CN105809368A - Information grade assessment method and device - Google Patents
Information grade assessment method and device Download PDFInfo
- Publication number
- CN105809368A CN105809368A CN201610193123.0A CN201610193123A CN105809368A CN 105809368 A CN105809368 A CN 105809368A CN 201610193123 A CN201610193123 A CN 201610193123A CN 105809368 A CN105809368 A CN 105809368A
- Authority
- CN
- China
- Prior art keywords
- message
- user profile
- information
- level
- message level
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/22—Social work
Abstract
The invention discloses an information grade assessment method.The information grade assessment method comprises the steps that when an information grade assessment instruction of user information is detected, the user information to be assessed is determined; all pieces of key information corresponding to the user information are obtained, wherein the key information comprises user grade information, online time information, question-answering time information and question-answering score information; the information grade of the user information is calculated on the basis of all the pieces of the key information.The invention further discloses an information grade assessment device.According to the information grade assessment method and device, the accuracy of information grade assessment is improved.
Description
Technical field
The present invention relates to field of information processing, particularly relate to assessment method and the device of a kind of message level.
Background technology
Current information platform, such as medical information platform, message level for doctor does not have corresponding evaluation criteria, it is typically all and evaluates accordingly in the grade of present hospitals according to doctor, such as doctor's grade within the hospital is director, then rating director Shi Yeshi in Baidu's health platform.If user's landing platform is putd question to, generally can put question to according to the corresponding doctor of hierarchical selection, but due to suitable low of groups of people's liveness in platform, the information that is easily caused persistently is not replied, obviously, in present information platform, the mode that the message level of doctor is evaluated is not accurate enough.
Summary of the invention
Present invention is primarily targeted at the assessment method and device that propose a kind of message level, it is intended to solve in present information platform, the technical problem not accurate enough to the evaluation of message level.
For achieving the above object, the assessment method of a kind of message level provided by the invention, the assessment method of described message level includes:
When message level user profile being detected evaluates instruction, it is determined that user profile to be evaluated；
Obtaining each key message that described user profile is corresponding, wherein, described key message includes user gradation information, on-line time information, Reaction time information, answer score information；
The message level of described user profile is calculated based on each key message.
Preferably, the triggering mode of described message level evaluation instruction includes:
When key message user profile being detected updates, trigger message ranking instruction；
Or, when increasing user profile in information platform being detected, trigger message ranking instruction.
Preferably, the step of the described message level calculating described user profile based on each key message includes:
Obtain the score value that in described user profile, each key message is corresponding；
Obtain the weight coefficient that each key message preset is corresponding；
Respectively weight coefficient corresponding for each key message and score value are weighted on average, the message level corresponding to obtain described user profile.
Preferably, described being weighted on average by weight coefficient corresponding for each key message and score value respectively, the step to obtain message level corresponding to described user profile includes:
Respectively weight coefficient corresponding for each key message and score value are weighted on average, the total score corresponding to obtain described user profile；
Determine that the score value at described total score place is interval；
According to the interval mapping relations with message level of default score value, obtain the message level that the score value interval determined is corresponding.
Preferably, after the step of the described message level calculating described user profile based on each key message, the assessment method of described message level also includes:
When there being the message level of user profile lower than predetermined level, send information to user terminal corresponding to described user profile.
Additionally, for achieving the above object, the present invention also proposes the evaluation device of a kind of message level, and the evaluation device of described message level includes:
Determine module, during for evaluating instruction at message level user profile being detected, it is determined that user profile to be evaluated；
Acquisition module, for obtaining each key message that described user profile is corresponding, wherein, described key message includes user gradation information, on-line time information, Reaction time information, answer score information；
Computing module, for calculating the message level of described user profile based on each key message.
Preferably, the triggering mode of described message level evaluation instruction includes:
When key message user profile being detected updates, trigger message ranking instruction；
Or, when increasing user profile in information platform being detected, trigger message ranking instruction.
Preferably, described computing module includes:
Obtain submodule, for obtaining the score value that in described user profile, each key message is corresponding；
Described acquisition submodule, is additionally operable to obtain the weight coefficient that each key message preset is corresponding；
Calculating sub module, for respectively weight coefficient corresponding for each key message and score value being weighted on average, the message level corresponding to obtain described user profile.
Preferably, described calculating sub module includes:
Computing unit, for respectively weight coefficient corresponding for each key message and score value being weighted on average, the total score corresponding to obtain described user profile；
Determining unit, the score value for determining described total score place is interval；
Acquiring unit, for according to the interval mapping relations with message level of the score value preset, obtaining the message level that the score value interval determined is corresponding.
Preferably, the evaluation device of described message level also includes:
Sending module, for when there being the message level of user profile lower than predetermined level, sends information to user terminal corresponding to described user profile.
The assessment method of the message level that the present invention proposes and device, when message level user profile being detected evaluates instruction, first determine user profile to be evaluated, then each key message that described user profile is corresponding is obtained, wherein, described key message includes user gradation information, on-line time information, Reaction time information, answer score information, it is finally based on each key message and calculates the message level of described user profile, such as, when user profile is information about doctor, key message according to information about doctor calculates message level, and be not only evaluate accordingly in the grade of present hospitals according to doctor, the present invention calculates the message level of described user profile according to each key message comprised in user profile, improve the accuracy of message level evaluation.
Accompanying drawing explanation
Fig. 1 is the schematic flow sheet of the assessment method first embodiment of message level of the present invention；
Fig. 2 is the schematic flow sheet that the present invention calculates the message level preferred embodiment of described user profile based on each key message；
Fig. 3 is that weight coefficient corresponding for each key message and score value are weighted on average by the present invention respectively, to obtain the schematic flow sheet of message level preferred embodiment corresponding to described user profile；
Fig. 4 is the high-level schematic functional block diagram of assessment method second embodiment of message level of the present invention；
Fig. 5 is the high-level schematic functional block diagram of the evaluation device first embodiment of message level of the present invention；
Fig. 6 is the refinement high-level schematic functional block diagram of computing module in Fig. 5；
Fig. 7 is the refinement high-level schematic functional block diagram of calculating sub module in Fig. 6；
Fig. 8 is the high-level schematic functional block diagram of evaluation device second embodiment of message level of the present invention.
The realization of the object of the invention, functional characteristics and advantage will in conjunction with the embodiments, are described further with reference to accompanying drawing.
Detailed description of the invention
Should be appreciated that specific embodiment described herein is only in order to explain the present invention, is not intended to limit the present invention.
The present invention provides the assessment method of a kind of message level.
Schematic flow sheet with reference to the assessment method first embodiment that Fig. 1, Fig. 1 are message level of the present invention.
The present embodiment proposes the assessment method of a kind of message level, and the assessment method of described message level includes:
Step S10, when message level user profile being detected evaluates instruction, it is determined that user profile to be evaluated；
In the present embodiment, the triggering mode of described message level evaluation instruction includes:
A, detect user profile key message update time, trigger message ranking instruction；
In the present embodiment, each key message corresponding to described user profile includes: user gradation information, on-line time information, Reaction time information, answer score information etc., therefore, when any one key message user profile being detected updates, get final product trigger message ranking instruction, be equivalent to, when the key message having user profile updates, the evaluation of message level to be re-started, it is achieved that upgrading in time of message level.
B, in information platform being detected increase user profile time, trigger message ranking instruction.
In the present embodiment, in default information platform, in Baidu's health platform, detect that user profile increases, when namely increasing user profile in information platform, according to the user profile trigger message ranking instruction increased.
In the present embodiment, when message level user profile being detected evaluates instruction, user profile to be evaluated is determined in evaluation instruction according to described message level, specifically, when key message user profile being detected updates, using update key message described user profile as user profile to be evaluated；And when increasing user profile in information platform being detected, using the user profile of increase as user profile to be evaluated.
It should be noted that the user profile in the present embodiment includes nutritionist's information, information about doctor, fitness's information, lecturer's information etc..
Step S20, obtains each key message that described user profile is corresponding, and wherein, described key message includes user gradation information, on-line time information, Reaction time information, answer score information；
In the present embodiment, determining after the user profile evaluated, obtain each key message that described user profile is corresponding, in the present embodiment, described key message includes user gradation information, on-line time information, Reaction time information, answer score information, certainly, may also include user's evaluation information or pouplarity information etc..
For being best understood from the present embodiment, being exemplified below: when user profile is information about doctor, the user gradation information of described information about doctor represents doctor's professional grade information in being currently located hospital, such as archiater or deputy director doctor etc.；The on-line time information of described information about doctor represents the time of information about doctor logon information every day platform, described information platform such as Baidu's health platform or cloud health service platform etc.；The Reaction time information of described information about doctor represents that user is to after doctor's proposition problem, the time that doctor answers a question；And the answer score information of described information about doctor represents that doctor is after having answered the information of patient, the mark that the information that doctor answers is marked by patient.
Step S30, calculates the message level of described user profile based on each key message.
In the present embodiment, after getting each key message that described user profile is corresponding, calculating the message level of described user profile according to each key message obtained, specifically, the embodiment of described step S30 includes:
1) mode one, described step S30 include:
Step 1, obtain the mark that each key message is corresponding；
Before the mark that each key message of described acquisition is corresponding, including the step calculating mark corresponding to each key message, the mode of the mark that each key message of described calculating is corresponding is exemplified below: when user profile is information about doctor, if in the key message that described user profile is corresponding, including user gradation information, on-line time information, Reaction time information, answer score information four, and the total score of each is all 25 points.So, the described user gradation information rating calculation score according to doctor's correspondence within the hospital, for instance, hospital includes 5 grades, then 5 ranking score are followed successively by 5,10,15,20,25 points.And on-line time information accounts for according to the time reached the standard grade in one day and calculates score working total time, for instance, working total time is 8 hours, and on-line time is 7 hours, then the score that on-line time information is corresponding is 7/8*25=22 and divides.And Reaction time information is determined according to the time range preset, such as, answer a question in 5 minutes to be divided into 25 points, answer a question in 5 minutes-15 minutes to be divided into 20 points, answer a question in 15 minutes-30 minutes to be divided into 15 points, answer a question in 30 minutes-60 minutes to be divided into 10 points, answered a question to be divided into 5 points more than 60 minutes.And described answer score information is given a mark according to the satisfaction of patient, the 0-25 that ranges for of marking divides.
Further, for improving the motility of message level evaluation, the answer score information that preferably information about doctor of different message levels gets is also corresponding different, such as, user puts question to regard to the doctor of the same problem doctor to the first estate and the second grade, wherein, the first estate is higher than the second grade, so when two doctors are marked, doctor's score range of choice of the first estate is that 15-25 divides, and the doctor of the second grade marks, the range of choice is that 10-20 grades；Or doctor's score range of choice of the first estate is that 20-25 divides, and doctor's score range of choice of the second grade is that 15-20 grades.
Step 2, the mark of each key message obtained is added；
Step 3, determine the message level of described user profile according to the gross score after being added, wherein, the mode of the described message level determining described user profile according to the gross score after being added is: determine that the score value at described gross score place is interval, according to the interval mapping relations with message level of default score value, obtain the message level that the score value interval determined is corresponding.
For being best understood from the present embodiment, it is exemplified below: when user profile is information about doctor, if user gradation information is 20 points in information about doctor, on-line time information 22 points, Reaction time is 15 points, and answer score information is 19 points, then may know that the gross score of information about doctor is 76 points, it is then determined that the score value at described gross score place is interval, then according to the interval mapping relations with message level of the score value preset, obtain the message level that the score value interval determined is corresponding.If information platform includes 5 score value intervals, 0-20 divides corresponding 5th grade, 21-40 divides the corresponding fourth estate, 41-60 to divide the corresponding tertiary gradient, 61-80 to divide corresponding second grade, 81-100 to divide corresponding the first estate, so gross score 78 points according to described user profile, namely can determine that message level corresponding to described user profile is the second grade.It is understood that the interval mapping relations with message level of the score value of described information are configured as the case may be, it is possible to mark off 10 score values intervals and 10 message levels, repeat no more herein.
2) mode two, with reference to Fig. 2, described step S30 includes:
Step S31, obtains the score value that in described user profile, each key message is corresponding；
In the present embodiment, the score value that in the described user profile of described acquisition, each key message is corresponding is obtain the last score value obtained in described key message.In like manner, before the score value that each key message of described acquisition is corresponding, include the step calculating score value corresponding to each key message equally, the mode of the score value that each key message of described calculating is corresponding is exemplified below: when user profile is information about doctor, if in the key message that described user profile is corresponding, including user gradation information, on-line time information, Reaction time information, answer score information four, and the total score of each is all 100 points.So, the rating calculation score that described user gradation information divides within the hospital according to doctor, for instance, hospital includes 5 grades, then 5 ranking score are followed successively by 20,40,60,80,100 points.And on-line time information accounts for according to the time reached the standard grade in one day and calculates score working total time, for instance, working total time is 8 hours, and on-line time is 7 hours, then the score that on-line time information is corresponding is 7/8*100=86 and divides.And Reaction time information is determined according to the time range preset, such as, answer a question in 5 minutes to be divided into 100 points, answer a question in 5 minutes-15 minutes to be divided into 80 points, answer a question in 15 minutes-30 minutes to be divided into 60 points, answer a question in 30 minutes-60 minutes to be divided into 40 points, answered a question to be divided into 20 points more than 60 minutes.And described answer score information is given a mark according to the satisfaction of patient, the 0-100 that ranges for of marking divides.
Further, for improving the motility of message level evaluation, the answer score information that preferably information about doctor of different message levels gets is also corresponding different, such as, user puts question to regard to the doctor of the same problem doctor to the first estate and the second grade, wherein, the first estate is higher than the second grade, so when two doctors are marked, doctor's score range of choice of the first estate is that 80-100 divides, and the doctor of the second grade marks, the range of choice is that 70-90 grades；Or doctor's score range of choice of the first estate is that 90-100 divides, and doctor's score range of choice of the second grade is that 70-80 grades.
Step S32, obtains the weight coefficient that each key message preset is corresponding；
Step S33, is weighted on average by weight coefficient corresponding for each key message and score value respectively, the message level corresponding to obtain described user profile.
Further, in order to improve the accuracy that message level calculates, with reference to Fig. 3, described step S33 includes:
Step S331, is weighted on average by weight coefficient corresponding for each key message and score value respectively, the total score corresponding to obtain described user profile.
Step S332, it is determined that the score value at described total score place is interval；
Step S333, according to the interval mapping relations with message level of default score value, obtains the message level that the score value interval determined is corresponding.
nullIn the present embodiment，After obtaining the score value that in described user profile, each key message is corresponding，Obtain the weight coefficient that each key message preset is corresponding，The weight coefficient that each key message described is corresponding is configured as the case may be，Such as，By user gradation information、On-line time information、Reaction time information、The weight coefficient that four key messages of answer score information are preset is respectively set to 0.3、0.15、0.25 and 0.3，Then after getting the weight coefficient that each key message is corresponding，Weight coefficient corresponding for each key message and score value can be weighted on average，The total score corresponding to obtain described user profile，If in four key messages，User gradation information is 80 points，On-line time information 86 points，Reaction time is 60 points，Answer score information is 78 points，Then weight coefficient corresponding for each key message and score value are weighted average computing formula as follows:
0.3*80+0.15*86+0.25*60+0.3*78=76.3
Finally, the total score obtaining described user profile is 76.3 points, if now information platform includes 5 score value intervals, wherein, 0-20 divides corresponding 5th grade, 21-40 divides the corresponding fourth estate, 41-60 to divide the corresponding tertiary gradient, 61-80 to divide corresponding second grade, 81-100 to divide corresponding the first estate, then the PTS 76.3 points according to described user profile, namely can determine that message level corresponding to described user profile is the second grade.It is understood that the interval mapping relations with message level of the score value of described information are configured as the case may be, it is possible to mark off 10 score values intervals and 10 message levels, repeat no more herein.
The assessment method of the message level that the present embodiment proposes, when message level user profile being detected evaluates instruction, first determine user profile to be evaluated, then each key message that described user profile is corresponding is obtained, wherein, described key message includes user gradation information, on-line time information, Reaction time information, answer score information, it is finally based on each key message and calculates the message level of described user profile, such as, when user profile is information about doctor, key message according to information about doctor calculates message level, and be not only evaluate accordingly in the grade of present hospitals according to doctor, the present invention calculates the message level of described user profile according to each key message comprised in user profile, improve the accuracy of message level evaluation.
Further, in order to improve the intelligent of message level evaluation, the second embodiment of the assessment method of message level of the present invention is proposed based on first embodiment, in the present embodiment, with reference to Fig. 4, after described step S30, the assessment method of described message level also includes:
Step S40, when there being the message level of user profile lower than predetermined level, sends information to user terminal corresponding to described user profile.
In the present embodiment, if detect that the message level of user profile is lower than predetermined level, as during lower than the fourth estate, now, send the information user terminal that extremely described user profile is corresponding, corresponding operation is performed, as often reached the standard grade, information answering patient etc. in time for described user terminal.
In the present embodiment, when there being the message level of user profile lower than predetermined level, send information to user terminal corresponding to described user profile, it is simple to improve in information platform, the quality of user profile, improve the intelligent of message level evaluation.
The present invention further provides the evaluation device of a kind of message level.
High-level schematic functional block diagram with reference to the evaluation first embodiment that Fig. 5, Fig. 5 are message level of the present invention.
It is emphasized that, to one skilled in the art, functional block diagram shown in Fig. 5 is only the exemplary plot of a preferred embodiment, and those skilled in the art, around the functional module of the evaluation device of the message level shown in Fig. 5, can carry out supplementing of new functional module easily；The title of each functional module is self-defined title, only for assisting each program function block of the evaluation device understanding this message level, being not used in restriction technical scheme, the core of technical solution of the present invention is, the function that the functional module of each self-defined title to be reached.
The present embodiment proposes the evaluation device of a kind of message level, and the evaluation device of described message level includes:
Determine module 10, during for evaluating instruction at message level user profile being detected, it is determined that user profile to be evaluated；
In the present embodiment, the triggering mode of described message level evaluation instruction includes:
A, detect user profile key message update time, trigger message ranking instruction；
In the present embodiment, each key message corresponding to described user profile includes: user gradation information, on-line time information, Reaction time information, answer score information etc., therefore, when any one key message user profile being detected updates, get final product trigger message ranking instruction, be equivalent to, when the key message having user profile updates, the evaluation of message level to be re-started, it is achieved that upgrading in time of message level.
B, in information platform being detected increase user profile time, trigger message ranking instruction.
In the present embodiment, in default information platform, in Baidu's health platform, detect that user profile increases, when namely increasing user profile in information platform, according to the user profile trigger message ranking instruction increased.
In the present embodiment, when message level user profile being detected evaluates instruction, described determine module 10 according to described message level evaluation instruction determine user profile to be evaluated, specifically, when key message user profile being detected updates, using update key message described user profile as user profile to be evaluated；And when increasing user profile in information platform being detected, using the user profile of increase as user profile to be evaluated.
It should be noted that the user profile in the present embodiment includes nutritionist's information, information about doctor, fitness's information, lecturer's information etc..
Acquisition module 20, for obtaining each key message that described user profile is corresponding, wherein, described key message includes user gradation information, on-line time information, Reaction time information, answer score information；
In the present embodiment, determine that module 10 is determined after the user profile evaluated described, described acquisition module 20 obtains each key message that described user profile is corresponding, in the present embodiment, described key message includes user gradation information, on-line time information, Reaction time information, answer score information, certainly, may also include user's evaluation information or pouplarity information etc..
For being best understood from the present embodiment, being exemplified below: when user profile is information about doctor, the user gradation information of described information about doctor represents doctor's professional grade information in being currently located hospital, such as archiater or deputy director doctor etc.；The on-line time information of described information about doctor represents the time of information about doctor logon information every day platform, described information platform such as Baidu's health platform or cloud health service platform etc.；The Reaction time information of described information about doctor represents that user is to after doctor's proposition problem, the time that doctor answers a question；And the answer score information of described information about doctor represents that doctor is after having answered the information of patient, the mark that the information that doctor answers is marked by patient.
Computing module 30, for calculating the message level of described user profile based on each key message.
In the present embodiment, after described acquisition module 20 gets each key message that described user profile is corresponding, described computing module 30 calculates the message level of described user profile according to each key message obtained, specifically, the embodiment of the message level that described computing module 30 calculates described user profile based on each key message includes:
1) mode one, described computing module 30 include:
Obtain submodule, for obtaining the mark that each key message is corresponding；
Described computing module 30 also includes calculating sub module, described calculating sub module calculates the mode of mark corresponding to each key message and is exemplified below: when user profile is information about doctor, if in the key message that described user profile is corresponding, including user gradation information, on-line time information, Reaction time information, answer score information four, and the total score of each is all 25 points.So, the described user gradation information rating calculation score according to doctor's correspondence within the hospital, for instance, hospital includes 5 grades, then 5 ranking score are followed successively by 5,10,15,20,25 points.And on-line time information accounts for according to the time reached the standard grade in one day and calculates score working total time, for instance, working total time is 8 hours, and on-line time is 7 hours, then the score that on-line time information is corresponding is 7/8*25=22 and divides.And Reaction time information is determined according to the time range preset, such as, answer a question in 5 minutes to be divided into 25 points, answer a question in 5 minutes-15 minutes to be divided into 20 points, answer a question in 15 minutes-30 minutes to be divided into 15 points, answer a question in 30 minutes-60 minutes to be divided into 10 points, answered a question to be divided into 5 points more than 60 minutes.And described answer score information is given a mark according to the satisfaction of patient, the 0-25 that ranges for of marking divides.
Further, for improving the motility of message level evaluation, the answer score information that preferably information about doctor of different message levels gets is also corresponding different, such as, user puts question to regard to the doctor of the same problem doctor to the first estate and the second grade, wherein, the first estate is higher than the second grade, so when two doctors are marked, doctor's score range of choice of the first estate is that 15-25 divides, and the doctor of the second grade marks, the range of choice is that 10-20 grades；Or doctor's score range of choice of the first estate is that 20-25 divides, and doctor's score range of choice of the second grade is that 15-20 grades.
Described acquisition submodule, is additionally operable to the mark by each key message obtained and is added；
Determine submodule, for determining the message level of described user profile according to the gross score after being added, wherein, the mode of the described message level determining described user profile according to the gross score after being added is: determine that the score value at described gross score place is interval, according to the interval mapping relations with message level of default score value, obtain the message level that the score value interval determined is corresponding.
For being best understood from the present embodiment, it is exemplified below: when user profile is information about doctor, if user gradation information is 20 points in information about doctor, on-line time information 22 points, Reaction time is 15 points, and answer score information is 19 points, then may know that the gross score of information about doctor is 76 points, it is then determined that the score value at described gross score place is interval, then according to the interval mapping relations with message level of the score value preset, obtain the message level that the score value interval determined is corresponding.If information platform includes 5 score value intervals, 0-20 divides corresponding 5th grade, 21-40 divides the corresponding fourth estate, 41-60 to divide the corresponding tertiary gradient, 61-80 to divide corresponding second grade, 81-100 to divide corresponding the first estate, so gross score 78 points according to described user profile, namely can determine that message level corresponding to described user profile is the second grade.It is understood that the interval mapping relations with message level of the score value of described information are configured as the case may be, it is possible to mark off 10 score values intervals and 10 message levels, repeat no more herein.
2) mode two, with reference to Fig. 6, described computing module 30 includes:
Obtain submodule 31, for obtaining the score value that in described user profile, each key message is corresponding；
In the present embodiment, described acquisition submodule 31 obtains the score value that in described user profile, each key message is corresponding is obtain the last score value obtained in described key message.In like manner, described calculating sub module calculates the mode of score value corresponding to each key message and is exemplified below: when user profile is information about doctor, if in the key message that described user profile is corresponding, including user gradation information, on-line time information, Reaction time information, answer score information four, and the total score of each is all 100 points.So, the rating calculation score that described user gradation information divides within the hospital according to doctor, for instance, hospital includes 5 grades, then 5 ranking score are followed successively by 20,40,60,80,100 points.And on-line time information accounts for according to the time reached the standard grade in one day and calculates score working total time, for instance, working total time is 8 hours, and on-line time is 7 hours, then the score that on-line time information is corresponding is 7/8*100=86 and divides.And Reaction time information is determined according to the time range preset, such as, answer a question in 5 minutes to be divided into 100 points, answer a question in 5 minutes-15 minutes to be divided into 80 points, answer a question in 15 minutes-30 minutes to be divided into 60 points, answer a question in 30 minutes-60 minutes to be divided into 40 points, answered a question to be divided into 20 points more than 60 minutes.And described answer score information is given a mark according to the satisfaction of patient, the 0-100 that ranges for of marking divides.
Further, for improving the motility of message level evaluation, the answer score information that preferably information about doctor of different message levels gets is also corresponding different, such as, user puts question to regard to the doctor of the same problem doctor to the first estate and the second grade, wherein, the first estate is higher than the second grade, so when two doctors are marked, doctor's score range of choice of the first estate is that 80-100 divides, and the doctor of the second grade marks, the range of choice is that 70-90 grades；Or doctor's score range of choice of the first estate is that 90-100 divides, and doctor's score range of choice of the second grade is that 70-80 grades.
Described acquisition submodule 31, is additionally operable to obtain the weight coefficient that each key message preset is corresponding；
Calculating sub module 32, for respectively weight coefficient corresponding for each key message and score value being weighted on average, the message level corresponding to obtain described user profile.
Further, in order to improve the accuracy that message level calculates, with reference to Fig. 7, described calculating sub module 32 includes:
Computing unit 321, for respectively weight coefficient corresponding for each key message and score value being weighted on average, the total score corresponding to obtain described user profile；
Determining unit 322, the score value for determining described total score place is interval；
Acquiring unit 323, for according to the interval mapping relations with message level of the score value preset, obtaining the message level that the score value interval determined is corresponding.
nullIn the present embodiment，After described acquisition submodule 31 obtains the score value that in described user profile, each key message is corresponding，Described acquisition submodule 31 obtains the weight coefficient that each key message preset is corresponding，The weight coefficient that each key message described is corresponding is configured as the case may be，Such as，By user gradation information、On-line time information、Reaction time information、The weight coefficient that four key messages of answer score information are preset is respectively set to 0.3、0.15、0.25 and 0.3，Then after described acquisition submodule 31 gets the weight coefficient that each key message is corresponding，Weight coefficient corresponding for each key message and score value can be weighted on average by described calculating sub module 32，The total score corresponding to obtain described user profile，If in four key messages，User gradation information is 80 points，On-line time information 86 points，Reaction time is 60 points，Answer score information is 78 points，Then weight coefficient corresponding for each key message and score value are weighted average computing formula as follows:
0.3*80+0.15*86+0.25*60+0.3*78=76.3
Finally, the total score obtaining described user profile is 76.3 points, if now information platform includes 5 score value intervals, wherein, 0-20 divides corresponding 5th grade, 21-40 divides the corresponding fourth estate, 41-60 to divide the corresponding tertiary gradient, 61-80 to divide corresponding second grade, 81-100 to divide corresponding the first estate, then the PTS 76.3 points according to described user profile, namely can determine that message level corresponding to described user profile is the second grade.It is understood that the interval mapping relations with message level of the score value of described information are configured as the case may be, it is possible to mark off 10 score values intervals and 10 message levels, repeat no more herein.
The evaluation device of the message level that the present embodiment proposes, when message level user profile being detected evaluates instruction, first determine user profile to be evaluated, then each key message that described user profile is corresponding is obtained, wherein, described key message includes user gradation information, on-line time information, Reaction time information, answer score information, it is finally based on each key message and calculates the message level of described user profile, such as, when user profile is information about doctor, key message according to information about doctor calculates message level, and be not only evaluate accordingly in the grade of present hospitals according to doctor, the present invention calculates the message level of described user profile according to each key message comprised in user profile, improve the accuracy of message level evaluation.
Further, in order to improve the intelligent of message level evaluation, proposing the second embodiment of the evaluation device of message level of the present invention based on first embodiment, in the present embodiment, with reference to Fig. 8, the evaluation device of described message level also includes:
Sending module 40, for when there being the message level of user profile lower than predetermined level, sends information to user terminal corresponding to described user profile.
In the present embodiment, if detect that the message level of user profile is lower than predetermined level, as during lower than the fourth estate, now, described sending module 40 sends the information user terminal that extremely described user profile is corresponding, corresponding operation is performed, as often reached the standard grade, information answering patient etc. in time for described user terminal.
In the present embodiment, when there being the message level of user profile lower than predetermined level, send information to user terminal corresponding to described user profile, it is simple to improve in information platform, the quality of user profile, improve the intelligent of message level evaluation.
It should be noted that, in this article, term " includes ", " comprising " or its other variant any are intended to comprising of nonexcludability, so that include the process of a series of key element, method, article or device not only include those key elements, but also include other key element being not expressly set out, or also include the key element intrinsic for this process, method, article or device.When there is no more restriction, statement " including ... " key element limited, it is not excluded that there is also other identical element in including the process of this key element, method, article or device.
The invention described above embodiment sequence number, just to describing, does not represent the quality of embodiment.
Through the above description of the embodiments, those skilled in the art is it can be understood that can add the mode of required general hardware platform by software to above-described embodiment method and realize, hardware can certainly be passed through, but in a lot of situation, the former is embodiment more preferably.Based on such understanding, the part that prior art is contributed by technical scheme substantially in other words can embody with the form of software product, this computer software product is stored in a storage medium (such as ROM/RAM, magnetic disc, CD), including some instructions with so that a station terminal equipment (can be mobile phone, computer, server, air-conditioner, or the network equipment etc.) perform the method described in each embodiment of the present invention.
These are only the preferred embodiments of the present invention; not thereby the scope of the claims of the present invention is limited; every equivalent structure utilizing description of the present invention and accompanying drawing content to make or equivalence flow process conversion; or directly or indirectly it is used in other relevant technical field, all in like manner include in the scope of patent protection of the present invention.
Claims (10)
1. the assessment method of a message level, it is characterised in that the assessment method of described message level comprises the following steps:
When message level user profile being detected evaluates instruction, it is determined that user profile to be evaluated；
Obtaining each key message that described user profile is corresponding, wherein, described key message includes user gradation information, on-line time information, Reaction time information, answer score information；
The message level of described user profile is calculated based on each key message.
2. the assessment method of message level as claimed in claim 1, it is characterised in that the triggering mode of described message level evaluation instruction includes:
When key message user profile being detected updates, trigger message ranking instruction；
Or, when increasing user profile in information platform being detected, trigger message ranking instruction.
3. the assessment method of message level as claimed in claim 1, it is characterised in that the step of the described message level calculating described user profile based on each key message includes:
Obtain the score value that in described user profile, each key message is corresponding；
Obtain the weight coefficient that each key message preset is corresponding；
Respectively weight coefficient corresponding for each key message and score value are weighted on average, the message level corresponding to obtain described user profile.
4. the assessment method of message level as claimed in claim 3, it is characterised in that described respectively weight coefficient corresponding for each key message and score value are weighted on average, the step to obtain message level corresponding to described user profile includes:
Respectively weight coefficient corresponding for each key message and score value are weighted on average, the total score corresponding to obtain described user profile；
Determine that the score value at described total score place is interval；
According to the interval mapping relations with message level of default score value, obtain the message level that the score value interval determined is corresponding.
5. the assessment method of the message level as described in any one of claim 1-4, it is characterised in that after the step of the described message level calculating described user profile based on each key message, the assessment method of described message level also includes:
When there being the message level of user profile lower than predetermined level, send information to user terminal corresponding to described user profile.
6. the evaluation device of a message level, it is characterised in that the evaluation device of described message level includes:
Determine module, during for evaluating instruction at message level user profile being detected, it is determined that user profile to be evaluated；
Acquisition module, for obtaining each key message that described user profile is corresponding, wherein, described key message includes user gradation information, on-line time information, Reaction time information, answer score information；
Computing module, for calculating the message level of described user profile based on each key message.
7. the evaluation device of message level as claimed in claim 6, it is characterised in that the triggering mode of described message level evaluation instruction includes:
When key message user profile being detected updates, trigger message ranking instruction；
Or, when increasing user profile in information platform being detected, trigger message ranking instruction.
8. the evaluation device of message level as claimed in claim 6, it is characterised in that described computing module includes:
Obtain submodule, for obtaining the score value that in described user profile, each key message is corresponding；
Described acquisition submodule, is additionally operable to obtain the weight coefficient that each key message preset is corresponding；
Calculating sub module, for respectively weight coefficient corresponding for each key message and score value being weighted on average, the message level corresponding to obtain described user profile.
9. the evaluation device of message level as claimed in claim 8, it is characterised in that described calculating sub module includes:
Computing unit, for respectively weight coefficient corresponding for each key message and score value being weighted on average, the total score corresponding to obtain described user profile；
Determining unit, the score value for determining described total score place is interval；
Acquiring unit, for according to the interval mapping relations with message level of the score value preset, obtaining the message level that the score value interval determined is corresponding.
10. the evaluation device of the message level as described in any one of claim 6-9, it is characterised in that the evaluation device of described message level also includes:
Sending module, for when there being the message level of user profile lower than predetermined level, sends information to user terminal corresponding to described user profile.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610193123.0A CN105809368A (en) | 2016-03-30 | 2016-03-30 | Information grade assessment method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610193123.0A CN105809368A (en) | 2016-03-30 | 2016-03-30 | Information grade assessment method and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN105809368A true CN105809368A (en) | 2016-07-27 |
Family
ID=56459340
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610193123.0A Pending CN105809368A (en) | 2016-03-30 | 2016-03-30 | Information grade assessment method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105809368A (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107038930A (en) * | 2017-05-19 | 2017-08-11 | 华中师范大学 | A kind of Chinese language word school work ability diagnostic method and its device based on contextualized learning |
| CN107633338A (en) * | 2016-12-30 | 2018-01-26 | 平安科技（深圳）有限公司 | List sort management method and device |
| CN107784419A (en) * | 2016-11-14 | 2018-03-09 | 平安科技（深圳）有限公司 | The method and apparatus for distributing list data |
| CN107967829A (en) * | 2017-12-29 | 2018-04-27 | 深圳中兴网信科技有限公司 | Dynamic layered teaching equipment and dynamic layered teaching method |
| CN108074123A (en) * | 2016-11-14 | 2018-05-25 | 平安科技（深圳）有限公司 | The distribution method and system of outgoing call list |
| CN108898022A (en) * | 2018-06-22 | 2018-11-27 | 珠海市君天电子科技有限公司 | A kind of method for testing performance, device and electronic equipment |
| CN109039712A (en) * | 2018-07-13 | 2018-12-18 | 广州神马移动信息科技有限公司 | Management method, device, the system, storage medium of user in online Knowledge Community |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102043811A (en) * | 2009-10-13 | 2011-05-04 | 北京大学 | Method and system for evaluating medical information |
| CN102332053A (en) * | 2011-07-22 | 2012-01-25 | 大连亿创天地科技发展有限公司 | Scoring and rating system for public praise of doctor |
| CN103093315A (en) * | 2013-01-18 | 2013-05-08 | 余飞 | Medical ethics file quantitative evaluation system based on multiple evaluation subject |
-
2016
- 2016-03-30 CN CN201610193123.0A patent/CN105809368A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102043811A (en) * | 2009-10-13 | 2011-05-04 | 北京大学 | Method and system for evaluating medical information |
| CN102332053A (en) * | 2011-07-22 | 2012-01-25 | 大连亿创天地科技发展有限公司 | Scoring and rating system for public praise of doctor |
| CN103093315A (en) * | 2013-01-18 | 2013-05-08 | 余飞 | Medical ethics file quantitative evaluation system based on multiple evaluation subject |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107784419A (en) * | 2016-11-14 | 2018-03-09 | 平安科技（深圳）有限公司 | The method and apparatus for distributing list data |
| CN108074123A (en) * | 2016-11-14 | 2018-05-25 | 平安科技（深圳）有限公司 | The distribution method and system of outgoing call list |
| CN107633338A (en) * | 2016-12-30 | 2018-01-26 | 平安科技（深圳）有限公司 | List sort management method and device |
| CN107038930A (en) * | 2017-05-19 | 2017-08-11 | 华中师范大学 | A kind of Chinese language word school work ability diagnostic method and its device based on contextualized learning |
| CN107967829A (en) * | 2017-12-29 | 2018-04-27 | 深圳中兴网信科技有限公司 | Dynamic layered teaching equipment and dynamic layered teaching method |
| CN108898022A (en) * | 2018-06-22 | 2018-11-27 | 珠海市君天电子科技有限公司 | A kind of method for testing performance, device and electronic equipment |
| CN109039712A (en) * | 2018-07-13 | 2018-12-18 | 广州神马移动信息科技有限公司 | Management method, device, the system, storage medium of user in online Knowledge Community |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105809368A (en) | Information grade assessment method and device | |
| TWI567685B (en) | System and method of truly reflecting ability of testee through online test and storage medium storing the method | |
| CN109816265B (en) | Knowledge characteristic mastery degree evaluation method, question recommendation method and electronic equipment | |
| US7552104B2 (en) | Decision support system and method | |
| CN108882174A (en) | Mobile terminal locating method, device, electronic equipment and storage medium | |
| KR102126718B1 (en) | System and method of providing custom-made learning contents using artificial intelligence | |
| CN111858906B (en) | Problem recommendation method and device, electronic equipment and computer readable storage medium | |
| KR20160135451A (en) | System of fixing department and method thereof | |
| CN107504634A (en) | Cleanliness factor detection method, device, air conditioner and the readable storage medium storing program for executing of screen pack | |
| KR20200012431A (en) | Method for providing an information of a question analysis using big data | |
| CN110232498A (en) | Employee's Potential Analysis method, apparatus, equipment and computer readable storage medium | |
| JP2009169461A (en) | Training support system, training support method and training support program | |
| CN113409174A (en) | Knowledge point evaluation method and device | |
| CN115526754A (en) | Intelligent comprehensive old people evaluation method and system based on Bayesian network | |
| US20210019656A1 (en) | Information processing device, information processing method, and computer program | |
| KR101577716B1 (en) | A method of extracting couples with optimal condition using weight ratio for one's spouse index and the record medium recording thereof | |
| CN110851721A (en) | Method and equipment for recommending test questions according to individual features of user | |
| Kamakura et al. | Tailored interviewing: An application of item response theory for personality measurement | |
| CN109102357A (en) | A kind of method for pushing based on Articles detecting, device and terminal | |
| CN108766527B (en) | Method and device for determining food calorie | |
| CN114936281A (en) | Big data based test question dynamic classification method, device, equipment and storage medium | |
| CN113094245B (en) | Method for measuring health of database cluster | |
| CN114944219A (en) | Mental scale recommendation method and device based on artificial intelligence and storage medium | |
| CN114429269A (en) | Human factor work efficiency evaluation method, system and device | |
| CN107658025A (en) | Health and fitness information method for pushing, device, equipment and computer-readable recording medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20190417 Address after: 518000 Guangdong province Shenzhen Longgang District Bantian Street five and Avenue North 4012 Yuan Zheng Industrial Park. Applicant after: Yuanzheng Science and Technology Co., Ltd., Shenzhen City Address before: 518000 Room 201, building A, No. 1, Qian Wan Road, Qianhai Shenzhen Hong Kong cooperation zone, Shenzhen, Guangdong (Shenzhen Qianhai business secretary Co., Ltd.) Applicant before: HESVIT HEALTH TECH CO., LTD. |
|
| TA01 | Transfer of patent application right | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20160727 |
|
| RJ01 | Rejection of invention patent application after publication |