CN112735563A - Recommendation information generation method and device and processor - Google Patents
Recommendation information generation method and device and processor Download PDFInfo
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Abstract
The invention discloses a method, a device and a processor for generating recommendation information. Wherein, the method comprises the following steps: acquiring sleep statistical information of a target object, wherein the sleep statistical information is obtained by a plurality of sleep reports generated by a plurality of sleep monitoring applications, and the plurality of sleep monitoring applications are used for simultaneously collecting sleep records of the target object in a sleep process; generating a target sleep report according to the sleep statistical information; and analyzing the target sleep report to generate recommendation information, wherein the recommendation information is used for providing sleep advice for the target object. The invention solves the technical problem that the sleep advice recommended by the prior art based on a single sleep monitoring application is inaccurate.
Description
Technical Field
The invention relates to the field of data processing, in particular to a recommendation information generation method, a recommendation information generation device and a recommendation information generation processor.
Background
With the improvement of living standard, people pay more and more attention to body health. Currently, people monitor the health status of the body in real time through applications installed on terminal devices (e.g., mobile phones, smart bands, etc.).
Currently, the sleep monitoring function of the sleep monitoring application is becoming more sophisticated, and different sleep monitoring products monitor the sleep of a user through different sensors and metering methods to generate reports and sleep advice. However, different sleep monitoring applications have different sleep reports and sleep advice of different sleep monitoring applications due to different sensors and metering methods, different monitoring accuracy and different monitoring emphasis, and therefore the sleep reports and the sleep advice of the different sleep monitoring applications are different or even greatly different, and therefore, the sleep advice recommended by the single sleep monitoring application has the problem of inaccuracy. In addition, because there are differences between individuals of users, users cannot scientifically and effectively select sleep reports and suggestions generated by the sleep monitoring application.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the invention provides a method, a device and a processor for generating recommendation information, which aim to at least solve the technical problem that sleep suggestions recommended based on a single sleep monitoring application in the prior art are inaccurate.
According to an aspect of an embodiment of the present invention, a method for generating recommendation information is provided, including: acquiring sleep statistical information of a target object, wherein the sleep statistical information is obtained by a plurality of sleep reports generated by a plurality of sleep monitoring applications, and the plurality of sleep monitoring applications are used for simultaneously collecting sleep records of the target object in a sleep process; generating a target sleep report according to the sleep statistical information; and analyzing the target sleep report to generate recommendation information, wherein the recommendation information is used for providing sleep advice for the target object.
Further, the method for generating recommendation information further comprises: determining a plurality of target sleep monitoring applications according to the application score and/or the download number of each sleep monitoring application, and acquiring sleep statistic information from sleep reports generated by the target sleep monitoring applications; or responding to the selection instruction, determining a plurality of target sleep monitoring applications from the plurality of sleep monitoring applications according to the selection instruction, and acquiring sleep statistic information from sleep reports generated by the plurality of target sleep monitoring applications.
Further, the method for generating recommendation information further comprises: acquiring a weight value of each sleep monitoring application in a plurality of sleep monitoring applications under each sleep attribute according to the sleep statistical information; determining attribute parameters corresponding to each sleep attribute according to the weight values; and generating a target sleep report according to the attribute parameters corresponding to each sleep attribute.
Further, the method for generating recommendation information further comprises: acquiring a download number coefficient of each sleep monitoring application, an application scoring coefficient, an accuracy coefficient of a sleep report generated by each sleep monitoring application and an important coefficient of a current sleep attribute, wherein the important coefficient represents the importance degree of the current sleep attribute to the sleep report generated by each sleep monitoring application; calculating the sum of the download number coefficient, the application scoring coefficient, the accuracy coefficient and the important coefficient to obtain a first result; calculating the weight sum of all sleep monitoring applications to obtain a second result; and calculating the ratio of the first result to the second result to obtain the weight value of each sleep monitoring application under each sleep attribute.
Further, the method for generating recommendation information further comprises: acquiring a current weight value of each sleep monitoring application under a sleep state attribute; determining a sleep state corresponding to each sleep monitoring application at the current moment; determining a target sleep monitoring application with the largest current weight value from a plurality of sleep monitoring applications; determining that the sleep state corresponding to the target sleep monitoring application is the target sleep state corresponding to the current moment; and counting the sleep duration corresponding to each target sleep state.
Further, the method for generating recommendation information further comprises: and under the condition that a plurality of target sleep monitoring applications exist, determining a random sleep monitoring application from the target sleep monitoring applications based on a random selection mode, and determining that the sleep state corresponding to the random sleep monitoring application is the target sleep state corresponding to the current moment.
Further, the method for generating recommendation information further comprises: acquiring a target weight value of each sleep monitoring application under a target attribute; counting the occurrence times of target attributes of each sleep monitoring application within a preset time length; calculating the product of the current weight value and the frequency of each sleep monitoring application to obtain a third result; and calculating the sum of the third results of all the sleep monitoring applications to obtain a fourth result, wherein the fourth result represents the average occurrence frequency of the target attribute within the preset time length.
According to another aspect of the embodiments of the present invention, there is also provided a recommendation information generating apparatus, including: the sleep monitoring system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring sleep statistical information of a target object, the sleep statistical information is acquired by a plurality of sleep reports generated by a plurality of sleep monitoring applications, and the plurality of sleep monitoring applications are used for simultaneously acquiring sleep records of the target object in a sleep process; the first generation module is used for generating a target sleep report according to the sleep statistical information; and the second generation module is used for analyzing the target sleep report and generating recommendation information, wherein the recommendation information is used for providing sleep advice for the target object.
According to another aspect of the embodiments of the present invention, there is also provided a non-volatile storage medium having a computer program stored therein, wherein the computer program is configured to execute the above-mentioned recommendation information generation method when running.
According to another aspect of the embodiments of the present invention, there is also provided a processor for executing a program, wherein the program is configured to execute the above-mentioned recommendation information generation method when running.
In the embodiment of the invention, a mode of analyzing sleep reports generated by different sleep monitoring applications is adopted, after sleep statistical information of a target object is obtained, the target sleep report is generated according to the sleep statistical information, the target sleep report is analyzed, and recommendation information is generated, wherein the sleep statistical information is obtained by a plurality of sleep reports generated by a plurality of sleep monitoring applications, the plurality of sleep monitoring applications are used for simultaneously collecting sleep records of the target object in a sleep process, and the recommendation information is used for providing sleep suggestions for the target object.
In the process, the sleep statistical information of the sleep reports is analyzed, the sleep advice is provided for the user according to the analysis result, and the process considers the sleep statistical results corresponding to different sleep monitoring applications, so that the finally obtained recommended information is more scientific and more suitable for the user, and the problem that the sleep advice recommendation is inaccurate or not suitable for the user due to different sensors, different metering modes, different measurement precision, different measurement focus points and other factors of a single sleep monitoring application is solved.
Therefore, the purpose of improving the accuracy of the sleep advice is achieved by the scheme provided by the application, the technical effect of providing the accurate sleep advice for the user is achieved, and the technical problem that the sleep advice recommended based on the single sleep monitoring application in the prior art is inaccurate is solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
fig. 1 is a flowchart of a method of generating recommendation information according to an embodiment of the present invention;
FIG. 2 is a flow chart of an alternative recommendation information generation method according to an embodiment of the present invention;
FIG. 3 is a flow chart of an alternative recommendation information generation method according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a recommendation information generation apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, 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 only a part of the embodiments of the present invention, and not all of the embodiments. 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 the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1
In accordance with an embodiment of the present invention, there is provided an embodiment of a method for generating recommendation information, it should be noted that the steps illustrated in the flowchart of the drawings may be performed in a computer system such as a set of computer executable instructions, and that while a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than here.
Fig. 1 is a flowchart of a method for generating recommendation information according to an embodiment of the present invention, as shown in fig. 1, the method includes the following steps:
step S102, acquiring sleep statistic information of the target object, wherein the sleep statistic information is acquired by a plurality of sleep reports generated by a plurality of sleep monitoring applications, and the plurality of sleep monitoring applications are used for simultaneously collecting sleep records of the target object in a sleep process.
In step S102, the sleep monitoring apparatus may serve as an execution subject of the method provided in this embodiment.
In an optional embodiment, a plurality of sleep monitoring applications may be installed in the sleep monitoring device, during a process of sleeping of a user (i.e., a target object), the plurality of sleep monitoring applications run simultaneously to monitor the sleep of the user and generate a sleep report, and the sleep monitoring device performs statistics on sleep information in each sleep report to obtain sleep statistical information.
In another alternative embodiment, multiple sleep monitoring applications may be installed on different terminal devices, for example, the sleep monitoring application a is installed on a mobile phone, the sleep monitoring application B is installed on a smart band, and the sleep monitoring application C is installed on a smart tablet. In the sleeping process of a user, a plurality of terminal devices start corresponding sleep monitoring applications to monitor the sleep of the user and generate a sleep report. After the sleep reports are generated, the plurality of terminal devices communicate with the sleep monitoring device and send the respective generated sleep reports to the sleep monitoring device, so that the sleep monitoring device counts the sleep information in each sleep report to obtain sleep statistical information.
And step S104, generating a target sleep report according to the sleep statistical information.
Optionally, the sleep statistics include, but are not limited to, sleep time, wake time, time to fall asleep, sleep time, deep sleep time, REM (Rapid eye Movement) time, light sleep time, body Movement times, number of bed exits, average breathing rate, and average heart rate. After the sleep statistical information is obtained, the sleep monitoring device performs statistics on the obtained sleep statistical information to generate a target sleep report, wherein the sleep monitoring device may further generate a chart according to the sleep statistical information, for example, draw a heart rate chart, a respiration chart, a sleep state report chart, and the like.
And step S106, analyzing the target sleep report to generate recommendation information, wherein the recommendation information is used for providing sleep advice for the target object.
In step S106, in the process of analyzing the target sleep report, object information of the target object, for example, information such as age, weight, and sleeping habits of the target object, may be added, that is, the target sleep report and the object information of the target object are analyzed to generate recommendation information. It is easy to notice that the object information of the target object is considered, so that the finally generated recommendation information is more adaptive to the target object, and the sleep advice is more suitable for the target object, thereby improving the user experience of the target object.
Optionally, fig. 2 is a flowchart illustrating an optional method for generating recommendation information, and in fig. 2, a user may input object information such as age, weight, sleep habit, and the like through a sleep monitoring device and select at least two sleep monitoring applications. After the sleep monitoring device generates a target sleep report according to the sleep reports generated by at least two sleep monitoring applications, the target sleep report is combined with object information such as age, weight, sleep habits and the like input by a user, and recommendation information is generated through analysis of a sleep suggestion library (or other recommendation systems) so as to give reasonable sleep suggestions to the user.
Based on the schemes defined in steps S102 to S106, it can be known that, in the embodiment of the present invention, a sleep report generated by different sleep monitoring applications is analyzed, after sleep statistical information of a target object is obtained, a target sleep report is generated according to the sleep statistical information, and the target sleep report is analyzed to generate recommendation information, where the sleep statistical information is obtained by a plurality of sleep reports generated by a plurality of sleep monitoring applications, the plurality of sleep monitoring applications are configured to simultaneously collect sleep records of the target object during a sleep process, and the recommendation information is configured to provide a sleep recommendation for the target object.
It is easy to note that in the above process, the sleep statistical information of multiple sleep reports is analyzed, and a sleep advice is provided to the user according to the analysis result, and because the process takes into account the sleep statistical results corresponding to different sleep monitoring applications, the finally obtained recommendation information is more scientific and more suitable for the user, and the problem that the sleep advice recommendation is inaccurate or not suitable for the user due to different sensors, different metering modes, different measurement precisions, different measurement emphasis points and other factors of a single sleep monitoring application is avoided.
Therefore, the purpose of improving the accuracy of the sleep advice is achieved by the scheme provided by the application, the technical effect of providing the accurate sleep advice for the user is achieved, and the technical problem that the sleep advice recommended based on the single sleep monitoring application in the prior art is inaccurate is solved.
In an alternative embodiment, fig. 3 shows a flowchart of an alternative recommendation information generation method, and in fig. 3, the sleep monitoring device integrates the features of the sleep monitoring applications for selection by the user. When a user enters a sleep state, the sleep monitoring equipment starts all preselected sleep monitoring applications, after the user finishes sleeping, each sleep monitoring application outputs a corresponding sleep report, and the sleep monitoring equipment performs unified report collection and analysis and integrates to generate a final target sleep report.
According to the above process, before acquiring the sleep statistic information of the target object, the user needs to select the sleep monitoring application for performing sleep monitoring. Optionally, the sleep monitoring application may be selected in any one of the following manners, so that the sleep monitoring application monitors the sleep of the user to obtain the sleep statistical information.
The first method is as follows: the sleep monitoring device determines a plurality of target sleep monitoring applications according to the application score and/or the download number of each sleep monitoring application, and acquires sleep statistic information from sleep reports generated by the plurality of target sleep monitoring applications.
In this manner, the sleep monitoring device counts application scores and/or download numbers of each sleep monitoring application, ranks the sleep monitoring applications according to the application scores and/or download numbers, selects a sleep monitoring application ranked at the top as a target sleep monitoring application from the sleep monitoring applications, for example, selects 5 types of applications with the application scores and download numbers ranked at the top as the target sleep monitoring applications, and then acquires sleep statistics information from sleep reports generated by the target sleep monitoring applications.
The second method comprises the following steps: the sleep monitoring device responds to the selection instruction, determines a plurality of target sleep monitoring applications from the plurality of sleep monitoring applications according to the selection instruction, and acquires sleep statistic information from sleep reports generated by the plurality of target sleep monitoring applications.
In this approach, the user selects a target sleep monitoring application by sending a selection instruction to the sleep monitoring device. The sleep monitoring device integrates and summarizes the sleep monitoring applications mainstream in each software market, including but not limited to the downloading times of the applications, the number of commonly used users, the comprehensive rating of the software, the monitoring method of the software, the monitoring direction of the software and the like, and lists the applications to the users so that the users can select the cooperative sleep monitoring software.
In an optional embodiment, after the sleep statistical information is obtained, the sleep monitoring device obtains, according to the sleep statistical information, a weight value of each sleep monitoring application of the multiple sleep monitoring applications under each sleep attribute, determines an attribute parameter corresponding to each sleep attribute according to the weight value, and then generates a target sleep report according to the attribute parameter corresponding to each sleep attribute.
It should be noted that different sleep monitoring applications may monitor the same sleep attribute of the user, for example, the sleep monitoring application a and the sleep monitoring application B simultaneously monitor the heart rate of the user during the sleep process. However, the importance degree of the same sleep attribute in sleep reports generated by different sleep monitoring applications is different, so that more accurate recommendation information can be obtained by determining the weight value of each sleep attribute under different sleep monitoring applications, further determining the attribute parameter of the sleep attribute in the target sleep report, and generating the target sleep report based on the attribute parameter.
In an alternative embodiment, the sleep monitoring device obtains a download number coefficient of each sleep monitoring application, an application scoring coefficient, an accuracy coefficient of a sleep report generated by each sleep monitoring application, and an importance coefficient of a current sleep attribute, then calculates a sum of the download number coefficient, the application scoring coefficient, the accuracy coefficient, and the importance coefficient to obtain a first result, calculates a weighted sum of all the sleep monitoring applications to obtain a second result, and finally calculates a ratio of the first result to the second result to obtain a weighted value of each sleep monitoring application under each sleep attribute. Wherein the importance factor characterizes how important the current sleep attribute is to the sleep report generated by each sleep monitoring application.
Optionally, the weight value of the current sleep monitoring application under the current sleep attribute may be represented by the following formula:
in the above equation, p is a weight value of the current sleep monitoring application under the current sleep attribute; s is a weight sum corresponding to the current sleep monitoring application, namely a first result; s is the sum of the weights of all sleep monitoring applications participating in sleep monitoring, i.e. the second result.
Wherein the first result s satisfies the following equation:
s＝i+j+k+l
in the above formula, i is a download number coefficient of the current sleep monitoring application, j is an application scoring coefficient of the current sleep monitoring application, l is an accuracy coefficient corresponding to the current sleep monitoring application, and k is an important coefficient of the current sleep monitoring application, for example, the heart rate, the body movement, the getting out of bed and the sleep state attribute are sleep attributes to be monitored mainly by the sleep monitoring application corresponding to the smart band, and therefore, the numerical values corresponding to the important coefficients corresponding to the heart rate, the body movement, the getting out of bed and the sleep state attribute are large; the respiration frequency and the sleep state are sleep attributes to be monitored in a focused manner by the sleep monitoring application with the audio acquisition function, so that the numerical values corresponding to the important coefficients corresponding to the respiration frequency and the sleep state are large.
The second result S satisfies the following equation:
S＝s1+s2+…+sn
in the above equation, s1, s2, sn represent the sum of the weights of all sleep attributes corresponding to different sleep monitoring applications.
In an optional embodiment, after obtaining the weight value corresponding to each sleep monitoring application under each sleep attribute, for the case where the parameter value corresponding to the sleep attribute is determined by the time point, the sleep monitoring device performs two-classification and multi-classification by using the weight of each sleep monitoring application. Specifically, the sleep monitoring device first obtains a current weight value of each sleep monitoring application under the attribute of the sleep state, determines the sleep state corresponding to each sleep monitoring application at the current moment, then determines a target sleep monitoring application with the largest current weight value from the multiple sleep monitoring applications, determines the sleep state corresponding to the target sleep monitoring application as a target sleep state corresponding to the current moment, and finally counts the sleep duration corresponding to each target sleep state.
Optionally, for the attribute of the sleep state, the attribute parameter may be determined by monitoring the sleep state of the user at a certain time, where the attribute parameter is a sleep duration. For example, the sleep monitor application A, B, C, D, E detects the sleep attributes corresponding to the user at the current time, respectively, where the sleep monitor application A, B determines that the sleep state is a deep sleep state, the sleep monitor application C, D determines that the sleep state is a light sleep state, and the sleep monitor application E determines that the sleep state is an REM state, then:
Pdeep to＝PA+PB
PShallow＝PC+PD
Prem＝PE
P＝max[PDeep to，PShallow，Prem]
In the above formula, PDeep toWeight, P, corresponding to the deep sleep stateShallowWeight, P, corresponding to light sleep stateremWeight, P, corresponding to the state of REMA、PB、PC、PDAnd PERespectively representing the corresponding weights of different sleep monitoring applications under the attribute of the sleep state, wherein P is PDeep to、PShallowAnd PremThe largest weight in (1).
If two or more sleep state attributes are weighted equally, then the sleep state is determined using the principle of the largest single weight, e.g., PDeep to＝PShallowAnd, max [ PA，PB，PC，PD]＝PAThen due to PDeep toFrom PAIs determined, moreover, PAIs [ P ]A，PB，PC，PD]Therefore, the sleep state corresponding to the current time is the deep sleep state.
Optionally, when there are multiple target sleep monitoring applications, the random sleep monitoring application is determined from the multiple target sleep monitoring applications based on a random selection manner, and a sleep state corresponding to the random sleep monitoring application is determined as a target sleep state corresponding to the current time. That is, if there are multiple maximum weights, the sleep state corresponding to the maximum weight at the current time is randomly selected as the sleep state corresponding to the current time, for example, PA＝PCAnd is [ PA，PB，PC，PD]And determining the sleep state corresponding to the current moment to be a deep sleep state or a light sleep state in a randomly selected mode.
By the mode, the sleep monitoring application further draws the sleep state report chart and obtains corresponding data of sleep time, wake-up time, sleep time, deep sleep time, REM time, light sleep time and the like.
In an alternative embodiment, the sleep attribute for the statistics of times may be determined by means of a weighted average. Specifically, the sleep monitoring device first obtains a target weight value of each sleep monitoring application under a target attribute, then counts the number of times that the target attribute appears in a preset time length of each sleep monitoring application, calculates the product of the current weight value and the number of times of each sleep monitoring application to obtain a third result, and finally calculates the sum of the third results of all sleep monitoring applications to obtain a fourth result, wherein the fourth result represents the average number of times that the target attribute appears in the preset time length.
Optionally, for the average heart rate within the preset time duration, the sleep monitor application A, B, C, D, E determines that the average heart rate corresponding to the preset time duration is a, b, c, d, e, respectively, then
In the above-mentioned formula, the compound of formula,
average heart rate for a predetermined duration, PA、PB、PC、PDAnd PERespectively representing the corresponding weights of different sleep monitoring applications under the heart rate attribute.
It should be noted that, in addition to calculating the average heart rate attribute, the method can also calculate the body movement, bed leaving, respiration and heart rate times in different time periods, so as to obtain the total body movement, bed leaving times, average respiration and heart rate times, and draw corresponding graphs.
According to the scheme, the sleep reports of different sleep monitoring applications are compared, scientific and comprehensive target sleep reports and recommended sleep suggestions are generated in an integrated mode, the problem that the sleep reports and the recommended sleep suggestions are inaccurate or not suitable for users due to the fact that a single sleep monitoring application is different in sensors, different in metering methods, different in measurement accuracy, different in measurement emphasis and the like is solved, the generated recommendation information is more scientific and comprehensive, and the user can sleep scientifically and healthily.
Example 2
According to an embodiment of the present invention, there is further provided an embodiment of a device for generating recommendation information, where fig. 4 is a schematic diagram of the device for generating recommendation information according to the embodiment of the present invention, and as shown in fig. 4, the device includes the following steps: an acquisition module 401, a first generation module 403, and a second generation module 405.
The acquiring module 401 is configured to acquire sleep statistics information of a target object, where the sleep statistics information is acquired by multiple sleep reports generated by multiple sleep monitoring applications, and the multiple sleep monitoring applications are configured to simultaneously acquire sleep records of the target object during a sleep process; a first generating module 403, configured to generate a target sleep report according to the sleep statistic information; a second generating module 405, configured to analyze the target sleep report and generate recommendation information, where the recommendation information is used to provide a sleep recommendation to the target object.
Optionally, the obtaining module includes: the device comprises a first determination module and a second determination module. The first determining module is used for determining a plurality of target sleep monitoring applications according to the application score and/or the download number of each sleep monitoring application and acquiring sleep statistic information from sleep reports generated by the target sleep monitoring applications; and the second determining module is used for responding to the selection instruction, determining a plurality of target sleep monitoring applications from the plurality of sleep monitoring applications according to the selection instruction, and acquiring sleep statistic information from sleep reports generated by the plurality of target sleep monitoring applications.
Optionally, the first generating module includes: the device comprises a first obtaining module, a third determining module and a third generating module. The first obtaining module is used for obtaining a weight value of each sleep monitoring application in the plurality of sleep monitoring applications under each sleep attribute according to the sleep statistic information; the third determining module is used for determining attribute parameters corresponding to each sleep attribute according to the weight values; and the third generation module is used for generating a target sleep report according to the attribute parameters corresponding to each sleep attribute.
Optionally, the first obtaining module includes: the device comprises a second acquisition module, a first calculation module, a second calculation module and a third calculation module. The second obtaining module is used for obtaining a download quantity coefficient of each sleep monitoring application, an application scoring coefficient, an accuracy coefficient of a sleep report generated by each sleep monitoring application and an important coefficient of a current sleep attribute, wherein the important coefficient represents the importance degree of the current sleep attribute to the sleep report generated by each sleep monitoring application; the first calculation module is used for calculating the sum of the download number coefficient, the application scoring coefficient, the accuracy coefficient and the important coefficient to obtain a first result; the second calculation module is used for calculating the weight sum of all the sleep monitoring applications to obtain a second result; and the third calculating module is used for calculating the ratio of the first result to the second result to obtain the weight value of each sleep monitoring application under each sleep attribute.
Optionally, the third determining module includes: the device comprises a third obtaining module, a fourth determining module, a fifth determining module, a sixth determining module and a first counting module. The third obtaining module is used for obtaining a current weight value of each sleep monitoring application under the attribute of the sleep state; the fourth determining module is used for determining the sleep state corresponding to each sleep monitoring application at the current moment; a fifth determining module, configured to determine, from the multiple sleep monitoring applications, a target sleep monitoring application with a largest current weight value; a sixth determining module, configured to determine that the sleep state corresponding to the target sleep monitoring application is the target sleep state corresponding to the current time; and the first statistic module is used for counting the sleep duration corresponding to each target sleep state.
Optionally, the apparatus for generating recommendation information further includes: and the seventh determining module is used for determining the random sleep monitoring application from the target sleep monitoring applications based on the random selection mode under the condition that the target sleep monitoring applications are multiple, and determining the sleep state corresponding to the random sleep monitoring application as the target sleep state corresponding to the current moment.
Optionally, the third determining module includes: the device comprises a fourth acquisition module, a second statistic module, a fourth calculation module and a fifth calculation module. The fourth obtaining module is used for obtaining a target weight value of each sleep monitoring application under a target attribute; the second counting module is used for counting the frequency of occurrence of the target attribute of each sleep monitoring application within a preset time length; the fourth calculation module is used for calculating the product of the current weight value and the frequency of each sleep monitoring application to obtain a third result; and the fifth calculation module is used for calculating the sum of the third results of all the sleep monitoring applications to obtain a fourth result, wherein the fourth result represents the average times of the target attributes appearing in the preset time length.
Example 3
According to another aspect of the embodiments of the present invention, there is also provided a nonvolatile storage medium having a computer program stored therein, wherein the computer program is configured to execute the method for generating recommendation information in embodiment 1 described above when running.
Example 4
According to another aspect of the embodiments of the present invention, there is also provided a processor for executing a program, wherein the program is configured to execute the method for generating recommendation information in embodiment 1 when running.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (10)
1. A method for generating recommendation information, comprising:
acquiring sleep statistical information of a target object, wherein the sleep statistical information is obtained by a plurality of sleep reports generated by a plurality of sleep monitoring applications, and the plurality of sleep monitoring applications are used for simultaneously collecting sleep records of the target object in a sleep process;
generating a target sleep report according to the sleep statistical information;
analyzing the target sleep report and generating recommendation information, wherein the recommendation information is used for providing sleep advice to the target object.
2. The method of claim 1, wherein obtaining sleep statistics of the target subject comprises:
determining a plurality of target sleep monitoring applications according to the application score and/or the download number of each sleep monitoring application, and acquiring the sleep statistical information from sleep reports generated by the target sleep monitoring applications; alternatively, the first and second electrodes may be,
responding to a selection instruction, determining the target sleep monitoring applications from the sleep monitoring applications according to the selection instruction, and acquiring the sleep statistic information from sleep reports generated by the target sleep monitoring applications.
3. The method of claim 1, wherein generating a target sleep report based on the sleep statistics comprises:
acquiring a weight value of each sleep monitoring application in the plurality of sleep monitoring applications under each sleep attribute according to the sleep statistical information;
determining attribute parameters corresponding to each sleep attribute according to the weight values;
and generating the target sleep report according to the attribute parameters corresponding to each sleep attribute.
4. The method of claim 3, wherein obtaining a weight value for each sleep monitoring application of the plurality of sleep monitoring applications under each sleep attribute according to the sleep statistics comprises:
acquiring a download number coefficient of each sleep monitoring application, an application scoring coefficient, an accuracy coefficient of a sleep report generated by each sleep monitoring application and an important coefficient of a current sleep attribute, wherein the important coefficient represents the importance degree of the current sleep attribute to the sleep report generated by each sleep monitoring application;
calculating the sum of the download number coefficient, the application scoring coefficient, the accuracy coefficient and the importance coefficient to obtain a first result;
calculating the weight sum of all sleep monitoring applications to obtain a second result;
and calculating the ratio of the first result to the second result to obtain the weight value of each sleep monitoring application under each sleep attribute.
5. The method of claim 3, wherein determining the attribute parameter corresponding to each sleep attribute according to the weight value comprises:
acquiring a current weight value of each sleep monitoring application under a sleep state attribute;
determining a sleep state corresponding to each sleep monitoring application at the current moment;
determining a target sleep monitoring application with the largest current weight value from the plurality of sleep monitoring applications;
determining that the sleep state corresponding to the target sleep monitoring application is the target sleep state corresponding to the current moment;
and counting the sleep duration corresponding to each target sleep state.
6. The method of claim 5, further comprising:
and under the condition that a plurality of target sleep monitoring applications exist, determining a random sleep monitoring application from the target sleep monitoring applications based on a random selection mode, and determining that the sleep state corresponding to the random sleep monitoring application is the target sleep state corresponding to the current moment.
7. The method of claim 3, wherein determining the attribute parameter corresponding to each sleep attribute according to the weight value comprises:
acquiring a target weight value of each sleep monitoring application under a target attribute;
counting the occurrence times of the target attribute of each sleep monitoring application within a preset time length;
calculating the product of the current weight value of each sleep monitoring application and the times to obtain a third result;
and calculating the sum of the third results of all the sleep monitoring applications to obtain a fourth result, wherein the fourth result represents the average occurrence frequency of the target attribute in the preset time length.
8. An apparatus for generating recommendation information, comprising:
the sleep monitoring system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring sleep statistical information of a target object, the sleep statistical information is acquired by a plurality of sleep reports generated by a plurality of sleep monitoring applications, and the plurality of sleep monitoring applications are used for simultaneously acquiring sleep records of the target object in a sleep process;
the first generation module is used for generating a target sleep report according to the sleep statistical information;
and the second generation module is used for analyzing the target sleep report and generating recommendation information, wherein the recommendation information is used for providing sleep advice for the target object.
9. A non-volatile storage medium, wherein a computer program is stored in the non-volatile storage medium, wherein the computer program is configured to execute the method for generating recommendation information according to any one of claims 1 to 7 when running.
10. A processor for running a program, wherein the program is configured to execute the method for generating recommendation information according to any one of claims 1 to 7.
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