CN113761340A - Information recommendation method and device, electronic equipment and computer readable medium - Google Patents
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Abstract
The embodiment of the disclosure discloses an information recommendation method, an information recommendation device, electronic equipment and a computer readable medium. One embodiment of the method comprises: acquiring at least one detection result of each detection item in each detection item related to a target user; generating detection information of a preset storage structure according to at least one detection result of each detection item in each detection item; determining whether to diagnose each detection item in the detection information; responding to diagnosis of all detection items, and determining at least one detection item with abnormal detection results in all detection items and at least one department corresponding to each detection item with abnormal detection results; and recommending the related information of at least one target diagnosis person for showing to the target user. The embodiment recommends the relevant target diagnostician by generating a detection item in which the detection result is abnormal among the detection information of the predetermined storage structure.
Description
Technical Field
The embodiment of the disclosure relates to the technical field of computers, in particular to an information recommendation method, an information recommendation device, electronic equipment and a computer readable medium.
Background
Currently, each health-related platform generally supports users to subscribe to detection services (e.g., physical examination, home detection, genetic detection) online to generate reports. After the user finishes the detection, the report is uploaded to the system by offline workers. The system supports the user to view and recommend the relevant doctor to perform report interpretation/analysis on line. The commonly used approach is: reports in a Document format such as PDF (Portable Document format) are often used to show users, and support users to send the entire report to doctors for interpretation. The above approaches often have the following problems: at present, a report in a document format can not show each specific condition in a report of a user, and only a general practitioner can make a detailed diagnosis, but can not make a preliminary diagnosis for the user.
Disclosure of Invention
This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.
Some embodiments of the present disclosure propose information recommendation methods, apparatuses, devices and computer readable media to solve the technical problems mentioned in the background section above.
In a first aspect, some embodiments of the present disclosure provide an information recommendation method, including: acquiring at least one detection result of each detection item in each detection item related to a target user, wherein each detection item corresponds to at least one department, and each department corresponds to at least one diagnostic person; generating detection information of a preset storage structure according to at least one detection result of each detection item in the detection items, wherein the preset storage structure represents the association relationship among departments, the detection items and the detection results; determining whether to diagnose each detection item in the detection information; responding to the diagnosis of the detection items, and determining at least one detection item with abnormal detection result in the detection items and at least one department corresponding to the detection item with abnormal detection result; and recommending relevant information of at least one target diagnosis person to be displayed to the target user according to at least one department corresponding to the detection item with abnormal detection result.
Optionally, the generating detection information of a predetermined storage structure according to at least one detection result of each detection item in the detection items includes: and generating detection information of a preset storage structure associated with the target user according to at least one detection result of each detection item in the detection items and the user information of the target user.
Optionally, after generating the detection information of the predetermined storage structure according to at least one detection result of each detection item in the detection items, the method further includes: and responding to the viewing instruction of the target user, and adjusting the layout of each detection item of the detection information and at least one detection result of each detection item according to the abnormal detection result in at least one detection result of each detection item in each detection item to obtain the adjusted detection information.
Optionally, the type of the detection result includes at least one of the following: numerical type, image type, and text type; and the detection result with abnormality in at least one detection result of each detection item is determined by the following steps: in response to determining that a detection result of a numerical type exists in at least one detection result of each detection item, determining whether the detection result of the numerical type is abnormal through numerical comparison; and in response to determining that the detection result of the image type and/or the character type exists in at least one detection result of each detection item, determining whether the detection result of the image type and/or the character type is abnormal or not through semantic analysis.
Optionally, after generating the detection information with a predetermined storage structure according to at least one detection result of each detection item in the detection items, the method further includes: responding to a detection information screening instruction of the target user, and determining at least one detection item selected by the target user in the detection information; and generating the screened detection information according to the at least one detection item selected by the target user and the user information of the target user.
Optionally, after generating the detection information with a predetermined storage structure according to at least one detection result of each detection item in the detection items, the method further includes: responding to a detection information merging instruction of the target user, and determining whether the target user has historical detection information; and in response to the existence of the history detection information by the target user, writing at least one detection result of each detection item selected by the target user in the history detection information into the detection information, and obtaining the written detection information as detection information.
Optionally, the recommending, according to at least one department corresponding to the detection item with the abnormal detection result, the relevant information of at least one target diagnosis person to be displayed to the target user includes: according to at least one department corresponding to the detection item with abnormal detection result, distributing corresponding weight to each department in the detection information; according to the weight distributed to each department in each department, distributing corresponding weight to each diagnostician in each diagnostician corresponding to each department; and recommending relevant information of at least one target diagnostician related to the detection item with abnormal detection results according to the weight distributed to each diagnostician in the diagnosticians so as to display the relevant information to the target user.
In a second aspect, some embodiments of the present disclosure provide an information recommendation apparatus, including: the system comprises an acquisition unit, a judging unit and a judging unit, wherein the acquisition unit is configured to acquire at least one detection result of each detection item in each detection item related to a target user, each detection item corresponds to at least one department, and each department corresponds to at least one diagnostic person; the generating unit is configured to generate detection information of a preset storage structure according to at least one detection result of each detection item in the detection items, wherein the preset storage structure represents the association relationship among departments, the detection items and the detection results; a first determination unit configured to determine whether or not to diagnose each detection item in the detection information; a second determining unit configured to determine, in response to the diagnosis of the respective detection items, at least one detection item in which an abnormality exists in at least one detection result among the respective detection items and at least one department corresponding to each detection item in which an abnormality exists in the detection result; and the recommending unit is configured to recommend the relevant information of at least one target diagnosis person to be displayed to the target user according to at least one department corresponding to the detection item with the abnormal detection result.
Optionally, the generating unit is further configured to: and generating detection information of a preset storage structure associated with the target user according to at least one detection result of each detection item in the detection items and the user information of the target user.
Optionally, the apparatus further comprises: and responding to the viewing instruction of the target user, and adjusting the layout of each detection item of the detection information and at least one detection result of each detection item according to the abnormal detection result in at least one detection result of each detection item in each detection item to obtain the adjusted detection information.
Optionally, the type of the detection result includes at least one of the following: numerical type, image type, and text type; and the detection result with abnormality in at least one detection result of each detection item is determined by the following steps: in response to determining that a detection result of a numerical type exists in at least one detection result of each detection item, determining whether the detection result of the numerical type is abnormal through numerical comparison; and in response to determining that the detection result of the image type and/or the character type exists in at least one detection result of each detection item, determining whether the detection result of the image type and/or the character type is abnormal or not through semantic analysis.
Optionally, the apparatus further comprises: responding to a detection information screening instruction of the target user, and determining at least one detection item selected by the target user in the detection information; and generating the screened detection information according to the at least one detection item selected by the target user and the user information of the target user.
Optionally, the apparatus further comprises: responding to a detection information merging instruction of the target user, and determining whether the target user has historical detection information; and in response to the existence of the history detection information by the target user, writing at least one detection result of each detection item selected by the target user in the history detection information into the detection information, and obtaining the written detection information as detection information.
Optionally, the recommending unit is further configured to: according to at least one department corresponding to the detection item with abnormal detection result, distributing corresponding weight to each department in the detection information; according to the weight distributed to each department in each department, distributing corresponding weight to each diagnostician in each diagnostician corresponding to each department; and recommending relevant information of at least one target diagnostician related to the detection item with abnormal detection results according to the weight distributed to each diagnostician in the diagnosticians so as to display the relevant information to the target user.
In a third aspect, some embodiments of the present disclosure provide an electronic device, comprising: one or more processors; a storage device having one or more programs stored thereon which, when executed by one or more processors, cause the one or more processors to implement a method as in any one of the first aspects.
In a fourth aspect, some embodiments of the disclosure provide a computer readable medium having a computer program stored thereon, wherein the program when executed by a processor implements a method as in any one of the first aspect.
The above embodiments of the present disclosure have the following beneficial effects: the information recommendation method of some embodiments of the present disclosure may recommend the relevant target diagnosis person by generating a detection item in which the detection result is abnormal in the detection information of the predetermined storage structure. Specifically, the current report in the document format can only be handed to a general practitioner to perform detailed diagnosis because the specific conditions in the report of the user cannot be displayed, and cannot perform preliminary diagnosis for the user. Based on this, the information recommendation method of some embodiments of the present disclosure may first obtain at least one detection result of each detection item in the respective detection items, which is related to the target user. Each detection item corresponds to at least one department, and each department corresponds to at least one diagnostic person. Then, detection information of a predetermined storage structure is generated according to at least one detection result of each detection item in the detection items. The preset storage structure represents the association relation among departments, detection items and detection results. The detection information can simply and clearly provide the detection information of the target user, the corresponding department information and the diagnosis personnel information to the target user, and the detection experience of the user is greatly improved. Then, it is determined whether or not each detection item in the detection information is diagnosed. And responding to the diagnosis of the detection items, and determining at least one department corresponding to the detection item with abnormal detection result in at least one detection item and each detection item with abnormal detection result in the detection items. Therefore, the relevant diagnosis personnel information is provided for the target user in a more targeted and subsequent mode. And finally, recommending the related information of at least one target diagnosis person to be displayed to the target user according to at least one department corresponding to the detection item with the abnormal detection result. Therefore, the information recommendation method can recommend the relevant target diagnostician by generating the detection item with the abnormal detection result in the detection information of the preset storage structure.
Drawings
The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numbers refer to the same or similar elements. It should be understood that the drawings are schematic and that elements and features are not necessarily drawn to scale.
Fig. 1 is a schematic diagram of an application scenario of an information recommendation method according to some embodiments of the present disclosure;
FIG. 2 is a flow diagram of some embodiments of an information recommendation method according to the present disclosure;
FIG. 3 is a schematic illustration of detected information of a predetermined storage structure associated with a target user in an information recommendation method according to some embodiments of the present disclosure;
FIG. 4 is a schematic illustration of filtered detection information in an information recommendation method according to some embodiments of the present disclosure;
fig. 5 is a schematic diagram of the detection information after writing in the information recommendation method according to some embodiments of the present disclosure;
FIG. 6 is a flow diagram of further embodiments of an information recommendation method according to the present disclosure;
FIG. 7 is a schematic block diagram of some embodiments of an information recommendation device according to the present disclosure;
FIG. 8 is a schematic structural diagram of an electronic device suitable for use in implementing some embodiments of the present disclosure.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.
It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings. The embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict.
It should be noted that the terms "first", "second", and the like in the present disclosure are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence relationship of the functions performed by the devices, modules or units.
It is noted that references to "a", "an", and "the" modifications in this disclosure are intended to be illustrative rather than limiting, and that those skilled in the art will recognize that "one or more" may be used unless the context clearly dictates otherwise.
The names of messages or information exchanged between devices in the embodiments of the present disclosure are for illustrative purposes only, and are not intended to limit the scope of the messages or information.
The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Fig. 1 is a schematic diagram of an application scenario of an information recommendation method according to some embodiments of the present disclosure.
As shown in fig. 1, the electronic device 101 may first obtain at least one detection result 104 of each detection item in the respective detection items 103 related to the target user 102. Each detection item corresponds to at least one department, and each department corresponds to at least one diagnostic person. In this application scenario, each detection item 103 includes: cardiothoracic item 1031, respiratory item 1032, neural item 1033, and hepatobiliary item 1034. The cardiothoracic item 1031 corresponds to the first cardiothoracic detection result 1041 and the second cardiothoracic detection result 1042. The respiration item 1032 corresponds to the first respiration detection result 1043 and the second respiration detection result 1044. The above-described neural item 1033 corresponds to the first nerve detection result 1045 and the second nerve detection result 1046. The hepatobiliary items 1034 correspond to a first hepatobiliary detection node 1047 and a second hepatobiliary detection result 1048. The cardiothoracic item 1031 corresponds to the department 105. The respiratory item 1032 corresponds to the department 105. The above-described neural item 1033 corresponds to the department 105 and the department 106. The hepatobiliary project 1034 corresponds to department 105. The department 105 may be: "internal medicine". The department 106 may be: "surgery". Then, detection information 107 of a predetermined storage structure is generated based on at least one detection result of each of the above-described respective detection items 103. The preset storage structure represents the association relation among departments, detection items and detection results. Then, it is determined whether or not diagnosis is performed on each detection item 103 in the above-described detection information 107. Further, in response to the diagnosis of the detection items 103, at least one department corresponding to at least one detection item in which the detection result is abnormal among the detection items 103 and each detection item in which the detection result is abnormal is determined. In this application scenario, the detection items for which at least one of the detection results is abnormal include: neural item 1033 and hepatobiliary item 1034. The above-described neural item 1033 corresponds to the department 105 and the department 106. The hepatobiliary project 1034 corresponds to department 106. Finally, according to at least one department corresponding to the detection item with abnormal detection result, recommending the relevant information of at least one target diagnostician 108 to be displayed to the target user 102. In the present application scenario, the at least one target diagnostician 108 includes: a first target diagnostician 1081 and a second target diagnostician 1082.
The electronic device 101 may be hardware or software. When the electronic device is hardware, the electronic device may be implemented as a distributed cluster formed by a plurality of servers or terminal devices, or may be implemented as a single server or a single terminal device. When the electronic device is embodied as software, it may be installed in the above-listed hardware devices. It may be implemented, for example, as multiple software or software modules to provide distributed services, or as a single software or software module. And is not particularly limited herein.
It should be understood that the number of electronic devices in fig. 1 is merely illustrative. There may be any number of electronic devices, as desired for implementation.
With continued reference to fig. 2, a flow 200 of some embodiments of an information recommendation method according to the present disclosure is shown. The information recommendation method comprises the following steps:
at step 201, the question type of the question asked by the target user is determined.
In some embodiments, an executing subject of the information recommendation method (e.g., the electronic device 101 shown in fig. 1) may obtain at least one detection result of each detection item in the respective detection items related to the target user through a wired connection manner or a wireless connection manner. Each detection item corresponds to at least one department, and each department corresponds to at least one diagnostic person. Each of the above-mentioned detection items may be a human body part to be examined. The at least one detection result of each detection item may be a result of performing various aspects of detection on the target human body part. As an example, the above-mentioned diagnostician may be a doctor.
It should be noted that the wireless connection means may include, but is not limited to, a 3G/4G connection, a WiFi connection, a bluetooth connection, a WiMAX connection, a Zigbee connection, a uwb (ultra wideband) connection, and other wireless connection means now known or developed in the future.
In some embodiments, the execution subject may generate the detection information of the predetermined storage structure according to at least one detection result of each of the detection items. The preset storage structure represents the association relation among departments, detection items and detection results.
As an example, the execution body may compile a logic code written in advance by a related technician according to each detection result corresponding to each detection item to generate the detection information of the predetermined storage structure.
In some optional implementations of some embodiments, the detection information of the predetermined storage structure associated with the target user is generated according to at least one detection result of each detection item in the detection items and the user information of the target user.
As an example, the execution subject may compile logic code written in advance by a related technician according to at least one detection result of each of the detection items to generate detection information of a predetermined storage structure excluding information related to a target user. Then, the basic information, the past history and the family history of the target user are added to the detection information, and the detection information of the preset storage structure associated with the target user is obtained. Fig. 3 may be referred to for detection information of a predetermined storage structure associated with the target user.
In some optional implementations of some embodiments, the foregoing step further includes:
the method comprises the following steps of responding to a detection information screening instruction of a target user, and determining at least one detection item selected by the target user in the detection information.
And secondly, generating screened detection information according to the at least one detection item selected by the target user and the user information of the target user.
As an example, as shown in fig. 4, in response to the detection information filtering instruction of the target user, neural items and cardiothoracic items selected by the target user in the detection information are determined. And then, generating the screened detection information according to at least one detection item selected by the target user and the basic information, the past history and the family history of the target user.
In some optional implementations of some embodiments, the foregoing step further includes:
and step one, responding to a detection information merging instruction of the target user, and determining whether the target user has historical detection information.
And a second step of writing at least one detection result of each detection item selected by the target user in the history detection information into the detection information in response to the presence of the history detection information by the target user, and obtaining the written detection information as detection information.
As an example, as shown in fig. 5, in response to the detection information merging instruction of the target user, the execution main body may first determine whether the target user has history detection information 502. Then, in response to the presence of the history detection information 502 by the target user, at least one detection result for each detection item selected by the target user in the history detection information 502 is written into the detection information 501, and written detection information 503 is obtained.
In some embodiments, the execution subject may determine whether to diagnose each detection item in the detection information.
And 204, responding to the diagnosis of the detection items, and determining at least one detection item with abnormal detection result in the detection items and at least one department corresponding to the detection item with abnormal detection result.
In some embodiments, in response to diagnosing the detection items, the execution subject may determine at least one detection item in which at least one detection result is abnormal among the detection items and at least one department corresponding to each detection item in which the detection result is abnormal.
Step 205, recommending relevant information of at least one target diagnosis person according to at least one department corresponding to the detection item with abnormal detection result to show the relevant information to the target user.
In some embodiments, the execution subject may recommend, according to at least one department corresponding to a detection item in which each detection result has an abnormality, related information of at least one target diagnosis person to be presented to the target user. As an example, the related information of the target diagnostician may be name information and image information of the target diagnostician.
In some optional implementation manners of some embodiments, the recommending, according to at least one department corresponding to a detection item in which each detection result is abnormal, related information of at least one target diagnosis person to be displayed to the target user may include the following steps:
first, according to at least one department corresponding to the detection item with each abnormal detection result, corresponding weight is distributed to each department in the detection information. As an example, the execution subject may determine, according to a department set (i.e., the at least one department) corresponding to each detection item having an abnormality in the detection result, a department set group corresponding to each detection item having an abnormality in the detection result. The number of repetitions for each department in the set of departments (i.e., the individual departments) is then determined. And finally, according to the repeated number corresponding to each department in each department, assigning corresponding weight to each department.
And secondly, according to the weight distributed to each department in each department, distributing corresponding weight to each diagnostician in each diagnostician corresponding to each department. As an example, the executive body may first determine a diagnostic staff set corresponding to each department in each department, and obtain a diagnostic staff set group. Then, the weight assigned to each department is assigned to the corresponding set of diagnostic persons. And finally, determining at least one weight distributed to each diagnostician, and adding to obtain the weight corresponding to each diagnostician and the weight distributed to each diagnostician correspondingly.
And thirdly, recommending relevant information of at least one target diagnostician related to the detection item with abnormal detection results according to the weight distributed to each diagnostician in the diagnosticians so as to display the relevant information to the target user.
The above embodiments of the present disclosure have the following beneficial effects: the information recommendation method of some embodiments of the present disclosure may recommend the relevant target diagnosis person by generating a detection item in which the detection result is abnormal in the detection information of the predetermined storage structure. Specifically, the current report in the document format can only be handed to a general practitioner to perform detailed diagnosis because the specific conditions in the report of the user cannot be displayed, and cannot perform preliminary diagnosis for the user. Based on this, the information recommendation method of some embodiments of the present disclosure may first obtain at least one detection result of each detection item in the respective detection items, which is related to the target user. Each detection item corresponds to at least one department, and each department corresponds to at least one diagnostic person. Then, detection information of a predetermined storage structure is generated according to at least one detection result of each detection item in the detection items. The preset storage structure represents the association relation among departments, detection items and detection results. The detection information can simply and clearly provide the detection information of the target user, the corresponding department information and the diagnosis personnel information to the target user, and the detection experience of the user is greatly improved. Then, it is determined whether or not each detection item in the detection information is diagnosed. And responding to the diagnosis of the detection items, and determining at least one department corresponding to the detection item with abnormal detection result in at least one detection item and each detection item with abnormal detection result in the detection items. Therefore, the relevant diagnosis personnel information is provided for the target user in a more targeted and subsequent mode. And finally, recommending the related information of at least one target diagnosis person to be displayed to the target user according to at least one department corresponding to the detection item with the abnormal detection result. Therefore, the information recommendation method can recommend the relevant target diagnostician by generating the detection item with the abnormal detection result in the detection information of the preset storage structure.
With continued reference to FIG. 6, a flow 600 of further embodiments of an information recommendation method according to the present disclosure is shown. The information recommendation method comprises the following steps:
In some embodiments, in response to the viewing instruction of the target user, the execution main body (for example, the electronic device 101 shown in fig. 1) may adjust the layout of each detection item of the detection information and the layout of at least one detection result of each detection item according to a detection result that an abnormality exists in the at least one detection result of each detection item of the detection items, so as to obtain adjusted detection information.
In some optional implementations of some embodiments, the type of the detection result includes at least one of: numerical type, image type, and text type; and the detection result with abnormality in at least one detection result of each detection item is determined by the following steps:
in the first step, in response to determining that a numerical detection result exists in at least one detection result of each detection item, whether the numerical detection result is abnormal is determined through numerical comparison.
And a second step of determining whether the detection result of the image type and/or the character type is abnormal or not through semantic analysis in response to determining that the detection result of the image type and/or the character type exists in at least one detection result of each detection item. As an example, in response to determining that there is an image-type detection result in the at least one detection result of each detection item, the execution main body first extracts character information in the detection result, and then determines whether the image-type detection result is abnormal by a text analysis method.
In some embodiments, the specific implementation and technical effects of steps 601, 602, and 604 and 606 can refer to steps 201 and 205 in the embodiments corresponding to fig. 2, which are not described herein again.
As can be seen from fig. 6, compared with the description of some embodiments corresponding to fig. 2, the flow 600 of the information recommendation method in some embodiments corresponding to fig. 6 embodies a step of adjusting the detected information when viewed by the target user. Therefore, the schemes described in the embodiments can support the target user to check at least one abnormal detection result in each detection item, so as to adjust the layout of the detection information, facilitate the target user to check the abnormal information in the detection information, and greatly improve the user experience.
With continued reference to fig. 7, as an implementation of the above-described method for the above-described figures, the present disclosure provides some embodiments of an information recommendation apparatus, which correspond to those of the method embodiments described above in fig. 2, and which may be applied to various electronic devices in particular.
As shown in fig. 7, an information recommendation apparatus 700 of some embodiments includes: an acquisition unit 701, a generation unit 702, a first determination unit 703, a second determination unit 704, and a recommendation unit 705. The obtaining unit 701 is configured to obtain at least one detection result of each detection item in the detection items related to the target user, where each detection item corresponds to at least one department, and each department corresponds to at least one diagnostic person. A generating unit 702 configured to generate detection information of a predetermined storage structure according to at least one detection result of each of the detection items, wherein the predetermined storage structure represents an association relationship among a department, the detection items and the detection results. A first determination unit 703 configured to determine whether or not to diagnose each detection item in the detection information. A second determining unit 704 configured to determine, in response to the diagnosis of the detection items, at least one detection item in which the detection result is abnormal and at least one department corresponding to each detection item in which the detection result is abnormal. The recommending unit 705 is configured to recommend relevant information of at least one target diagnosing person to be displayed to the target user according to at least one department corresponding to the detection item with the abnormal detection result.
In some optional implementations of some embodiments, the generating unit 702 of the information recommendation apparatus 700 may be further configured to: and generating detection information of a preset storage structure associated with the target user according to at least one detection result of each detection item in the detection items and the user information of the target user.
In some optional implementations of some embodiments, the apparatus further includes an adjustment unit (not shown in the figures). Wherein the adjusting unit may be configured to: and responding to the viewing instruction of the target user, and adjusting the layout of each detection item of the detection information and at least one detection result of each detection item according to the abnormal detection result in at least one detection result of each detection item in each detection item to obtain the adjusted detection information.
In some optional implementations of some embodiments, the type of the detection result includes at least one of: numerical type, image type, and text type; and the detection result with abnormality in at least one detection result of each detection item is determined by the following steps: in response to determining that a detection result of a numerical type exists in at least one detection result of each detection item, determining whether the detection result of the numerical type is abnormal through numerical comparison; and in response to determining that the detection result of the image type and/or the character type exists in at least one detection result of each detection item, determining whether the detection result of the image type and/or the character type is abnormal or not through semantic analysis.
In some optional implementations of some embodiments, the apparatus further includes: a detection item determination unit and an information generation unit (not shown in the figure). The detection item determination unit may be configured to: and responding to a detection information screening instruction of the target user, and determining at least one detection item selected by the target user in the detection information. The information generating unit may be configured to: and generating the screened detection information according to the at least one detection item selected by the target user and the user information of the target user.
In some optional implementations of some embodiments, the apparatus further includes: a history detection information determination unit and a writing unit (not shown in the figure). The history detection information determination unit may be configured to: and responding to the detection information merging instruction of the target user, and determining whether the target user has history detection information. The writing unit may be configured to: and in response to the existence of the history detection information by the target user, writing at least one detection result of each detection item selected by the target user in the history detection information into the detection information, and obtaining the written detection information as detection information.
In some optional implementations of some embodiments, the propulsion unit 705 of the information recommendation device 700 may be further configured to: according to at least one department corresponding to the detection item with abnormal detection result, distributing corresponding weight to each department in the detection information; according to the weight distributed to each department in each department, distributing corresponding weight to each diagnostician in each diagnostician corresponding to each department; and recommending relevant information of at least one target diagnostician related to the detection item with abnormal detection results according to the weight distributed to each diagnostician in the diagnosticians so as to display the relevant information to the target user.
It will be understood that the elements described in the apparatus 700 correspond to various steps in the method described with reference to fig. 2. Thus, the operations, features and resulting advantages described above with respect to the method are also applicable to the apparatus 700 and the units included therein, and will not be described herein again.
Referring now to fig. 8, shown is a schematic diagram of an electronic device 800 suitable for use in implementing some embodiments of the present disclosure. The electronic device shown in fig. 8 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 8, an electronic device 800 may include a processing means (e.g., central processing unit, graphics processor, etc.) 801 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)802 or a program loaded from a storage means 808 into a Random Access Memory (RAM) 803. In the RAM803, various programs and data necessary for the operation of the electronic apparatus 800 are also stored. The processing apparatus 801, the ROM 802, and the RAM803 are connected to each other by a bus 804. An input/output (I/O) interface 805 is also connected to bus 804.
Generally, the following devices may be connected to the I/O interface 805: input devices 806 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 807 including, for example, a Liquid Crystal Display (LCD), speakers, vibrators, and the like; storage 808 including, for example, magnetic tape, hard disk, etc.; and a communication device 809. The communication means 809 may allow the electronic device 800 to communicate wirelessly or by wire with other devices to exchange data. While fig. 8 illustrates an electronic device 800 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided. Each block shown in fig. 8 may represent one device or may represent multiple devices as desired.
In particular, according to some embodiments of the present disclosure, the processes described above with reference to the flow diagrams may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In some such embodiments, the computer program may be downloaded and installed from a network through communications device 809, or installed from storage device 808, or installed from ROM 802. The computer program, when executed by the processing apparatus 801, performs the above-described functions defined in the methods of some embodiments of the present disclosure.
It should be noted that the computer readable medium described above in some embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In some embodiments of the disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
In some embodiments, the clients, servers may communicate using any currently known or future developed network Protocol, such as HTTP (HyperText Transfer Protocol), and may interconnect with any form or medium of digital data communication (e.g., a communications network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.
The computer readable medium may be embodied in the apparatus; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: acquiring at least one detection result of each detection item in each detection item related to a target user, wherein each detection item corresponds to at least one department, and each department corresponds to at least one diagnostic person; generating detection information of a preset storage structure according to at least one detection result of each detection item in the detection items, wherein the preset storage structure represents the association relationship among departments, the detection items and the detection results; determining whether to diagnose each detection item in the detection information; responding to the diagnosis of the detection items, and determining at least one detection item with abnormal detection result in the detection items and at least one department corresponding to the detection item with abnormal detection result; and recommending relevant information of at least one target diagnosis person to be displayed to the target user according to at least one department corresponding to the detection item with abnormal detection result.
Computer program code for carrying out operations for embodiments of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in some embodiments of the present disclosure may be implemented by software, and may also be implemented by hardware. The described units may also be provided in a processor, and may be described as: a processor includes an acquisition unit, a generation unit, a first determination unit, a second determination unit, and a recommendation unit. Here, the names of these units do not constitute a limitation to the unit itself in some cases, and for example, the first determination unit may also be described as a "unit that determines whether or not to diagnose each detection item in the above-described detection information".
The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), systems on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is made without departing from the inventive concept as defined above. For example, the above features and (but not limited to) technical features with similar functions disclosed in the embodiments of the present disclosure are mutually replaced to form the technical solution.
Claims (10)
1. An information recommendation method, comprising:
acquiring at least one detection result of each detection item in each detection item related to a target user, wherein each detection item corresponds to at least one department, and each department corresponds to at least one diagnostic person;
generating detection information of a preset storage structure according to at least one detection result of each detection item in each detection item, wherein the preset storage structure represents an association relation among departments, the detection items and the detection results;
determining whether to diagnose each detection item in the detection information;
responding to the diagnosis of the detection items, and determining at least one detection item with abnormal detection result in the detection items and at least one department corresponding to the detection item with abnormal detection result;
and recommending relevant information of at least one target diagnosis person to be displayed to the target user according to at least one department corresponding to the detection item with abnormal detection result.
2. The method of claim 1, wherein the generating detection information of a predetermined storage structure according to at least one detection result of each detection item of the detection items comprises:
and generating detection information of a preset storage structure associated with the target user according to at least one detection result of each detection item in the detection items and the user information of the target user.
3. The method of claim 1, wherein after generating the detection information of the predetermined storage structure according to at least one detection result of each of the respective detection items, the method further comprises:
and responding to the viewing instruction of the target user, and adjusting the layout of each detection item of the detection information and at least one detection result of each detection item according to the abnormal detection result in at least one detection result of each detection item in each detection item to obtain the adjusted detection information.
4. The method of claim 3, wherein the type of detection result comprises at least one of: numerical type, image type, and text type; and
the detection result with abnormality in the at least one detection result of each detection item is determined by the following steps:
in response to determining that a detection result of a numerical type exists in at least one detection result of each detection item, determining whether the detection result of the numerical type is abnormal through numerical comparison;
and in response to determining that the detection result of the image type and/or the character type exists in the at least one detection result of each detection item, determining whether the detection result of the image type and/or the character type is abnormal through semantic analysis.
5. The method of claim 1, wherein after the generating of the detection information of the predetermined storage structure according to at least one detection result of each of the respective detection items, the method further comprises:
responding to a detection information screening instruction of the target user, and determining at least one detection item selected by the target user in the detection information;
and generating screened detection information according to the at least one detection item selected by the target user and the user information of the target user.
6. The method of claim 1, wherein after the generating of the detection information of the predetermined storage structure according to at least one detection result of each of the respective detection items, the method further comprises:
responding to a detection information merging instruction of the target user, and determining whether the target user has historical detection information;
and responding to the historical detection information of the target user, writing at least one detection result of each detection item selected by the target user in the historical detection information into the detection information, and obtaining the written detection information as detection information.
7. The method of claim 1, wherein recommending, according to at least one department corresponding to the detection item with the abnormal detection result, relevant information of at least one target diagnosis person for presentation to the target user comprises:
according to at least one department corresponding to the detection item with abnormal detection result, distributing corresponding weight to each department in the detection information;
according to the weight distributed to each department in each department, distributing corresponding weight to each diagnostic person in each diagnostic person corresponding to each department;
and recommending relevant information of at least one target diagnostician related to the detection item with abnormal detection results according to the weight distributed to each diagnostician in the diagnosticians so as to display the relevant information to the target user.
8. An information recommendation apparatus comprising:
the system comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is configured to acquire at least one detection result of each detection item in each detection item related to a target user, each detection item corresponds to at least one department, and each department corresponds to at least one diagnostic person;
the generating unit is configured to generate detection information of a preset storage structure according to at least one detection result of each detection item in the detection items, wherein the preset storage structure represents the association relationship among departments, the detection items and the detection results;
a first determination unit configured to determine whether or not to diagnose each detection item in the detection information;
a second determining unit configured to determine, in response to the diagnosis of the respective detection items, at least one detection item in which an abnormality exists in at least one detection result among the respective detection items and at least one department corresponding to each detection item in which an abnormality exists in the detection result;
and the recommending unit is configured to recommend the relevant information of at least one target diagnosis person to be displayed to the target user according to at least one department corresponding to the detection item with the abnormal detection result.
9. An electronic device, comprising:
one or more processors;
storage means for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method recited in any of claims 1-7.
10. A computer-readable medium, on which a computer program is stored, wherein the program, when executed by a processor, implements the method of any one of claims 1-7.
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