CN110911005A - Data analysis system and server - Google Patents
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
- G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
- G16H40/67—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H80/00—ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
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Abstract
The embodiment of the invention provides a data analysis system and a server side, and relates to the technical field of data analysis. According to the data analysis system and the server provided by the embodiment of the invention, the data analysis request sent by the client is responded, the symptom options are provided for the client sending the data analysis request, so that the client selects at least one option in the symptom options and sends the selected option to the server, and after the server receives the option selected by the client, the option selected by the client is matched with each symptom corresponding to a plurality of pre-stored data analysis results to obtain a target data analysis result, and the target data analysis result is sent to the client, so that the self-service analysis of data is realized, the analysis efficiency of pet data is improved, and the delay of the optimal opportunity of data analysis and diagnosis and treatment is avoided.
Description
Technical Field
The invention relates to the technical field of data analysis, in particular to a data analysis system and a server side.
Background
With the improvement of living standard, people pay more and more attention to spiritual pursuit, for example, more and more people choose to raise pets, and build deep friendship with pets, so as to enrich own emotions. However, in the raising process, not only the diet of the pet is taken care of, but also the data of the pet is analyzed.
At present, the data analysis of pets is carried out by carrying the pets to a specified site, and the pets are observed and analyzed manually. In the process of arriving at a designated site, a plurality of uncontrollable factors exist, and the optimal time for analyzing and diagnosing the pet data is delayed.
Disclosure of Invention
Based on the research, the invention provides a data analysis system and a server side.
Embodiments of the invention may be implemented as follows:
in a first aspect, an embodiment provides a data analysis system, including a server and a client, where the server is in communication connection with the client; at least one symptom corresponding to each data analysis result is prestored in the server;
the server is used for responding to a data analysis request sent by the client and providing symptom options for the client sending the data analysis request;
the client is used for selecting at least one option in the symptom options and sending the selected option to the server;
the server is used for receiving the options selected by the client, matching the options selected by the client with various symptoms corresponding to various pre-stored data analysis results to obtain target data analysis results, and sending the target data analysis results to the client.
In an optional embodiment, the server also prestores the weight of each symptom corresponding to each data analysis result;
the server is used for mapping and matching the options selected by the client with various symptoms corresponding to various pre-stored data analysis results to obtain target symptoms corresponding to each option selected by the client and target data analysis results corresponding to all the target symptoms;
and obtaining the occurrence probability of the target data analysis result according to the weight of each target symptom corresponding to the target data analysis result.
In an optional implementation manner, the server is configured to add the weight of each target symptom corresponding to the target data analysis result to obtain an occurrence probability of the target data analysis result.
In an alternative embodiment, the symptom options include a first set of symptom options and a second set of symptom options;
the server is used for responding to a data analysis request sent by the client and providing the first symptom option set for the client sending the data analysis request;
the client is used for selecting at least one option in the first symptom option set and sending the option in the selected first symptom option to the server;
the server is used for providing the second symptom option set for the client after receiving the options in the first symptom options sent by the client;
the client is used for selecting at least one option in the second symptom option set according to the second symptom option set provided by the server and sending the selected option in the second symptom option set to the server.
In an optional embodiment, the server is further configured to provide symptom filling information to the client sending the data analysis request;
the client is used for filling in information according to the symptoms provided by the server, filling in the symptom information and sending the symptom information to the server;
the server side is used for extracting keywords in the symptom information after receiving the symptom information, mapping and matching the keywords with various symptoms corresponding to various pre-stored data analysis results to obtain target data analysis results, and sending the target data analysis results to the client side.
In an optional embodiment, the server side further prestores an analysis principle of each data analysis result;
and the server is also used for sending the analysis principle of the target data analysis result to the client after the target data analysis result is obtained.
In an optional embodiment, the server is further configured to send an inquiry request to the client after receiving the option selected by the client;
the client is used for selecting whether to confirm the selected option or not after receiving the inquiry request, and if so, sending a confirmation request to the server so that the server matches the option selected by the client with each symptom corresponding to a plurality of data analysis results after receiving the confirmation request; and if not, sending a negative request to the server, so that the server provides symptom options to the client again after receiving the negative request.
In a second aspect, an embodiment provides a server, where the server is in communication connection with a client; at least one symptom corresponding to each data analysis result is prestored in the server;
the server is used for responding to a data analysis request sent by the client, providing symptom options for the client sending the data analysis request, matching the options selected by the client with various symptoms corresponding to various pre-stored data analysis results after receiving the options selected by the client to obtain target data analysis results, and sending the target data analysis results to the client.
In an optional embodiment, the server also prestores the weight of each symptom corresponding to each data analysis result;
the server is used for mapping and matching the options selected by the client with various symptoms corresponding to various pre-stored data analysis results to obtain target symptoms corresponding to each option selected by the client and target data analysis results corresponding to all the target symptoms;
and obtaining the occurrence probability of the target data analysis result according to the weight of each target symptom corresponding to the target data analysis result.
In an optional implementation manner, the server is configured to add the weight of each target symptom corresponding to the target data analysis result to obtain an occurrence probability of the target data analysis result.
According to the data analysis system and the server provided by the embodiment of the invention, the data analysis request sent by the client is responded, the symptom options are provided for the client sending the data analysis request, so that the client selects at least one option in the symptom options and sends the selected option to the server, and after the server receives the option selected by the client, the option selected by the client is matched with each symptom corresponding to a plurality of pre-stored data analysis results to obtain a target data analysis result, and the target data analysis result is sent to the client, so that the self-service analysis of data is realized, the analysis efficiency of pet data is improved, and the delay of the optimal opportunity of data analysis and diagnosis and treatment is avoided.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a block diagram of a data analysis system according to an embodiment of the present invention.
Fig. 2 is a block diagram of a server according to an embodiment of the present invention.
Fig. 3 is a block diagram of a client according to an embodiment of the present invention.
FIG. 4 is a diagram illustrating a symptom option provided by an embodiment of the present invention.
Icon: 100-a data analysis system; 10-a server side; 11-a first memory; 12-a first processor; 13-a first communication unit; 20-a client; 21-a second memory; 22-a second processor; 23-an input-output unit; 24-a display unit; 25-a second communication unit; 30-network.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of 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.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
In the description of the present invention, it should be noted that if the terms "upper", "lower", "inside", "outside", etc. indicate an orientation or a positional relationship based on that shown in the drawings or that the product of the present invention is used as it is, this is only for convenience of description and simplification of the description, and it does not indicate or imply that the device or the element referred to must have a specific orientation, be constructed in a specific orientation, and be operated, and thus should not be construed as limiting the present invention.
Furthermore, the appearances of the terms "first," "second," and the like, if any, are used solely to distinguish one from another and are not to be construed as indicating or implying relative importance.
It should be noted that the features of the embodiments of the present invention may be combined with each other without conflict.
At present, data analysis of pets is carried out by carrying the pets to a specified site, and observation and analysis are carried out manually. In the process of arriving at a designated site, there are many uncontrollable factors, such as traffic jams and the like, that delay the best opportunity for pet data analysis and diagnosis.
Based on the above research, the present embodiment provides a data analysis system to improve the above problems.
Referring to fig. 1, a data analysis system 100 provided in the present embodiment includes a server 10 and a client 20, and fig. 1 is an interaction diagram of the communication between the server 10 and at least one client 20 according to the preferred embodiment of the present invention. The server 10 can communicate with the client 20 through the network 30 to realize data communication or interaction between the server 10 and the client 20.
In this embodiment, the server 10 may be, but is not limited to, a web server, an ftp (file transfer protocol) server, and the like. The client 20 may be, but is not limited to, a smart phone, a Personal Computer (PC), a tablet PC, a Personal Digital Assistant (PDA), a Mobile Internet Device (MID), and the like.
The network 30 may be, but is not limited to, a wired network or a wireless network, such as General Packet Radio Service (GPRS), third Generation mobile communication technology (3rd-Generation, 3G), fourth Generation mobile communication technology (4G), fifth Generation mobile communication technology (5th-Generation, 5G), wireless network (WIFI), and the like.
The operating system of the client 20 may be, but is not limited to, an Android system, an ios (Android system), a Windows phone system, a Windows system, and the like. The client 20 may download an APPlication (APP) required for installation from the server 10 through the network 30. The application program installed on the client 20 can directly perform data communication and interaction with the server 10.
As shown in fig. 2, in the present embodiment, the server 10 includes a first memory 11, a first processor 12 and a first communication unit 13, and the elements of the first memory 11, the first processor 12 and the first communication unit 13 are electrically connected to each other directly or indirectly to implement data transmission or interaction. For example, the components may be electrically connected to each other via one or more communication buses or signal lines.
The first Memory 11 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like. The first memory 11 is used for storing programs or data. The first communication unit 13 is configured to establish a communication connection between the server 10 and the client 20 through the network 30, and is configured to transceive data through the network 30.
As shown in fig. 3, in the present embodiment, the client 20 includes a second memory 21, a second processor 22, an input-output unit 23, a display unit 24, and a second communication unit 25. The elements of the second memory 21, the second processor 22, the input/output unit 23, the display unit 24 and the second communication unit 25 are directly or indirectly electrically connected to each other to realize data transmission or interaction. For example, the components may be electrically connected to each other via one or more communication buses or signal lines.
The hardware configuration of the second memory 21 is the same as that of the first memory 11, and is not described herein again.
The first processor 12 and the second processor 22 may be integrated circuit chips having signal processing capabilities. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but may also be a Digital Signal Processor (DSP)), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The input and output unit 23 is used for providing input data for a user to realize the interaction of the user and the client 20. The input/output unit 23 may be, but is not limited to, a mouse, a keyboard, and the like.
The display unit 24 provides an interactive interface (e.g., a user interface) between the client 20 and a user for displaying web page information. In this embodiment, the display unit 24 may be a liquid crystal display or a touch display.
The second communication unit 25 is configured to establish a connection with the first communication unit 13 of the server 10 through the network 30, so as to implement a communication connection between the server 10 and the client 20.
The following describes an interaction diagram of the server 10 communicating with at least one client 20.
The server 10 is configured to provide a symptom option to the client 20 sending the data analysis request in response to the data analysis request sent by the client 20.
Optionally, in this embodiment, the client 20 is installed with an APP, and if the user needs to analyze a pet, the user enters the APP and initiates a data analysis request to the server 10 through the APP on the client 20. Specifically, when the user enters the APP interface, the type of pet to be analyzed, such as a cat, a dog, a pet, etc., is selected, and thus a data analysis request is initiated to the server 10, where the data analysis request includes the type of pet to be analyzed.
After receiving the data analysis request initiated by the client 20, the server 10 responds to the data analysis request, analyzes the data analysis request to obtain the type of the pet to be analyzed, and provides a symptom option for the client 20 sending the data analysis request according to the type of the pet and the symptom corresponding to the data analysis result. The server 10 stores at least one symptom corresponding to each data analysis result in advance.
The client 20 is configured to select at least one of the symptom options and send the selected option to the server 10.
The symptom options provided by the server 10 to the client 20 include multiple options, which mainly include conventional symptom options of the type of pet to be analyzed, such as body temperature, skin, and the like, and the specific options can be adjusted according to the selection frequency and the needs of the user.
After receiving the symptom options provided by the server 10, the client 20 presents the options to the user, the user selects at least one corresponding option from the presented symptom options, and after obtaining the options selected by the user, the client 20 sends the options selected by the user to the server 10 for processing.
The server 10 is configured to receive the option selected by the client 20, match the option selected by the client 20 with each symptom corresponding to a plurality of pre-stored data analysis results to obtain a target data analysis result, and send the target data analysis result to the client 20.
The server 10 stores at least one symptom corresponding to each data analysis result in advance, and then, after receiving the option selected by the client 20, the server 10 can match the option selected by the client 20 with each symptom corresponding to a plurality of pre-stored data analysis results to obtain a target analysis result. For example, the a data analysis result includes a symptom, B symptom, and C symptom, the B data analysis result includes C symptom, and the C data analysis result includes a symptom, B symptom, and D symptom, the options selected by the client 20 include an a option and a B option, the a option corresponds to the a symptom, the B option corresponds to the B symptom, the option selected by the client 20 is matched with each symptom corresponding to the plurality of pre-stored data analysis results, and the a data analysis result and the C data analysis result are obtained as the target data analysis result.
In this embodiment, the correspondence between each data analysis result and the symptom is constructed in advance based on the result obtained by analyzing the symptom manually on site and each literature, and is stored in the server 10. Taking the analysis result of the data of the respiratory system of dogs as an example, the resistance of dogs in different age groups to diseases of the respiratory system is different, such as: the data analysis result of the canine infectious tracheobronchitis mainly occurs to young dogs and then to young dogs in 2-6 months, the number of the canine infectious tracheobronchitis diseases is small, the canine infectious tracheobronchitis diseases do not occur in dogs eating breast milk, the data analysis result of the canine infectious tracheobronchitis is related to the body temperature of the dogs and the capability of resisting pathogenic bacteria, the body temperature of the young dogs below 2 months is 38.7-39.5 ℃, the optimal growth temperature of the bordetella bronchiseptica is 35-37 ℃, and the body temperature of the dogs above 6 months is 37.5-38.5 ℃, so that the respiratory tract of the young dogs above 6 months is quite suitable for the growth of the bordetella bronchiseptica, the young dogs can be triggered as long as the resistance of the young dogs is reduced, and the young dogs above 18 months are almost infected and can obtain a certain resistance, so the canine infectious tracheobronchitis bronchiseptica basically cannot be triggered. Therefore, the symptoms corresponding to the data analysis result of the canine infectious tracheobronchitis comprise 6 to 18 months of age, and when the data analysis is carried out, the screening is carried out according to the age of the dog, the time consumption is reduced, and the working efficiency is improved.
Meanwhile, many canine respiratory diseases are obviously seasonal, and usually peak times are reached when the summer months alternate in spring and summer to the 6 months in autumn and winter to the 11 months in winter. Therefore, in this embodiment, seasonal factors are also stored in association as symptom options of the data analysis result. Moreover, some diseases in the respiratory system of dogs belong to infectious diseases, such as infectious bronchitis of dogs, which are urgent in onset, high in infectivity and high in death rate, and need to be paid attention to. Therefore, in this embodiment, whether the animal has been contacted with other diseased animals or whether other animals contacted with the diseased animals have similar symptoms is also stored in association as a symptom option of the data analysis result of the canine infectious tracheobronchitis.
In addition, since canine respiratory diseases have similar symptoms, many diseases show partially the same symptoms, and most respiratory diseases show symptoms of watery nasal discharge and cough, it is necessary to distinguish the diseased region, whether the disease is a systemic disease or a respiratory disease, whether the disease is an upper respiratory disease or a lower respiratory disease, wherein the upper respiratory disease includes a nasal disease and a throat region, and the lower respiratory disease includes a tracheobronchial disease and a pulmonary disease. Further, in the present embodiment, the body part also stores the symptom options as the data analysis results in association.
It should be noted that the data analysis system 100 provided in the present embodiment can also be used for conventional data analysis of pets, such as age and weight analysis of pets, mental state data analysis of pets, and physical characteristics and varieties analysis of pets, and is not limited to the above-mentioned examples.
Optionally, the corresponding relationship between each data analysis result and the symptom may be updated according to a certain period.
The data analysis system 100 provided in this embodiment obtains the target data analysis result by matching the option selected by the client 20 with each symptom corresponding to a plurality of pre-stored data analysis results, and sends the target data analysis result to the client 20, thereby implementing self-service analysis of pet data and improving the analysis efficiency of pet data.
In an optional embodiment, the server 10 further prestores weights of the symptoms corresponding to each data analysis result, and the server 10 is configured to map and match the option selected by the client 20 with the prestored symptoms corresponding to multiple data analysis results to obtain target symptoms corresponding to each option selected by the client 20 and target data analysis results corresponding to all the target symptoms.
And obtaining the occurrence probability of the target data analysis result according to the weight of each target symptom corresponding to the target data analysis result.
In this embodiment, the server 10 provides the client 20 with the symptom options corresponding to the pre-stored symptoms, and further maps and matches the options selected by the client 20 with the pre-stored symptoms corresponding to each data analysis result, so as to obtain a plurality of target symptoms corresponding to the options, and then obtains the target data analysis results corresponding to all the target symptoms according to the correspondence between the data analysis results and the symptoms, where the obtained target data analysis results may also be a plurality of target data analysis results.
For example, the server 10 stores a plurality of symptoms corresponding to data analysis results, such as symptoms corresponding to conventional data analysis results, such as growth conditions, and after the user sends a data analysis request to the server 10 through the client 20, the server 10 provides various symptom options, such as symptom options of body temperature increase, body temperature decrease, nasal dryness, age, and the like, to the client 20 according to the data analysis request, and each symptom option has a corresponding data analysis result; after receiving the various symptom options, the client 20 selects one or more options, such as options of body temperature rise, nasal dryness, three months of age, and sends the selected options to the server 10; the server 10 maps and matches the option selected by the client 20 with the pre-stored symptoms to obtain the target symptoms of body temperature rise, nasal dryness and three months of age, wherein the data analysis result corresponding to the target symptom of body temperature rise comprises a data analysis result and b data analysis result, the data analysis result corresponding to the target symptom of nasal dryness comprises a data analysis result and c data analysis result, and the data analysis result corresponding to the target symptom of three months of age comprises a data analysis result and d data analysis result, so that the target data analysis results corresponding to all the target symptoms comprise a data analysis result, b data analysis result, c data analysis result and d data analysis result.
As an alternative implementation, the symptom options provided in this embodiment include a conventional symptom option (such as body temperature, skin, etc.) and a numerical symptom option (such as age, time, etc.), and if the options selected by the client 20 include the numerical symptom option, the numerical symptom option is subjected to range mapping matching with the pre-stored symptoms, for example, the pre-stored symptoms are less than 6 months old, more than 6 months old, etc., and the options selected by the client 20 are three months old, the numerical symptom option is subjected to range mapping matching with the pre-stored symptoms, and the obtained target symptom is less than 6 months old.
After all the target data analysis results are obtained, the occurrence probability of each target data analysis result can be obtained according to the weight of each target symptom corresponding to each target data analysis result.
Specifically, the server 10 is configured to add the weight of each target symptom corresponding to each target data analysis result to obtain the occurrence probability of the target data analysis result.
For example, the symptoms corresponding to the analysis result of the target data include symptoms such as increased body temperature, nasal dryness, three months of age, thickened foot pad, and cough, which are weighted 15%, 25%, 30%, 16%, and 14%, the symptoms corresponding to the analysis result of the target data include increased body temperature, vomiting, and other symptoms, which are weighted 10%, 30%, and 70%, the symptoms corresponding to the analysis result of the target data include nasal dryness and other symptoms, which are weighted 26% and 74%, and the symptoms corresponding to the analysis result of the target data include three months of age, which are weighted 30% and 70%, respectively. And adding the weight of each target symptom corresponding to each target data analysis result to obtain that the occurrence probability of the target data analysis result is 70%, the occurrence probability of the target data analysis result is 10%, the occurrence probability of the target data analysis result is 26% and the occurrence probability of the target data analysis result is 30%.
As an optional implementation manner, in this embodiment, the weight of the symptom corresponding to the data analysis result may also be adjusted according to the use condition of the user, that is, the accuracy of the corresponding relationship between the selected option and the data analysis result, so as to update the corresponding relationship between the data analysis result and the symptom.
In an alternative embodiment, to facilitate user operation and improve convenience of operation, please refer to fig. 4 in combination, the symptom options include a first set of symptom options and a second set of symptom options.
The server 10 is configured to provide the first symptom option set to the client 20 sending the data analysis request in response to the data analysis request sent by the client 20.
The client 20 is configured to select at least one option in the first symptom option set, and send an option in the selected first symptom options to the server 10.
The server 10 is configured to provide the second set of symptom options to the client 20 after receiving an option in the first symptom options sent by the client 20.
The client 20 is configured to select at least one option in the second symptom option set according to the second symptom option set provided by the server 10, and send the selected option in the second symptom option set to the server 10.
Optionally, in this embodiment, the second symptom option set is a subset of options in the first symptom option set, that is, the options in the second symptom option set are sub-options of the options in the first symptom option set. For example, as shown in fig. 4, the service 10 provides a first set of symptom options to the sending client 20, where the first set of symptom options includes a option, B option, C option, and the like, the client 20 provides a option to the service 10 after selecting a option, and the service 10 provides a second set of symptom options to the client 20 according to the a option, where the second set of symptom options includes a1 option, a2 option, and A3 option, that is, the a1 option, the a2 option, and the A3 option are sub-options of the a option.
In an alternative embodiment, the server 10 is further configured to provide symptom filling information to the client 20 that sent the data analysis request.
The client 20 is configured to fill in information according to the symptom provided by the server 10, fill in symptom information, and send the information to the server 10.
The server 10 is configured to extract keywords from the symptom information after receiving the symptom information, perform mapping matching on the keywords and each symptom corresponding to a plurality of pre-stored data analysis results to obtain target data analysis results, and send the target data analysis results to the client 20.
In this embodiment, if the symptom option provided by the server 10 to the client 20 sending the data analysis request is not selectable by the client 20, the client 20 may also initiate a filling request to the server 10, and the server 10 provides symptom filling information to the client 20 after receiving the filling request initiated by the client 20. The client 20 receives the symptom filling information, fills the symptom information, and sends the symptom information to the server 10, and after receiving the symptom information, the server 10 processes the symptom information, extracts keywords in the symptom information, then maps and matches the keywords with various symptoms corresponding to a plurality of pre-stored data analysis results, so as to obtain a target data analysis result, and sends the target data analysis result to the client 20.
In an alternative embodiment, the server 10 also prestores the analysis principle of each data analysis result.
The server 10 is further configured to send an analysis principle of the target data analysis result to the client 20 after the target data analysis result is obtained.
Optionally, in this embodiment, after obtaining the target data analysis result, the server 10 sends the target data analysis result to the client 20, and simultaneously, may also send the analysis principle of the target data analysis result to the client 20, so that the user can conveniently check the result, take care of the pet, and avoid delaying the optimal time for analyzing and diagnosing the pet data.
In an alternative embodiment, in order to ensure the accuracy of the option selected by the user, the server 10 is further configured to send an inquiry request to the client 20 after receiving the option selected by the client 20.
The client 20 is configured to select whether to confirm the selected option after receiving the query request, and if so, send a confirmation request to the server 10, so that the server 10 matches the option selected by the client 20 with each symptom corresponding to the multiple data analysis results after receiving the confirmation request; if not, sending a negative request to the server 10, so that the server 10 provides symptom options to the client 20 again after receiving the negative request.
The data analysis system 100 provided in this embodiment sends an inquiry request to the client 20, so that the client 20 confirms the selected option, thereby ensuring the correctness of the option selected by the user and improving the accuracy of data analysis.
As an optional implementation manner, the data analysis system 100 provided in this implementation may further analyze the symptom corresponding to the data analysis result according to the data analysis result, specifically, the server 10 provides the data analysis result to the client 20, the client 20 selects the corresponding data analysis result, and the server 10 obtains the corresponding symptom according to the data analysis result selected by the client 20 and sends the obtained symptom to the client 20, so that the user can conveniently know the symptom corresponding to the data analysis result.
As an optional implementation manner, the technical platform adopted by the data analysis system 100 provided by this embodiment is Spring MVC, and a Spring Cloud micro-service framework is used, and the APP of the client 20 is developed in a native mode, and compared with an H5 mode, the running speed is fast, and the operation experience is good.
On the basis, the embodiment further provides a server 10, where the server 10 is in communication connection with the client 20; at least one symptom corresponding to each data analysis result is prestored in the server 10.
The server 10 is configured to respond to a data analysis request sent by the client 20, provide symptom options to the client 20 that sends the data analysis request, match the options selected by the client 20 with various symptoms corresponding to multiple pre-stored data analysis results after receiving the options selected by the client 20, obtain target data analysis results, and send the target data analysis results to the client 20.
In an optional embodiment, the server 10 further prestores weights of symptoms corresponding to each data analysis result.
The server 10 is configured to map and match the options selected by the client 20 with the pre-stored symptoms corresponding to multiple data analysis results, so as to obtain target symptoms corresponding to each option selected by the client 20 and target data analysis results corresponding to all the target symptoms.
And obtaining the occurrence probability of the target data analysis result according to the weight of each target symptom corresponding to the target data analysis result.
In an optional embodiment, the server 10 is configured to add the weight of each target symptom corresponding to the target data analysis result to obtain the occurrence probability of the target data analysis result.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process of the server 10 described above may refer to the corresponding process in the foregoing method, and will not be described in too much detail herein.
The data analysis system and the server provided by the embodiment establish a technical platform for remote analysis of pet data based on a network by combining the computing power and data processing technology of a computer with the internet technology, and provide a new idea for solving the problem of difficulty in analyzing pet data.
In summary, the data analysis system and the server provided in this embodiment provide the symptom options to the client sending the data analysis request by responding to the data analysis request sent by the client, so that the client selects at least one of the symptom options and sends the selected option to the server, and after receiving the option selected by the client, the server matches the option selected by the client with each symptom corresponding to a plurality of pre-stored data analysis results to obtain a target data analysis result, and sends the target data analysis result to the client, thereby implementing self-service analysis of data, improving analysis efficiency of pet data, and avoiding delaying the optimal time for data analysis and diagnosis and treatment.
The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (10)
1. A data analysis system is characterized by comprising a server and a client, wherein the server is in communication connection with the client; at least one symptom corresponding to each data analysis result is prestored in the server;
the server is used for responding to a data analysis request sent by the client and providing symptom options for the client sending the data analysis request;
the client is used for selecting at least one option in the symptom options and sending the selected option to the server;
the server is used for receiving the options selected by the client, matching the options selected by the client with various symptoms corresponding to various pre-stored data analysis results to obtain target data analysis results, and sending the target data analysis results to the client.
2. The data analysis system of claim 1, wherein the server further pre-stores a weight of each symptom corresponding to each data analysis result;
the server is used for mapping and matching the options selected by the client with various symptoms corresponding to various pre-stored data analysis results to obtain target symptoms corresponding to each option selected by the client and target data analysis results corresponding to all the target symptoms;
and obtaining the occurrence probability of the target data analysis result according to the weight of each target symptom corresponding to the target data analysis result.
3. The data analysis system of claim 2, wherein the server is configured to add the weights of each of the target symptoms corresponding to the target data analysis result to obtain the occurrence probability of the target data analysis result.
4. The data analysis system of claim 1, wherein the symptom options include a first set of symptom options and a second set of symptom options;
the server is used for responding to a data analysis request sent by the client and providing the first symptom option set for the client sending the data analysis request;
the client is used for selecting at least one option in the first symptom option set and sending the option in the selected first symptom option to the server;
the server is used for providing the second symptom option set for the client after receiving the options in the first symptom options sent by the client;
the client is used for selecting at least one option in the second symptom option set according to the second symptom option set provided by the server and sending the selected option in the second symptom option set to the server.
5. The data analysis system of claim 1, wherein the server is further configured to provide symptom filling information to the client sending the data analysis request;
the client is used for filling in information according to the symptoms provided by the server, filling in the symptom information and sending the symptom information to the server;
the server side is used for extracting keywords in the symptom information after receiving the symptom information, mapping and matching the keywords with various symptoms corresponding to various pre-stored data analysis results to obtain target data analysis results, and sending the target data analysis results to the client side.
6. The data analysis system of claim 1, wherein the server is further pre-stored with an analysis principle of each data analysis result;
and the server is also used for sending the analysis principle of the target data analysis result to the client after the target data analysis result is obtained.
7. The data analysis system of claim 1, wherein the server is further configured to send a query request to the client after receiving the option selected by the client;
the client is used for selecting whether to confirm the selected option or not after receiving the inquiry request, and if so, sending a confirmation request to the server so that the server matches the option selected by the client with each symptom corresponding to a plurality of data analysis results after receiving the confirmation request; and if not, sending a negative request to the server, so that the server provides symptom options to the client again after receiving the negative request.
8. The server side is characterized in that the server side is in communication connection with a client side; at least one symptom corresponding to each data analysis result is prestored in the server;
the server is used for responding to a data analysis request sent by the client, providing symptom options for the client sending the data analysis request, matching the options selected by the client with various symptoms corresponding to various pre-stored data analysis results after receiving the options selected by the client to obtain target data analysis results, and sending the target data analysis results to the client.
9. The server according to claim 8, wherein the server also prestores weights of symptoms corresponding to each data analysis result;
the server is used for mapping and matching the options selected by the client with various symptoms corresponding to various pre-stored data analysis results to obtain target symptoms corresponding to each option selected by the client and target data analysis results corresponding to all the target symptoms;
and obtaining the occurrence probability of the target data analysis result according to the weight of each target symptom corresponding to the target data analysis result.
10. The server according to claim 9, wherein the server is configured to add the weights of each target symptom corresponding to the target data analysis result to obtain the occurrence probability of the target data analysis result.
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