the triggered damage assessment rule based on a preset first calculation rule, and scoring the non-triggered damage assessment rule based on a preset second calculation rule to obtain score values of the triggered damage assessment rule and the non-triggered damage assessment rule;
feeding back the triggered damage assessment rules and the triggerless damage assessment rules to a first user based on the ranking result of the score value, receiving feedback information sent by the first user based on the ranking result, selecting a first preset number of triggered damage assessment rules as a first candidate rule set according to the feedback information, and selecting a second preset number of triggerless damage assessment rules as a second candidate rule set;
and executing union operation on the first candidate rule set and the second candidate rule set to obtain a target damage assessment rule set, storing the target damage assessment rule set into the damage assessment rule engine, and feeding back all damage assessment rules of the target damage assessment rule set to a preset user.
Preferably, the matching the to-be-damaged item with a damage rule in a preset damage rule engine includes:
a1, reading any one accessory in the to-be-damaged item to be matched with the damage assessment rule in the damage assessment rule engine, and obtaining the damage assessment result of the accessory when the attribute information of the accessory is successfully matched with all sub-rules in the damage assessment rule;
a2, when the attribute information of the accessory fails to be matched with any sub-rule in the loss assessment rule, feeding back prompt information to a preset user according to the sub-rule with failed matching, receiving modification information sent by the preset user according to the prompt information, and when the modification information is successfully matched with the sub-rule in the loss assessment rule, obtaining a loss assessment result of the accessory.
A3, repeating A1-A2 until each accessory in the project to be damaged is matched with the damage rule in the damage rule engine to obtain a damage result.
Preferably, the obtaining a triggered impairment rule set and an triggerless impairment rule set of the to-be-impaired item includes:
when any one accessory in the to-be-determined item is successfully matched with a loss assessment rule in the loss assessment rule engine, reading the loss assessment rule of the loss assessment result which is successfully matched from the loss assessment rule engine to serve as the triggered loss assessment rule set;
and when any one accessory in the to-be-damaged item fails to be matched with the damage assessment rule in the damage assessment rule engine, reading the damage assessment rule which fails to be matched from the damage assessment rule engine to serve as the triggerless damage assessment rule set.
Preferably, the formula of the first calculation rule includes:
wherein, PiIs the score value, X, of the ith triggered damage rating ruleiNumber of tasks detected for ith triggered damage-assessment rule, YiAnd a is a score coefficient, which is the number of tasks of the ith triggered damage assessment rule.
Preferably, the formula of the second calculation rule includes:
Ni＝(T1-T2)×W×a
Niis the score value, T, of the ith un-triggered damage-assessment rule1For the creation time point of the ith triggerless damage-assessment rule, T2At the current time point, W is the rule weight, and a is the score coefficient.
Preferably, the receiving feedback information sent by the first user based on the sorting result includes:
and sorting the triggered damage assessment rule and the triggerless damage assessment rule from high to low based on the score value to obtain a sorting result, and taking the information selected from the sorting result by the first user as the feedback information.
Preferably, the feeding back all the damage assessment rules of the target damage assessment rule set to a preset user includes:
reading the weight value of each loss assessment rule in the target loss assessment rule set in the loss assessment rule engine, and multiplying the weight value by a preset coefficient to obtain a target weight value;
and sequencing each damage assessment rule in the target damage assessment rule set from high to low according to the target weight value, and setting the feedback times and time periods of each damage assessment rule fed back to the preset user according to the sequencing result.
In order to achieve the above object, the present invention further provides a damage assessment rule screening apparatus, including:
an acquisition module: the method comprises the steps that a project to be damaged is read from a preset database, and the project to be damaged is matched with a damage assessment rule in a preset damage assessment rule engine to obtain a triggered damage assessment rule set and an un-triggered damage assessment rule set of the project to be damaged; the triggered damage assessment rule set comprises at least one triggered damage assessment rule, and the triggerless damage assessment rule set comprises at least one triggerless damage assessment rule;
a calculation module: the system comprises a trigger damage assessment rule, a trigger damage assessment rule and a non-trigger damage assessment rule, wherein the trigger damage assessment rule is used for scoring based on a preset first calculation rule, and the non-trigger damage assessment rule is scored based on a preset second calculation rule to obtain scoring values of the trigger damage assessment rule and the non-trigger damage assessment rule;
a selecting module: the system comprises a first user, a second user and a third user, wherein the first user is used for sending a ranking result of the triggered damage assessment rules and the triggerless damage assessment rules based on the score value to the second user, receiving feedback information sent by the first user based on the ranking result, selecting a first preset number of triggered damage assessment rules as a first candidate rule set according to the feedback information, and selecting a second preset number of triggerless damage assessment rules as a second candidate rule set;
a recommendation module: the system comprises a first candidate rule set, a second candidate rule set and a damage assessment rule engine, wherein the first candidate rule set and the second candidate rule set are used for executing union set operation to obtain a target damage assessment rule set, the target damage assessment rule set is stored in the damage assessment rule engine, and all damage assessment rules of the target damage assessment rule set are fed back to a preset user.
In order to achieve the above object, the present invention also provides an electronic device, including:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores a program executable by the at least one processor to enable the at least one processor to perform the artificial intelligence based impairment rule screening method of any one of claims 1 to 7.
To achieve the above object, the present invention further provides a computer readable medium storing a damage rule filtering program, which when executed by a processor, implements the steps of the artificial intelligence based damage rule filtering method according to any one of claims 1 to 7.
The triggered damage assessment rule and the triggerless damage assessment rule are obtained from a damage assessment rule engine, the triggered damage assessment rule and the triggerless damage assessment rule are graded to obtain score values, the triggered damage assessment rule and the triggerless damage assessment rule are fed back to a first user based on the ranking results of the score values, feedback information sent by the first user based on the ranking results is received, a preset number of triggered damage assessment rules and triggerless damage assessment rules are selected as a target damage assessment rule set according to the feedback information, the target damage assessment rule set is stored in the damage assessment rule engine, and each damage assessment rule in the target damage assessment rule set is fed back to the preset user. The method and the device can screen out the loss assessment rule with practicability and effectiveness, feed the loss assessment rule with practicability and effectiveness back to all preset users, improve the hit matching rate of the rule and reduce the operation load of the CPU.
Drawings
FIG. 1 is a schematic flow chart diagram illustrating a preferred embodiment of the damage assessment rule screening method based on artificial intelligence of the present invention;
FIG. 2 is a block diagram of a loss assessment rule screening apparatus according to a preferred embodiment of the present invention;
FIG. 3 is a diagram of an electronic device according to a preferred embodiment of the present invention;
the implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the invention can acquire and process related data based on an artificial intelligence technology. Among them, Artificial Intelligence (AI) is a theory, method, technique and application system that simulates, extends and expands human Intelligence using a digital computer or a machine controlled by a digital computer, senses the environment, acquires knowledge and uses the knowledge to obtain the best result.
The artificial intelligence infrastructure generally includes technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a robot technology, a biological recognition technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and the like.
The invention provides a damage assessment rule screening method based on artificial intelligence. Referring to fig. 1, a schematic method flow chart of an embodiment of the damage assessment rule screening method based on artificial intelligence is shown. The method may be performed by an electronic device, which may be implemented by software and/or hardware. The damage assessment rule screening method based on artificial intelligence comprises the following steps:
step S10: reading an item to be damaged from a preset database, and matching the item to be damaged with a damage assessment rule in a preset damage assessment rule engine to obtain a triggered damage assessment rule set and an un-triggered damage assessment rule set of the item to be damaged; wherein the triggered damage assessment rule set comprises at least one triggered damage assessment rule, and the triggerless damage assessment rule set comprises at least one triggerless damage assessment rule.
In this embodiment, the preset database may refer to a self-built database inside an enterprise (e.g., an insurance damage database of an insurance company). And taking the staff who carries out the loss assessment task, the quotation task and the guidance task in each business scene as a preset user. And taking data of the loss assessment task, the quotation task and the guidance task which are input into a preset database by a preset user (staff) as items to be lost (for example, the input data comprise basic information of vehicles, information of repair shops, information of accessories, information of money amount and the like).
The enterprise accumulates a large amount of loss assessment rules in each past service scene (for example, loss assessment rules of different types of automobiles configured on the service, loss assessment rules of different suppliers of the same type of accessories with different prices, and the like), and the preset loss assessment rule engine can apply a calculation system of the rules according to an expression language engine framework of apache jexl, and store the loss assessment rules accumulated by the enterprise into the preset loss assessment rule engine. When the accessory in the project to be damaged is successfully matched with the damage assessment rule in the damage assessment rule engine, a damage assessment result of the accessory is obtained and fed back to the preset user, the preset user makes an assessment report according to the damage assessment result and sends the assessment report to a first user of an enterprise, and a worker who has tasks to be allocated, manages the preset user and has examination and approval authority on the assessment report in the enterprise is used as the first user.
In one embodiment, the matching the to-be-damaged item with a damage rule in a preset damage rule engine includes:
a1, reading any one accessory in the to-be-damaged item to be matched with the damage assessment rule in the damage assessment rule engine, and obtaining the damage assessment result of the accessory when the attribute information of the accessory is successfully matched with all sub-rules in the damage assessment rule;
a2, when the attribute information of the accessory fails to be matched with any sub-rule in the loss assessment rule, feeding back prompt information to a preset user according to the sub-rule with failed matching, receiving modification information sent by the preset user according to the prompt information, and when the modification information is successfully matched with the sub-rule in the loss assessment rule, obtaining a loss assessment result of the accessory.
A3, repeating A1-A2 until each accessory in the project to be damaged is matched with the damage rule in the damage rule engine to obtain a damage result.
The attribute information of the accessory includes the name, model, parameter, price, model, level, installation cost, etc. of the accessory, for example, when each attribute information of the accessory a is successfully matched with all sub-rules in the loss assessment rule E, the loss assessment result of the accessory a is obtained, all sub-rules in the loss assessment rule E are in one-to-one correspondence with the attribute information of the accessory a, the sub-rules respectively include multiple sub-rules of the name, model, parameter, price, model, level, installation cost, etc. of the accessory, and the loss assessment result of the accessory a can be obtained only when each attribute information of the accessory a is successfully matched with each sub-rule in the loss assessment rule E.
If a certain sub-rule in the damage-assessment rule E fails to be matched with certain attribute information of the accessory A, for example, the damage-assessment rule E is a damage-assessment rule of the accessory A, the matching of other attribute information and the corresponding sub-rule except for the matching failure of the price (attribute information) and the price sub-rule is successful, if the price of the accessory A is 400 yuan, the price of the sub-rule in the damage-assessment rule E is 350 yuan, because the price of the accessory A is higher than that of the damage-assessment rule E, the matching of the price sub-rule of the damage-assessment rule E and the price attribute information of the accessory A fails, the damage-assessment rule engine feeds back prompt information to a preset user (for example, you are good, the price of the submitted accessory A does not meet the condition, please modify), the preset user modifies the price of the accessory A according to the prompt information and submits the price sub-rule to the damage-assessment rule engine for matching until the price of the accessory A and the price sub-assessment rule in the damage-assessment rule E are successfully matched, the damage assessment results for fitting a were obtained. In addition, after the preset user modifies the price of the accessory A for multiple times, when the matching with the price sub-rule in the damage assessment rule E fails, the accessory A can also be selected to be matched with other rules, and the matching of the accessory A and the damage assessment rule E is abandoned. In an actual business scene, a plurality of accessories to be damaged and claim may be related to each project to be damaged, sometimes one accessory will be matched with more than one successful damage rule or a plurality of accessories will be matched with one successful damage rule at the same time.
In one embodiment, the obtaining a triggered impairment rule set and an triggerless impairment rule set of the pending impairment item includes:
when any one accessory in the to-be-determined item is successfully matched with a loss assessment rule in the loss assessment rule engine, reading the loss assessment rule of the loss assessment result which is successfully matched from the loss assessment rule engine to serve as the triggered loss assessment rule set;
and when any one accessory in the to-be-damaged item fails to be matched with the damage assessment rule in the damage assessment rule engine, reading the damage assessment rule which fails to be matched from the damage assessment rule engine to serve as the triggerless damage assessment rule set.
Judging whether the to-be-damaged item is successfully matched with the damage assessment rule in the damage assessment rule engine or not, and if yes, judging that each piece of attribute information of any one accessory in the to-be-damaged item is successfully matched with each sub-rule in the damage assessment rule engine to obtain a damage assessment result, wherein the rule is a triggered damage assessment rule of the to-be-damaged item; and when the attribute information of any accessory in the item to be damaged is judged to fail to be matched with any sub-rule in the damage assessment rule engine, the rule is the damage assessment rule which is not triggered by the item to be damaged.
According to the method and the device, the preset user is guided to continuously modify the attribute information of the accessory according to the prompt information of failure in matching of the accessory and the sub-rules in the loss assessment rule engine, and the leakage risk of claim settlement is effectively reduced.
Step S20: the system comprises a trigger damage assessment rule, a trigger damage assessment rule and a non-trigger damage assessment rule, wherein the trigger damage assessment rule is used for scoring based on a preset first calculation rule, and the non-trigger damage assessment rule is scored based on a preset second calculation rule to obtain scoring values of the trigger damage assessment rule and the non-trigger damage assessment rule;
in this embodiment, the relevance ratio of the triggered damage assessment rule is counted from the damage assessment rule engine, and the relevance ratio is multiplied by a score coefficient to perform a first calculation rule scoring on the triggered damage assessment rule, so as to obtain a score value of the triggered damage assessment rule. If two accessories A, B are simultaneously input and matched with all the damage assessment rules, the corresponding damage assessment rule E of the accessory A is obtained, the corresponding damage assessment rule F, G of the accessory B is obtained, in the process of matching each attribute information of the accessories, the fact that the accessory B does not accord with the damage assessment rule G and cannot be matched is prompted, the damage assessment result is obtained, after the attribute information of the accessory B is modified for multiple times, the accessory B cannot be matched to obtain the damage assessment result, the accessory B is removed, only the accessory A can be obtained, the damage assessment result accords with the damage assessment operation, and the fact that the accessory B has a detection rate (detection task) on the damage assessment rule F, G is considered. The score coefficient refers to a section coefficient of a corresponding calculation rule, which is used for conversion of the detection rate (for example, a score section of 0-100 is defined, and if the corresponding detection rate range is 0-80, the score coefficient is 80 divided by 100 and equals to 0.8).
And (4) counting the creation time length of the non-triggered damage rule from the damage rule engine, and respectively multiplying the creation time length by a score coefficient and the weight of the damage rule in the damage rule engine to carry out second calculation rule scoring to obtain the score value of the non-triggered damage rule. The time period from the creation time point of the damage rule to the current time point is read, and the time period is taken as the creation time period of the damage rule (for example, the creation time point of the damage rule G is 10:00AM at 8 months and 1 day at 2021 year, 8 months and 11 days at 10:00AM at 2021 year, and the creation time period of the damage rule G is 10 days). The rule weight is a priority that defines each of the impairment rules according to the importance of the rule (e.g., priorities a-F from high to low, their corresponding rule weight values range from 10 "1).
In one embodiment, the formula of the first calculation rule includes:
wherein, PiIs the score value, X, of the ith triggered damage rating ruleiNumber of tasks detected for ith triggered damage-assessment rule, YiAnd a is a score coefficient, which is the number of tasks of the ith triggered damage assessment rule.
The task quantity refers to the quantity of loss assessment tasks, quotation tasks and guidance tasks of the preset user in the operation. And counting the detection rate of the triggered damage assessment rule, wherein the higher the detection rate is, the higher the effectiveness of the triggered damage assessment rule is, the important role is played in risk control of fraud, leakage and the like in the damage assessment and claim process, and if the higher the score value obtained by triggering the damage assessment rule is, the better the damage assessment effect of the triggered damage assessment rule is represented.
For example, in a preset time period (for example, within 7 days), the number of detected tasks of the damage assessment rule E is 10, the number of tasks that have triggered the damage assessment rule is 100, the score coefficient is 0.8, and data is input into the first calculation rule to obtain the score value of the damage assessment rule E of 0.08.
In one embodiment, the formula of the second calculation rule includes:
Ni＝(T1-T2)×W×a
Niis the score value, T, of the ith un-triggered damage-assessment rule1For the creation time point of the ith triggerless damage-assessment rule, T2At the current time point, W is the rule weight, and a is the score coefficient.
The higher the score value obtained by the non-triggered damage assessment rule is, the worse the damage assessment effect of the non-triggered damage assessment rule is, in addition, the creation time of the non-triggered damage assessment rule exceeds a preset value (for example, the preset value is 180 days), a damage assessment result is obtained from the condition that the non-triggered damage assessment rule is not successfully matched with any damage assessment item, the non-triggered damage assessment rule is automatically cleared from a preset damage assessment rule engine, a large number of non-business-requirement or invalid damage assessment rules are prevented from occupying the storage space of the damage assessment rule engine, and the operation load of a CPU is reduced.
For example, the creation time point of the damage-assessment rule G is 10:00AM at 8/month 1/day 2021, the current time is 10:00AM at 8/month 11/month 2021, the corresponding rule weight value is 2, the score coefficient is 0.8, and the data is input into the second calculation rule to obtain the score value of the damage-assessment rule G, which is-16.
Step S30: feeding back the triggered damage assessment rules and the triggerless damage assessment rules to a first user based on the ranking result of the score value, receiving feedback information sent by the first user based on the ranking result, selecting a first preset number of triggered damage assessment rules as a first candidate rule set according to the feedback information, and selecting a second preset number of triggerless damage assessment rules as a second candidate rule set;
in this embodiment, the first calculation rule performs scoring to obtain that the score value of the triggered damage assessment rule is a positive number, the second calculation rule performs scoring to obtain that the score value of the non-triggered damage assessment rule is a negative number, the ranking results of the score values are fed back to the first user, after the first user receives the ranking results, the first user selects some damage assessment rules with high score or high detection rate from the ranking results of the positive number as a first candidate rule set on an operation interface based on the work experience of the first user or the requirement of service development, and selects some damage assessment rules with shorter creation time and larger weight values from the ranking results of the negative number as a second candidate rule set.
In one embodiment, the receiving feedback information sent by the first user based on the sorting result includes:
and sorting the triggered damage assessment rule and the triggerless damage assessment rule from high to low based on the score value to obtain a sorting result, and taking the information selected from the sorting result by the first user as the feedback information.
The selected information refers to which rules the first user selects according to the work experience or the business development requirement of the first user, selecting a preset first preset number of damage rules with high scoring values (for example, the first preset number can be 5000) from the triggered damage rules according to the sorting result, and using the selected first preset number as a first candidate rule set, selecting a second preset number of damage-assessment rules with low score values (for example, the second preset number may be 1000) from the triggerless damage-assessment rules according to the sorting result, and using the selected second preset number as a second candidate rule set, wherein the ratio of the number of triggered damage-assessment rules to the number of triggerless damage-assessment rules is generally kept at 10:2 or 10:1, if the ratio of the number of triggerless damage-assessment rules is too large, the execution effect of the damage assessment rule is greatly influenced, and meanwhile, certain un-triggered damage assessment rules with short creation time or large weight values have enough opportunity to match with the damage assessment items to obtain damage assessment results.
Step S40: and executing union operation on the first candidate rule set and the second candidate rule set to obtain a target damage assessment rule set, storing the target damage assessment rule set into the damage assessment rule engine, and feeding back all damage assessment rules of the target damage assessment rule set to a preset user.
In this embodiment, all the loss rules in the first candidate rule set and the second candidate rule set are merged to obtain a target loss rule set (for example, the first candidate rule set has 5000 rules, the second candidate rule set has 1000 rules, and the two rules are merged and added to obtain 6000 rules, and then the 6000 rules are used as the target loss rule set), the weight values of all the loss rules in the target loss rule set in the loss rule engine are multiplied by a preset coefficient (for example, the preset coefficient is 1.2 or 1.5 times), all the loss rules in the target loss rule set are fed back to a preset user by using a feedback mechanism in the loss rule engine, and the feedback mechanism gives more feedback times to the loss rules according to the larger weight values of the loss rules, and a display period. The feedback mechanism feeds any one damage rule in the target damage rule set back to an operation interface of a preset user, the preset user is helped to directly click the damage rule to match with a project to be damaged in an actual service scene, the preset user can conveniently and quickly find out the efficient damage rule, the preset user can be helped to save service time, and therefore working efficiency of the preset user is improved.
In one embodiment, the feeding back all the damage assessment rules of the target damage assessment rule set to a preset user includes:
reading the weight value of each loss assessment rule in the target loss assessment rule set in the loss assessment rule engine, and multiplying the weight value by a preset coefficient to obtain a target weight value;
and sequencing each damage assessment rule in the target damage assessment rule set from high to low according to the target weight value, and setting the feedback times and time periods of each damage assessment rule fed back to the preset user according to the sequencing result.
The specific weight value is multiplied by a preset coefficient to operate according to the actual service scenario (for example, the weight value of each loss rule in the target loss rule set is multiplied by a coefficient of 1.2 or 1.5 times to obtain a target weight value, so that more feedback times and a better display time period are obtained in the feedback mechanism), for example, in a preset time period (within 7 days), the target weight value of the loss rule E in the target loss rule set is 8, the corresponding feedback times are 30 times, and the feedback time period is 10: 00-12:00AM with 14: 00-16:00PM, wherein the target weight value of a loss assessment rule G in the target loss assessment rule set is 3, the corresponding feedback times are 10, and the feedback time period is 14: 00-16:00PM, and giving different display opportunities to each damage assessment rule in the target damage assessment rule set according to a feedback mechanism.
Referring to fig. 2, a functional block diagram of the damage assessment rule screening apparatus 100 according to the present invention is shown.
The damage assessment rule screening apparatus 100 according to the present invention may be installed in an electronic device. According to the implemented functions, the damage assessment rule screening apparatus 100 may include an obtaining module 110, a calculating module 120, a selecting module 130, and a recommending module 140. A module according to the present invention, which may also be referred to as a unit, refers to a series of computer program segments that can be executed by a processor of an electronic device and that can perform a fixed function, and that are stored in a memory of the electronic device.
In this embodiment, the functions of the modules/units are as follows:
the obtaining module 110 is configured to read an item to be damaged from a preset database, and match the item to be damaged with a damage assessment rule in a preset damage assessment rule engine to obtain a triggered damage assessment rule set and an un-triggered damage assessment rule set of the item to be damaged; wherein the triggered damage assessment rule set comprises at least one triggered damage assessment rule, and the triggerless damage assessment rule set comprises at least one triggerless damage assessment rule.
The calculating module 120 is configured to score the triggered damage assessment rule based on a preset first calculating rule, and score the trigged damage assessment rule based on a preset second calculating rule, so as to obtain score values of the triggered damage assessment rule and the trigged damage assessment rule.
The selecting module 130: the system comprises a first user, a second user and a third user, wherein the first user is used for sending a ranking result of the triggered damage assessment rules and the triggerless damage assessment rules based on the score value to the third user, receiving feedback information sent by the third user based on the ranking result, selecting a first preset number of triggered damage assessment rules as a first candidate rule set according to the feedback information, and selecting a second preset number of triggerless damage assessment rules as a second candidate rule set.
And the recommending module 140 is configured to perform union operation on the first candidate rule set and the second candidate rule set to obtain a target damage assessment rule set, store the target damage assessment rule set in the damage assessment rule engine, and feed back all damage assessment rules of the target damage assessment rule set to a preset user.
In one embodiment, the matching the to-be-damaged item with a damage rule in a preset damage rule engine includes:
a1, reading any one accessory in the to-be-damaged item to be matched with the damage assessment rule in the damage assessment rule engine, and obtaining the damage assessment result of the accessory when the attribute information of the accessory is successfully matched with all sub-rules in the damage assessment rule;
a2, when the attribute information of the accessory fails to be matched with any sub-rule in the loss assessment rule, feeding back prompt information to a preset user according to the sub-rule with failed matching, receiving modification information sent by the preset user according to the prompt information, and when the modification information is successfully matched with the sub-rule in the loss assessment rule, obtaining a loss assessment result of the accessory.
A3, repeating A1-A2 until each accessory in the project to be damaged is matched with the damage rule in the damage rule engine to obtain a damage result.
In one embodiment, the obtaining a triggered impairment rule set and an triggerless impairment rule set of the pending impairment item includes:
when any one accessory in the to-be-determined item is successfully matched with a loss assessment rule in the loss assessment rule engine, reading the loss assessment rule of the loss assessment result which is successfully matched from the loss assessment rule engine to serve as the triggered loss assessment rule set;
and when any one accessory in the to-be-damaged item fails to be matched with the damage assessment rule in the damage assessment rule engine, reading the damage assessment rule which fails to be matched from the damage assessment rule engine to serve as the triggerless damage assessment rule set.
In one embodiment, the formula of the first calculation rule includes:
wherein, PiIs the score value, X, of the ith triggered damage rating ruleiNumber of tasks detected for ith triggered damage-assessment rule, YiAnd a is a score coefficient, which is the number of tasks of the ith triggered damage assessment rule.
In one embodiment, the formula of the second calculation rule includes:
Ni＝(T1-T2)×W×a
Niis the score value, T, of the ith un-triggered damage-assessment rule1For the creation time point of the ith triggerless damage-assessment rule, T2At the current time point, W is the rule weight, and a is the score coefficient.
In one embodiment, the receiving feedback information sent by the first user based on the sorting result includes:
and sorting the triggered damage assessment rule and the triggerless damage assessment rule from high to low based on the score value to obtain a sorting result, and taking the information selected from the sorting result by the first user as the feedback information.
In one embodiment, the feeding back all the damage assessment rules of the target damage assessment rule set to a preset user includes:
reading the weight value of each loss assessment rule in the target loss assessment rule set in the loss assessment rule engine, and multiplying the weight value by a preset coefficient to obtain a target weight value;
and sequencing each damage assessment rule in the target damage assessment rule set from high to low according to the target weight value, and setting the feedback times and time periods of each damage assessment rule fed back to the preset user according to the sequencing result.
Fig. 3 is a schematic diagram of an electronic device 1 according to a preferred embodiment of the invention.
The electronic device 1 includes but is not limited to: memory 11, processor 12, display 13, and network interface 14. The electronic device 1 is connected to a network through a network interface 14 to obtain raw data. The network may be a wireless or wired network such as an Intranet (Intranet), the Internet (Internet), a Global System for Mobile communications (GSM), Wideband Code Division Multiple Access (WCDMA), a 4G network, a 5G network, Bluetooth (Bluetooth), Wi-Fi, or a communication network.
The memory 11 includes at least one type of readable medium including a flash memory, a hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a Programmable Read Only Memory (PROM), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the storage 11 may be an internal storage unit of the electronic device 1, such as a hard disk or a memory of the electronic device 1. In other embodiments, the memory 11 may also be an external storage device of the electronic device 1, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like equipped with the electronic device 1. Of course, the memory 11 may also comprise both an internal memory unit and an external memory device of the electronic device 1. In this embodiment, the memory 11 is generally used for storing an operating system installed in the electronic device 1 and various types of application software, such as program codes of the rule filter 10. Further, the memory 11 may also be used to temporarily store various types of data that have been output or are to be output.
Processor 12 may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor, or other data Processing chip in some embodiments. The processor 12 is typically used for controlling the overall operation of the electronic device 1, such as performing data interaction or communication related control and processing. In this embodiment, the processor 12 is configured to run the program code stored in the memory 11 or process data, such as the program code of the rule filter 10.
The display 13 may be referred to as a display screen or display unit. In some embodiments, the display 13 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an Organic Light-Emitting Diode (OLED) touch screen, or the like. The display 13 is used for displaying information processed in the electronic device 1 and for displaying a visual work interface, e.g. displaying the results of data statistics.
The network interface 14 may optionally comprise a standard wired interface, a wireless interface (e.g. WI-FI interface), the network interface 14 typically being used for establishing a communication connection between the electronic device 1 and other electronic devices.
Fig. 3 only shows the electronic device 1 with the components 11-14 and the rule filter 10, but it should be understood that not all of the shown components are required to be implemented, and that more or fewer components may be implemented instead.
Optionally, the electronic device 1 may further comprise a user interface, the user interface may comprise a Display (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface may further comprise a standard wired interface and a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an Organic Light-Emitting Diode (OLED) touch screen, or the like. The display, which may also be referred to as a display screen or display unit, is suitable for displaying information processed in the electronic device 1 and for displaying a visualized user interface, among other things.
The electronic device 1 may further include a Radio Frequency (RF) circuit, a sensor, an audio circuit, and the like, which are not described in detail herein.
In the above embodiment, the processor 12 may implement the following steps when executing the damage assessment rule filtering program 10 stored in the memory 11:
reading an item to be damaged from a preset database, and matching the item to be damaged with a damage assessment rule in a preset damage assessment rule engine to obtain a triggered damage assessment rule set and an un-triggered damage assessment rule set of the item to be damaged; the triggered damage assessment rule set comprises at least one triggered damage assessment rule, and the triggerless damage assessment rule set comprises at least one triggerless damage assessment rule;
scoring the triggered damage assessment rule based on a preset first calculation rule, and scoring the non-triggered damage assessment rule based on a preset second calculation rule to obtain score values of the triggered damage assessment rule and the non-triggered damage assessment rule;
feeding back the triggered damage assessment rules and the triggerless damage assessment rules to a first user based on the ranking result of the score value, receiving feedback information sent by the first user based on the ranking result, selecting a first preset number of triggered damage assessment rules as a first candidate rule set according to the feedback information, and selecting a second preset number of triggerless damage assessment rules as a second candidate rule set;
and executing union operation on the first candidate rule set and the second candidate rule set to obtain a target damage assessment rule set, storing the target damage assessment rule set into the damage assessment rule engine, and feeding back all damage assessment rules of the target damage assessment rule set to a preset user.
The storage device may be the memory 11 of the electronic device 1, or may be another storage device communicatively connected to the electronic device 1.
For the detailed description of the above steps, please refer to the above description of fig. 2 regarding the functional block diagram of the embodiment of the damage-assessment rule screening apparatus 100 and fig. 1 regarding the flowchart of the embodiment of the artificial intelligence-based damage-assessment rule screening method.
In addition, the embodiment of the present invention further provides a computer-readable medium, which may be non-volatile or volatile. The computer readable medium may be any one or any combination of hard disk, multimedia card, SD card, flash memory card, SMC, Read Only Memory (ROM), Erasable Programmable Read Only Memory (EPROM), portable compact disc read only memory (CD-ROM), USB memory, and the like. The computer readable medium includes a storage data area and a storage program area, the storage data area stores data created according to the use of the blockchain node, the storage program area stores a damage-assessment rule screening program 10, and when executed by a processor, the rule screening program 10 implements the following operations:
reading an item to be damaged from a preset database, and matching the item to be damaged with a damage assessment rule in a preset damage assessment rule engine to obtain a triggered damage assessment rule set and an un-triggered damage assessment rule set of the item to be damaged; the triggered damage assessment rule set comprises at least one triggered damage assessment rule, and the triggerless damage assessment rule set comprises at least one triggerless damage assessment rule;
scoring the triggered damage assessment rule based on a preset first calculation rule, and scoring the non-triggered damage assessment rule based on a preset second calculation rule to obtain score values of the triggered damage assessment rule and the non-triggered damage assessment rule;
feeding back the triggered damage assessment rules and the triggerless damage assessment rules to a first user based on the ranking result of the score value, receiving feedback information sent by the first user based on the ranking result, selecting a first preset number of triggered damage assessment rules as a first candidate rule set according to the feedback information, and selecting a second preset number of triggerless damage assessment rules as a second candidate rule set;
and executing union operation on the first candidate rule set and the second candidate rule set to obtain a target damage assessment rule set, storing the target damage assessment rule set into the damage assessment rule engine, and feeding back all damage assessment rules of the target damage assessment rule set to a preset user.
The specific implementation of the computer readable medium of the present invention is substantially the same as the above-mentioned specific implementation of the damage assessment rule screening method based on artificial intelligence, and will not be described herein again.
In another embodiment, in order to further ensure the privacy and security of all the occurring data, all the data may be stored in a node of a block chain. Such as the score value, the target damage-scoring rule set, and all of these data may be stored in the block link points.
It should be noted that the blockchain in the present invention is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanism, and encryption algorithm. A block chain (Blockchain), which is essentially a decentralized database, is a series of data blocks associated by using a cryptographic method, and each data block contains information of a batch of network transactions, so as to verify the validity (anti-counterfeiting) of the information and generate a next block. The blockchain may include a blockchain underlying platform, a platform product service layer, an application service layer, and the like.
It should be noted that the above-mentioned numbers of the embodiments of the present invention are merely for description, and do not represent the merits of the embodiments. And the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, apparatus, article, or method. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, apparatus, article, or method that includes the element.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention essentially or contributing to the prior art can be embodied in the form of a software product, which is stored in a medium (such as ROM/RAM, magnetic disk, optical disk) as described above and includes instructions for enabling a terminal device (such as a mobile phone, a computer, an electronic device, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A damage assessment rule screening method based on artificial intelligence is characterized by comprising the following steps:
reading an item to be damaged from a preset database, and matching the item to be damaged with a damage assessment rule in a preset damage assessment rule engine to obtain a triggered damage assessment rule set and an un-triggered damage assessment rule set of the item to be damaged; the triggered damage assessment rule set comprises at least one triggered damage assessment rule, and the triggerless damage assessment rule set comprises at least one triggerless damage assessment rule;
scoring the triggered damage assessment rule based on a preset first calculation rule, and scoring the non-triggered damage assessment rule based on a preset second calculation rule to obtain score values of the triggered damage assessment rule and the non-triggered damage assessment rule;
feeding back the triggered damage assessment rules and the triggerless damage assessment rules to a first user based on the ranking result of the score value, receiving feedback information sent by the first user based on the ranking result, selecting a first preset number of triggered damage assessment rules as a first candidate rule set according to the feedback information, and selecting a second preset number of triggerless damage assessment rules as a second candidate rule set;
and executing union operation on the first candidate rule set and the second candidate rule set to obtain a target damage assessment rule set, storing the target damage assessment rule set into the damage assessment rule engine, and feeding back all damage assessment rules of the target damage assessment rule set to a preset user.
2. The artificial intelligence based impairment rule screening method of claim 1, wherein the matching the item to be impaired with the impairment rule in a preset impairment rule engine comprises:
a1, reading any one accessory in the to-be-damaged item to be matched with the damage assessment rule in the damage assessment rule engine, and obtaining the damage assessment result of the accessory when the attribute information of the accessory is successfully matched with all sub-rules in the damage assessment rule;
a2, when the attribute information of the accessory fails to be matched with any sub-rule in the loss assessment rule, feeding back prompt information to a preset user according to the sub-rule with failed matching, receiving modification information sent by the preset user according to the prompt information, and when the modification information is successfully matched with the sub-rule in the loss assessment rule, obtaining a loss assessment result of the accessory.
A3, repeating A1-A2 until each accessory in the project to be damaged is matched with the damage rule in the damage rule engine to obtain a damage result.
3. The artificial intelligence based impairment rule screening method of claim 1, wherein the obtaining of the triggered impairment rule set and the triggerless impairment rule set of the to-be-impaired item comprises:
when any one accessory in the to-be-determined item is successfully matched with a loss assessment rule in the loss assessment rule engine, reading the loss assessment rule of the loss assessment result which is successfully matched from the loss assessment rule engine to serve as the triggered loss assessment rule set;
and when any one accessory in the to-be-damaged item fails to be matched with the damage assessment rule in the damage assessment rule engine, reading the damage assessment rule which fails to be matched from the damage assessment rule engine to serve as the triggerless damage assessment rule set.
4. The artificial intelligence based impairment rule screening method of claim 1, wherein the formula of the first calculation rule comprises:
wherein, PiIs the score value, X, of the ith triggered damage rating ruleiNumber of tasks detected for ith triggered damage-assessment rule, YiAnd a is a score coefficient, which is the number of tasks of the ith triggered damage assessment rule.
5. The artificial intelligence based impairment rule screening method of claim 1, wherein the formula of the second calculation rule comprises:
Ni＝(T1-T2)×W×a
Niis the score value, T, of the ith un-triggered damage-assessment rule1For the creation time point of the ith triggerless damage-assessment rule, T2At the current time point, W is the rule weight, and a is the score coefficient.
6. The artificial intelligence based impairment rule screening method of claim 1, wherein the receiving feedback information sent by the first user based on the ranking result comprises:
and sorting the triggered damage assessment rule and the triggerless damage assessment rule from high to low based on the score value to obtain a sorting result, and taking the information selected from the sorting result by the first user as the feedback information.
7. The artificial intelligence based damage assessment rule screening method of claim 1, wherein the feeding back all damage assessment rules of the target damage assessment rule set to a preset user comprises:
reading the weight value of each loss assessment rule in the target loss assessment rule set in the loss assessment rule engine, and multiplying the weight value by a preset coefficient to obtain a target weight value;
and sequencing each damage assessment rule in the target damage assessment rule set from high to low according to the target weight value, and setting the feedback times and time periods of each damage assessment rule fed back to the preset user according to the sequencing result.
8. The utility model provides a loss assessment rule sieving mechanism based on artificial intelligence which characterized in that, the device includes:
an acquisition module: the method comprises the steps that a project to be damaged is read from a preset database, and the project to be damaged is matched with a damage assessment rule in a preset damage assessment rule engine to obtain a triggered damage assessment rule set and an un-triggered damage assessment rule set of the project to be damaged; the triggered damage assessment rule set comprises at least one triggered damage assessment rule, and the triggerless damage assessment rule set comprises at least one triggerless damage assessment rule;
a calculation module: the system comprises a trigger damage assessment rule, a trigger damage assessment rule and a non-trigger damage assessment rule, wherein the trigger damage assessment rule is used for scoring based on a preset first calculation rule, and the non-trigger damage assessment rule is scored based on a preset second calculation rule to obtain scoring values of the trigger damage assessment rule and the non-trigger damage assessment rule;
a selecting module: the system comprises a first user, a second user and a third user, wherein the first user is used for sending a ranking result of the triggered damage assessment rules and the triggerless damage assessment rules based on the score value to the second user, receiving feedback information sent by the first user based on the ranking result, selecting a first preset number of triggered damage assessment rules as a first candidate rule set according to the feedback information, and selecting a second preset number of triggerless damage assessment rules as a second candidate rule set;
a recommendation module: the system comprises a first candidate rule set, a second candidate rule set and a damage assessment rule engine, wherein the first candidate rule set and the second candidate rule set are used for executing union set operation to obtain a target damage assessment rule set, the target damage assessment rule set is stored in the damage assessment rule engine, and all damage assessment rules of the target damage assessment rule set are fed back to a preset user.
9. An electronic device, characterized in that the electronic device comprises:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores a program executable by the at least one processor to enable the at least one processor to perform the artificial intelligence based impairment rule screening method of any one of claims 1 to 7.
10. A computer-readable medium, characterized in that the computer-readable medium stores a damage-assessment rule screening program, which when executed by a processor, implements the steps of the artificial intelligence-based damage-assessment rule screening method according to any one of claims 1 to 7.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114900468A (en) * | 2022-05-25 | 2022-08-12 | 曙光网络科技有限公司 | Rule matching method, device, equipment and storage medium |
| CN116579592A (en) * | 2023-07-14 | 2023-08-11 | 凯泰铭科技（北京）有限公司 | Vehicle damage assessment matching identification method in visual mode |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114900468A (en) * | 2022-05-25 | 2022-08-12 | 曙光网络科技有限公司 | Rule matching method, device, equipment and storage medium |
| CN114900468B (en) * | 2022-05-25 | 2024-04-12 | 曙光网络科技有限公司 | Rule matching method, device, equipment and storage medium |
| CN116579592A (en) * | 2023-07-14 | 2023-08-11 | 凯泰铭科技（北京）有限公司 | Vehicle damage assessment matching identification method in visual mode |
| CN116579592B (en) * | 2023-07-14 | 2023-09-08 | 凯泰铭科技（北京）有限公司 | Vehicle damage assessment matching identification method in visual mode |
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