CN110691145A - Data recommendation method and device, server and storage medium - Google Patents
Data recommendation method and device, server and storage medium Download PDFInfo
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Abstract
The invention provides a data recommendation method, a data recommendation device, a server and a storage medium, and relates to the technical field of data processing, wherein the data recommendation method and the data recommendation device are applied to the server, the server is in communication connection with a terminal, and the server stores a plurality of geographical positions and a custom data set corresponding to each geographical position in advance; the data recommendation method comprises the following steps: responding to a sleep mode setting request sent by a terminal, and acquiring a target geographical position corresponding to the sleep mode setting request; determining target data from a plurality of user-defined data sets according to the target geographic position; and feeding back the target data to the terminal so that the terminal displays the target data. Compared with the prior art, the user can complete the setting of the sleep mode only by selecting the target data, and meanwhile, the target data can improve the sleep comfort level of the user to the maximum extent, and the user experience is improved.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a data recommendation method, a data recommendation device, a server and a storage medium.
Background
With the development of science and technology, more and more smart homes are used in life and work of people, such as air conditioners, televisions, washing machines and the like. Taking an air conditioner as an example, it may operate according to an operation parameter (e.g., cooling/heating, set temperature, wind speed, etc.) set by a user, thereby providing a comfortable environment for the user. When a user sleeps, the air conditioner is usually set to be in a sleep mode, the current sleep mode requires that the user set various parameters one by one, and the situation that the user is waken up or is waken up due to improper parameter setting may occur, so that great influence is brought to the sleep quality of the user, and the user experience is influenced.
Disclosure of Invention
The invention solves the problem that the existing sleep mode setting mode can not meet the user requirements and influence the user experience.
In order to solve the problems, the invention provides a data recommendation method which is applied to a server, wherein the server is in communication connection with a terminal, and a plurality of geographical positions and a custom data set corresponding to each geographical position are stored in the server in advance; the data recommendation method comprises the following steps: responding to a sleep mode setting request sent by the terminal, and acquiring a target geographical position corresponding to the sleep mode setting request; determining target data from the plurality of user-defined data sets according to the target geographic position; and feeding back the target data to the terminal so that the terminal displays the target data.
Compared with the prior art, the data recommendation method has the following advantages: when a user enters a setting interface of a sleep mode, a terminal sends a sleep mode setting request to a server, and the server firstly acquires a target geographical position of the user after receiving the request; then, according to the target geographic position, target data are found out from the plurality of user-defined data sets and fed back to the terminal, the terminal displays the target data, and therefore a user can complete the setting of the sleep mode only by selecting the target data, meanwhile, the target data can improve the sleep comfort level of the user to the maximum degree, and user experience is improved.
Further, after the step of responding to the sleep mode setting request sent by the terminal and acquiring the target geographic position corresponding to the sleep mode setting request, the data recommendation method further includes: judging whether the target geographical position exists in a plurality of prestored geographical positions; if yes, executing the step of determining target data from the plurality of user-defined data sets according to the target geographic position; if not, acquiring preset data, and taking the preset data as the target data.
Further, the custom data set comprises a plurality of custom data items, each custom data item comprising at least one custom data; the step of determining target data from the plurality of user-defined data sets according to the target geographic position comprises the following steps: according to the target geographic position, determining a first user-defined data set corresponding to the target geographic position from the user-defined data sets; and obtaining the user-defined data with the maximum use times under each user-defined data item in the first user-defined data set to obtain a group of user-defined data with the maximum use times, and taking the group of user-defined data with the maximum use times as the target data.
Further, the step of determining target data from the plurality of user-defined data sets according to the target geographic location further includes: judging whether a group of user-defined data with the largest number of use times exists in the first user-defined data set; if so, executing the step of obtaining the user-defined data with the maximum use times in each user-defined data item in the first user-defined data set to obtain a group of user-defined data with the maximum use times, and taking the group of user-defined data with the maximum use times as the target data; if not, determining a second user-defined data set from the user-defined data sets according to the target geographic position, wherein the distance between the geographic position corresponding to the second user-defined data set and the target geographic position is smaller than the distance between the geographic position corresponding to any other user-defined data set and the target geographic position; and obtaining the user-defined data with the maximum use times under each user-defined data item in the second user-defined data set to obtain a group of user-defined data with the maximum use times, and taking the group of user-defined data with the maximum use times as the target data.
Further, the server stores a custom operation data set corresponding to the terminal in advance, the custom operation data set comprises a plurality of custom operation data items, and each custom operation data item comprises at least one custom operation data; the step of determining target data from the plurality of user-defined data sets according to the target geographic position further includes: obtaining the user-defined operation data with the maximum use times under each user-defined operation data item in the user-defined operation data set to obtain a group of user-defined operation data with the maximum use times; generating reference data according to the set of user-defined operation data with the largest number of use times; calculating a difference between the reference data and the target data; and if the difference exceeds a preset range, taking the reference data as the target data.
Further, the group of the custom data with the most use times comprises custom time data; the step of generating the reference data according to the set of the customized operation data with the largest number of use times comprises the following steps: and combining the group of the customized operation data with the maximum use times with the customized time data to obtain reference data.
The invention also provides a data recommendation device which is applied to a server, wherein the server is in communication connection with the terminal, and a plurality of geographical positions and a custom data set corresponding to each geographical position are prestored in the server; the data recommendation device comprises: the acquisition module is used for responding to a sleep mode setting request sent by the terminal and acquiring a target geographical position corresponding to the sleep mode setting request; the determining module is used for determining target data from the user-defined data sets according to the target geographic position; and the sending module is used for feeding the target data back to the terminal so as to display the target data by the terminal.
Further, the determining module is further configured to: judging whether the target geographical position exists in a plurality of prestored geographical positions; if yes, executing the step of determining target data from the plurality of user-defined data sets according to the target geographic position; if not, acquiring preset data, and taking the preset data as the target data.
The present invention also provides a server, wherein the server is in communication connection with a terminal, and the server comprises: one or more processors; a memory for storing one or more programs that, when executed by the one or more processors, cause the one or more processors to implement the data recommendation method described above.
The present invention also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the data recommendation method described above.
Drawings
Fig. 1 is a schematic view of an application scenario of the data recommendation method provided by the present invention.
Fig. 2 is a block diagram of a server according to the present invention.
Fig. 3 is a schematic flow chart of a data recommendation method provided by the present invention.
Fig. 4 is another schematic flow chart of a data recommendation method provided by the present invention.
Fig. 5 is a flowchart illustrating step S120 in the data recommendation method shown in fig. 3.
Fig. 6 is another flowchart illustrating step S120 in the data recommendation method shown in fig. 3.
Fig. 7 is another schematic flow chart of a data recommendation method provided by the present invention.
Fig. 8 is another flowchart illustrating step S120 in the data recommendation method shown in fig. 3.
Fig. 9 is a schematic diagram of functional modules of the data recommendation device provided in the present invention.
Description of reference numerals:
10-a server; 20-a terminal; 30-smart home; 11-a processor; 12-a memory; 13-a bus; 100-a data recommendation device; 110-an obtaining module; 120-a determination module; 130-sending module.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.
Referring to fig. 1, an application scenario diagram of the data recommendation method provided by the present invention includes a server 10, a terminal 20, and an intelligent home 30, where the server 10 is connected to at least one terminal 20 through a communication network, and the terminal 20 is connected to the intelligent home 30 through the communication network, where the communication network may be a wired network or a wireless network.
The server 10 may be a web (website) server, and the server 10 is configured to store a plurality of geographic locations and a customized data set corresponding to each geographic location, and determine target data from the plurality of customized data sets and feed the target data back to the terminal 20 when receiving a sleep mode setting request sent by the terminal 20.
The terminal 20 may be, but is not limited to, a smart phone, a Personal Computer (PC), a tablet PC, a wearable mobile terminal, a Personal Digital Assistant (PDA), and the like. The operating system of the terminal 20 may be, but is not limited to, an Android system, an ios (internet operating system) system, a Windows phone system, a Windows system, and the like.
The terminal 20 is installed with an Application (APP), through which a user can interact with the server 10 and the smart home 30, and specifically, when the user needs to set a sleep mode for the smart home 30, the Application of the terminal 20 can send a sleep mode setting request to the server 10 and receive target data returned by the server 10, and display the target data. Then, if the user selects the target data, the setting of the sleep mode can be directly completed, and if the user does not select the target data but sets the items of data of the sleep mode by himself, the terminal 20 transmits the custom data to the server 10 for storage. After the sleep mode of the smart home 30 is set, the terminal 20 may control the smart home 30 to operate in the sleep mode.
The smart home 30 may be, but is not limited to, an air conditioner, a television, a washing machine, etc. For convenience of description, the following embodiments will be described in detail with reference to an air conditioner as an example.
Referring to fig. 2, which is a block diagram of a server 10 according to the present invention, the server 10 includes a processor 11, a memory 12 and a bus 13, and the processor 11 and the memory 12 are connected by the bus 13.
The memory 12 is used to store a program, such as the data recommendation device 100 shown in fig. 9. The data recommendation device 100 includes at least one software function module which may be stored in the memory 12 in the form of software or firmware (firmware) or solidified in an Operating System (OS) of the server 10. After receiving the execution instruction, the processor 11 executes the program to implement the data recommendation method disclosed by the invention.
The processor 11 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 11. The Processor 11 may be a general-purpose Processor, and includes 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.
On the basis of the server 10 shown in fig. 2, a possible implementation manner of a data recommendation method is given below, specifically, fig. 3 is a schematic flow chart of the data recommendation method provided by the present invention, and please refer to fig. 3, the data recommendation method includes:
step S110, responding to the sleep mode setting request sent by the terminal, and acquiring a target geographical position corresponding to the sleep mode setting request.
In this embodiment, the sleep mode setting request may be a request sent to the server 10 when the user needs to set the air conditioner to the sleep mode, and may be automatically triggered when the user enters the sleep mode setting interface, or may be triggered by the user by clicking a sleep mode setting control, which is not limited herein. After receiving the sleep mode setting request, the server 10 needs to obtain a target geographic location corresponding to the sleep mode setting request, that is, a geographic location where the user is currently located, where the target geographic location may be accurate to a region or a city.
If the user authorizes the acquisition of the geographic position, the terminal 20 may transmit the current geographic position of the user, that is, the target geographic position, to the server 10 when transmitting the sleep mode setting request to the server 10, the server 10 may directly obtain the target geographic position corresponding to the sleep mode setting request, and if the user does not authorize the acquisition of the geographic position, the server 10 may acquire the target geographic position corresponding to the sleep mode setting request by using an indirect method after receiving the sleep mode setting request transmitted by the terminal 20, for example, using an IP Address (Internet Protocol Address) positioning method, the terminal 20 may acquire an IP Address of WiFi connected to the terminal 20 when transmitting the sleep mode setting request to the server 10, and upload the IP Address to the server 10, the server 10 queries an IP Address positioning service provider after receiving the IP Address, the current geographic position of the user can be obtained; for another example, the geographical location where the user is currently located, which is obtained by the operator by using the base station positioning method, is obtained by cooperating with the operator in advance.
And step S120, determining target data from the plurality of user-defined data sets according to the target geographic position.
In this embodiment, the server 10 stores a plurality of geographic locations and a custom data set corresponding to each geographic location in advance, and the geographic locations may be accurate to a district or a city, for example, as shown in table 1, the 4 geographic locations of the metropolis city, the Chongqing city, the Beijing city, and the Shenzhen city respectively correspond to the 1# custom data set, the 2# custom data set, the 3# custom data set, and the 4# custom data set.
TABLE 1 geographical location and custom data set
| Adult city | 1# custom data set |
| Chongqing city | 2# custom data set |
| Beijing City | 3# custom data set |
| Shenzhen city | 4# custom data set |
Each custom data set includes custom data sent by the terminal 20, the custom data is operation status data set by the user for the air conditioner through the terminal 20 when the air conditioner is operated in the sleep mode, and the custom data may include, but is not limited to, a time period of a sleep mode switch (e.g., 23: 00-6: 00), a wind speed (e.g., 0.8-1.6 m/s), an operation mode (e.g., cooling, heating), a temperature (e.g., 26-28 ℃), and the like. After the sleep mode setting is completed, the terminal 20 sends the user-defined data set by the user to the server 10, and the server 10 obtains the geographic position corresponding to the user-defined data and stores the user-defined data corresponding to the same geographic position into the same user-defined data set.
In addition, the custom data set includes a plurality of custom data items, each including at least one custom data, which may include, but is not limited to, time period of sleep mode switch, wind speed, operation mode, temperature, etc., for example, please refer to table 2, the # 1 custom data set is as follows:
TABLE 21 # custom data set
| Time period | Wind speed | Mode of operation | Temperature of |
| 23:00～6:00 | 0.8m/s | Refrigeration system | 24℃ |
| 22:00～6:00 | 0.9m/s | Refrigeration system | 25℃ |
| 23:00～7:00 | 1.0m/s | Refrigeration system | 24℃ |
| 23:00～6:30 | 0.8m/s | Refrigeration system | 26℃ |
After receiving the custom data sent by the terminal 20, the server 10 puts each value in the custom data into each custom data item of the corresponding custom data set according to the geographic position, for example, receives the custom data { time period: 23: 00-6: 30; the wind speed is 0.8 m/s; the operation mode is refrigeration; and (3) 26 ℃, and if the corresponding geographic position is urban, putting each value in the urban into each custom data item of the 1# custom data set.
After receiving the sleep mode setting request sent by the terminal 20 and acquiring the target geographic location corresponding to the sleep mode setting request, the server 10 first collects a plurality of user-defined data sets according to the target geographic locationDetermining a target custom data set corresponding to the target geographic position, and then, for each custom data item of the target custom data set, respectively taking a mode of all custom data under each custom data item, wherein the mode refers to the mode that the occurrence frequency is more than that of the target custom data items
The self-defined data n refers to the number of all self-defined data under the current self-defined data item, so that the mode of each self-defined data item can be obtained to form a group of self-defined data, and the group of self-defined data is target data, namely sleep mode setting parameters with the maximum number of use times of the target geographic position.
And step S130, feeding back the target data to the terminal so that the terminal displays the target data.
In this embodiment, after the server 10 obtains the target data corresponding to the sleep mode setting request, the target data is fed back to the terminal 20, and the terminal 20 displays the target data, so that the user only needs to select the target data to complete the setting of the sleep mode, and if the user does not select the target data but sets various items of data of the sleep mode, the terminal 20 sends the custom data to the server 10.
In a possible situation, the server 10 may not store the custom data set corresponding to the target geographic location in advance, for example, in a region where the user is currently located, the terminal 20 has not sent the custom data to the server 10, and at this time, the server 10 cannot determine the target data from the multiple custom data sets, so on the basis of fig. 3, fig. 4 is another flow chart of the data recommendation method provided by the present invention, please refer to fig. 4, and after step S110, the data recommendation method further includes:
step S101, judging whether a target geographical position exists in a plurality of geographical positions stored in advance.
In this embodiment, step S120 is performed if the target geographic location exists in the plurality of geographic locations stored in advance, and step S102 is performed if the target geographic location does not exist in the plurality of geographic locations stored in advance.
Step S102, acquiring preset data, and taking the preset data as target data.
In this embodiment, the preset data refers to default parameters of a sleep mode preset by the server 10, and may be a set of customized data with the largest number of times of use in all customized data sets, or a set of customized data set by a developer according to experience, which is not limited herein.
As an embodiment, referring to fig. 5 on the basis of fig. 3, step S120 may include:
and a substep S1201, determining a first custom data set corresponding to the target geographic position from the plurality of custom data sets according to the target geographic position.
For example, if the obtained target geographic location is metropolitan and is combined in table 1, the determined first custom data set is the # 1 custom data set.
And step S1202, obtaining the user-defined data with the maximum use times under each user-defined data item in the first user-defined data set to obtain a group of user-defined data with the maximum use times, and taking the group of user-defined data with the maximum use times as target data.
For example, assuming that the first custom data set is a # 1 custom data set, the custom data with the largest number of uses under each custom data item are respectively: the time period is 23: 00-6: 00; the wind speed is 0.8 m/s; the operation mode is refrigeration; when the temperature is 24 ℃, the target data is { time period: 23: 00-6: 00; the wind speed is 0.8 m/s; the operation mode is refrigeration; the temperature is 24 ℃.
In a possible situation, some users may have poor physical fitness, for example, the elderly, children, and patients, if the sleep mode setting of the air conditioner is performed according to the customized data with the largest number of uses in the current region, the user may be awakened after entering sleep, which may affect the health of the user, and therefore, referring to fig. 6 on the basis of fig. 5, after sub-step S1202, step S120 further includes:
and a substep S1203, obtaining the custom operation data with the most use times under each custom operation data item in the custom operation data set to obtain a group of custom operation data with the most use times.
In this embodiment, the server 10 further prestores a custom operation data set corresponding to the terminal 20, where the custom operation data set includes custom operation data sent by the terminal 20, and the custom operation data is operation state data set by the user for the air conditioner through the terminal 20 when the air conditioner operates in the normal mode, and may include, but is not limited to, a wind speed (e.g., 0.8 to 1.6m/s), an operation mode (e.g., cooling and heating), a temperature (e.g., 26 to 28 ℃), and the like. After the normal mode setting is completed, the terminal 20 may send the custom operation data set by the user to the server 10, and the server 10 may store the custom operation data.
Meanwhile, the customized operation data set includes a plurality of customized operation data items, each customized operation data item includes at least one customized operation data, and the plurality of customized operation data items may include, but are not limited to, wind speed, operation mode, temperature, and the like, for example, referring to table 3, the customized operation data set is as follows:
TABLE 3 custom run dataset
| Wind speed | Mode of operation | Temperature of |
| 0.8m/s | Refrigeration system | 26℃ |
| 0.9m/s | Refrigeration system | 27℃ |
| 0.8m/s | Refrigeration system | 27℃ |
| 0.8m/s | Refrigeration system | 26℃ |
After receiving the custom operation data sent by the terminal 20, the server 10 puts each value in the custom operation data into each custom operation data item of the custom operation data set, for example, receives the custom operation data { wind speed: 0.8 m/s; the operation mode is refrigeration; and the temperature is 26 ℃, and all the values are put into all the custom operation data items of the custom operation data set.
After the server 10 obtains a group of custom operation data with the largest number of times of use as target data, a custom operation data set needs to be obtained, and the custom operation data with the largest number of times of use under each custom operation data item obtains a group of custom operation data with the largest number of times of use, for example, { wind speed: 0.8 m/s; the operation mode is refrigeration; temperature 26 ℃.
And a substep S1204 of generating reference data according to the set of the custom operation data with the largest number of use times.
In this embodiment, the reference data includes a set of custom operation data with the largest number of times of use, and time period data in the target data, for example, { time period: 23: 00-6: 00; the wind speed is 0.8 m/s; the operation mode is refrigeration; temperature 26 ℃.
In sub-step S1205, a difference between the reference data and the target data is calculated.
And a substep S1206, taking the reference data as the target data if the difference exceeds a preset range.
In this embodiment, if the difference between the reference data and the target data exceeds the preset range, it indicates that the difference between the operation state data set for the air conditioner by the user in the normal mode through the terminal 20 and a set of customized data with the largest number of times of use in the area where the user is currently located is large, that is, the set of customized data with the largest number of times of use in the area where the user is currently located cannot meet the user's requirement, and therefore, the reference data needs to be used as the target data at this time.
In one possible scenario, after determining the first customized data set corresponding to the target geographic location from the plurality of customized data sets, there may not be a group of customized data with the largest number of usage times in the first data set, for example, the number of usage times of each customized data under each customized data item is the same, so, referring to fig. 7 on the basis of fig. 5, after sub-step S1201, step S120 further includes:
and a substep S120-1 of judging whether a group of custom data with the largest number of use times exists in the first custom data set.
In this embodiment, if there is a group of the custom data with the largest number of times of use in the first custom data set, the substep S1202 is performed, and if there is no group of the custom data with the largest number of times of use in the first custom data set, the substeps S120-2 to S120-3 are performed.
And a substep S120-2 of determining a second custom data set from the plurality of custom data sets according to the target geographic position, wherein the distance between the geographic position corresponding to the second custom data set and the target geographic position is smaller than the distance between the geographic position corresponding to any other custom data set and the target geographic position.
In this embodiment, the environmental temperatures in two areas with geographical locations close to each other are usually not greatly different, so if a group of customized data with the largest number of usage times does not exist in the first customized data set, the customized data set closest to the target geographical location in the multiple customized data sets may be used as the second customized data set, for example, the target geographical location is a metropolis, and the # 2 customized data set corresponding to the Chongqing city is determined to be the second customized data set if the group of customized data with the largest number of usage times does not exist in the # 1 customized data set in Table 1.
And a substep S120-3 of obtaining the custom data with the largest number of times of use under each custom data item in the second custom data set to obtain a group of custom data with the largest number of times of use, and taking the group of custom data with the largest number of times of use as target data.
Similarly, in a possible situation, some users may be physically weak, for example, the elderly, children, patients, etc., and in order to ensure the health of the users, it is further necessary to determine whether the target data obtained currently can meet the requirements of the users, and therefore, referring to fig. 8 on the basis of fig. 7, after sub-step S120-3 or sub-step S1202, step S120 further includes:
and a substep S120-4 of obtaining the user-defined operation data with the maximum use times under each user-defined operation data item in the user-defined operation data set to obtain a group of user-defined operation data with the maximum use times.
And a substep S120-5 of generating reference data according to the set of the customized operation data with the maximum use times.
And a substep S120-6 of calculating a difference between the reference data and the target data.
And a substep S120-7 of taking the reference data as target data if the difference exceeds a preset range.
Compared with the prior art, the embodiment has the following beneficial effects:
firstly, when a user enters a setting interface of a sleep mode, a terminal 20 sends a sleep mode setting request to a server, the server 10 determines target data after receiving the request and feeds the target data back to the terminal 20, and the terminal 20 displays the target data, so that the user can complete the setting of the sleep mode only by selecting the target data;
secondly, the server 10 pre-stores a plurality of geographical positions and a custom data set corresponding to each geographical position, and the server finds out a group of custom data with the largest number of use times from the custom data set corresponding to the target geographical position as target data according to the target geographical position, so that the target data can improve the sleeping comfort of a user to the greatest extent, and improve the user experience;
thirdly, after the server 10 obtains a group of custom data with the largest number of usage times as the target data, it further determines whether the currently obtained target data can meet the requirements of the user according to the custom operation data set corresponding to the terminal 20, thereby ensuring the health of the user.
In order to perform the corresponding steps in the above embodiments and various possible embodiments, an implementation of the data recommendation device is given below. Fig. 9 is a schematic diagram of functional modules of the data recommendation device 100 according to the present invention. It should be noted that the basic principle and the technical effect of the data recommendation device 100 according to the embodiment of the present invention are the same as those of the foregoing method embodiment, and for a brief description, the corresponding contents of the foregoing method embodiment can be referred to for the parts not mentioned in the embodiment. The data recommendation device 100 is applied to the server 10, and the data recommendation device 100 is described below with reference to fig. 3 to 8, where the data recommendation device 100 includes: an obtaining module 110, a determining module 120 and a sending module 130.
The obtaining module 110 is configured to respond to a sleep mode setting request sent by a terminal, and obtain a target geographic location corresponding to the sleep mode setting request.
A determining module 120, configured to determine target data from the multiple custom data sets according to the target geographic location.
The sending module 130 is configured to feed back the target data to the terminal, so that the terminal displays the target data.
Optionally, the determining module 120 is further configured to: judging whether a target geographical position exists in a plurality of geographical positions stored in advance; if yes, determining target data from the plurality of user-defined data sets according to the target geographic position; if not, acquiring preset data, and taking the preset data as target data.
Optionally, the custom data set comprises a plurality of custom data items, each custom data item comprising at least one custom data; the determining module 120 performs a method of determining target data from a plurality of custom data sets according to the target geographic location, including:
according to the target geographic position, determining a first user-defined data set corresponding to the target geographic position from a plurality of user-defined data sets; and obtaining the custom data with the maximum use times under each custom data item in the first custom data set to obtain a group of custom data with the maximum use times, and taking the group of custom data with the maximum use times as target data.
Optionally, the determining module 120 performs a method of determining the target data from the plurality of custom data sets according to the target geographic location, and further includes:
judging whether a group of user-defined data with the largest number of use times exists in the first user-defined data set; if so, acquiring the custom data with the maximum use times under each custom data item in the first custom data set to obtain a group of custom data with the maximum use times, and taking the group of custom data with the maximum use times as target data; if not, determining a second user-defined data set from the plurality of user-defined data sets according to the target geographic position, wherein the distance between the geographic position corresponding to the second user-defined data set and the target geographic position is smaller than the distance between the geographic position corresponding to any one of the other user-defined data sets and the target geographic position; and obtaining the user-defined data with the maximum use times under each user-defined data item in the second user-defined data set to obtain a group of user-defined data with the maximum use times, and taking the group of user-defined data with the maximum use times as target data.
Optionally, the server 10 prestores a custom operation data set corresponding to the terminal 20, where the custom operation data set includes a plurality of custom operation data items, and each custom operation data item includes at least one piece of custom operation data; the determining module 120 performs a method of determining target data from a plurality of custom data sets according to the target geographic location, and further includes:
obtaining the user-defined operation data with the maximum use times under each user-defined operation data item in a user-defined operation data set to obtain a group of user-defined operation data with the maximum use times; generating reference data according to the set of user-defined operation data with the largest number of use times; calculating a difference between the reference data and the target data; and if the difference value exceeds a preset range, taking the reference data as target data.
In summary, the data recommendation method and apparatus, the server and the storage medium provided by the present invention are applied to a server, wherein the server is in communication connection with a terminal, and the server stores a plurality of geographic locations and a custom data set corresponding to each geographic location in advance; the data recommendation method comprises the following steps: responding to a sleep mode setting request sent by a terminal, and acquiring a target geographical position corresponding to the sleep mode setting request; determining target data from a plurality of user-defined data sets according to the target geographic position; and feeding back the target data to the terminal so that the terminal displays the target data. Compared with the prior art, the user can complete the setting of the sleep mode only by selecting the target data, and meanwhile, the target data can improve the sleep comfort level of the user to the maximum extent, and the user experience is improved.
Although the present invention is disclosed above, the present invention is not limited thereto. Various changes and modifications may be effected therein by one skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (10)
1. The data recommendation method is applied to a server (10), the server (10) is in communication connection with a terminal (20), and the server (10) stores a plurality of geographical positions and a custom data set corresponding to each geographical position in advance; the data recommendation method comprises the following steps:
responding to a sleep mode setting request sent by the terminal (20), and acquiring a target geographical position corresponding to the sleep mode setting request;
determining target data from the plurality of user-defined data sets according to the target geographic position;
feeding back the target data to the terminal (20) so as to enable the terminal (20) to display the target data.
2. The data recommendation method according to claim 1, wherein after the step of obtaining the target geographical location corresponding to the sleep mode setting request in response to the sleep mode setting request sent by the terminal (20), the data recommendation method further comprises:
judging whether the target geographical position exists in a plurality of prestored geographical positions;
if yes, executing the step of determining target data from the plurality of user-defined data sets according to the target geographic position;
if not, acquiring preset data, and taking the preset data as the target data.
3. The data recommendation method of claim 1, wherein the custom data set comprises a plurality of custom data items, each custom data item comprising at least one custom data;
the step of determining target data from the plurality of user-defined data sets according to the target geographic position comprises the following steps:
according to the target geographic position, determining a first user-defined data set corresponding to the target geographic position from the user-defined data sets;
and obtaining the user-defined data with the maximum use times under each user-defined data item in the first user-defined data set to obtain a group of user-defined data with the maximum use times, and taking the group of user-defined data with the maximum use times as the target data.
4. The data recommendation method of claim 3, wherein said step of determining target data from a plurality of said customized data sets according to said target geographic location further comprises:
judging whether a group of user-defined data with the largest number of use times exists in the first user-defined data set;
if so, executing the step of obtaining the user-defined data with the maximum use times in each user-defined data item in the first user-defined data set to obtain a group of user-defined data with the maximum use times, and taking the group of user-defined data with the maximum use times as the target data;
if not, determining a second user-defined data set from the user-defined data sets according to the target geographic position, wherein the distance between the geographic position corresponding to the second user-defined data set and the target geographic position is smaller than the distance between the geographic position corresponding to any other user-defined data set and the target geographic position;
and obtaining the user-defined data with the maximum use times under each user-defined data item in the second user-defined data set to obtain a group of user-defined data with the maximum use times, and taking the group of user-defined data with the maximum use times as the target data.
5. The data recommendation method according to claim 3 or 4, characterized in that the server (10) stores a customized operation data set corresponding to the terminal (20) in advance, the customized operation data set comprises a plurality of customized operation data items, and each customized operation data item comprises at least one customized operation data;
the step of determining target data from the plurality of user-defined data sets according to the target geographic position further includes:
obtaining the user-defined operation data with the maximum use times under each user-defined operation data item in the user-defined operation data set to obtain a group of user-defined operation data with the maximum use times;
generating reference data according to the set of user-defined operation data with the largest number of use times;
calculating a difference between the reference data and the target data;
and if the difference exceeds a preset range, taking the reference data as the target data.
6. The data recommendation method of claim 5, wherein the set of customized data with the most usage times comprises customized time data;
the step of generating the reference data according to the set of the customized operation data with the largest number of use times comprises the following steps:
and combining the group of the customized operation data with the maximum use times with the customized time data to obtain reference data.
7. The data recommendation device is applied to a server (10), the server (10) is in communication connection with a terminal (20), and the server (10) stores a plurality of geographical positions and custom data sets corresponding to the geographical positions in advance; the data recommendation apparatus (100) includes:
an obtaining module (110) configured to respond to a sleep mode setting request sent by the terminal (20) and obtain a target geographic location corresponding to the sleep mode setting request;
a determining module (120) configured to determine target data from the plurality of custom data sets according to the target geographic location;
a sending module (130) for feeding back the target data to the terminal (20) so as to enable the terminal (20) to display the target data.
8. The data recommendation device of claim 7, wherein the determining module (120) is further configured to:
judging whether the target geographical position exists in a plurality of prestored geographical positions;
if yes, executing the step of determining target data from the plurality of user-defined data sets according to the target geographic position;
if not, acquiring preset data, and taking the preset data as the target data.
9. A server, characterized in that the server (10) is communicatively connected to a terminal (20), the server (10) comprising:
one or more processors (11);
memory (12) for storing one or more programs which, when executed by the one or more processors (11), cause the one or more processors (11) to implement the data recommendation method of any one of claims 1-6.
10. A computer-readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor (11), carries out the data recommendation method according to any one of claims 1-6.
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