CN105989066A - Information processing method and device - Google Patents
Information processing method and device Download PDFInfo
- Publication number
- CN105989066A CN105989066A CN201510068060.1A CN201510068060A CN105989066A CN 105989066 A CN105989066 A CN 105989066A CN 201510068060 A CN201510068060 A CN 201510068060A CN 105989066 A CN105989066 A CN 105989066A
- Authority
- CN
- China
- Prior art keywords
- target information
- information
- ranking factor
- coupling
- factor value
- 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
Landscapes
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The embodiment of the invention provides an information processing method and device. The information processing method comprises the following steps: acquiring a sorting factor of target information, wherein the sorting factor comprises at least two of rank of a user, number of fans of the user, number of forwarding, number of comments, problem types, emotion nature and wait processing time; determining a sorting factor value corresponding to the sorting factor of the target information; according to the sorting factor value and weight of the sorting factor, calculating sensitivity of the target information; and sorting the target information according to the sensitivity of the target information. The information processing method has the advantages that accuracy on sorting of the target information is improved, timely and effectively processing on information is guaranteed and satisfaction of the user is improved.
Description
Technical field
The application relates to technical field of data processing, particularly relates to a kind of information processing method and a kind of letter
Breath processing means.
Background technology
Along with developing rapidly of Internet technology, the spread speed of information is increased dramatically.The common people are permissible
By various information exchange platforms, such as microblogging etc., the information received is commented on and forwards.
Wherein, public feelings information is to describe a kind of of public sentiment and reflection, theoretically, is in common people society
Can political attitude collection, arrange, analyze, report and submit, utilize and in feedack motor process, use
To objectively respond the information of public sentiment state and motion conditions thereof, message, message, information, instruction, data
And signal.
In public feelings information processing procedure, to the ordering requirements of public feelings information it is: " page 1 effectiveness " is (front
Article ten).Information public sentiment the highest grade is needed to be illustrated in foremost, it is ensured that urgent public sentiment finds at first,
Processed the soonest.In other information processes, the problem that information sorting can be related to too,
To know common people's information of interest etc..
And at present in information process, more single to the attribute of information sorting institute foundation, it is mostly single
Pure carry out message level sequence based on user property factors such as user gradation or vermicelli numbers, such as, propagate or comment
The user gradation of this information of opinion is the highest, then the sequence of this information is the most forward.But, the method cannot be true
The sensitivity of reflection information, relatively low to the precision of information sorting, and then easily cause information processing improper.
Summary of the invention
The embodiment of the present application technical problem to be solved is to provide a kind of information processing method, it is possible to increase
The precision of information sorting.
Accordingly, the embodiment of the present application additionally provides a kind of information processor, in order to ensure said method
Realization and application.
In order to solve the problems referred to above, this application discloses a kind of information processing method, including:
Obtaining the ranking factor of target information, described ranking factor includes the user etc. of described target information
Level, user's vermicelli number, forward number, comment number, problem types, emotion attribute, etc. in the pending time
At least two；
Determine the ranking factor value that the ranking factor of described target information is corresponding；
According to described ranking factor value and the weight of ranking factor, calculate the sensitivity of described target information；
According to the sensitivity of described target information, described target information is ranked up.
Further, when the ranking factor of described target information is problem types, described determine described target
The ranking factor value that the ranking factor of information is corresponding, including:
Described target information is carried out information content coupling；
Adding up the information content of each coupling target information, wherein, described coupling target information is for having mutually
The target information of the information content of coupling；
Judge that whether the information content of described coupling target information is more than or equal to predetermined threshold value；
The most then according to presetting rule arrange sequence corresponding to the problem types of described coupling target information because of
Subvalue.
Further, described the row that the problem types of described coupling target information is corresponding is set according to presetting rule
Sequence factor values, including:
Ranking factor value corresponding for the problem types of described coupling target information is set to emergent specific because of
Subvalue.
Further, described the row that the problem types of described coupling target information is corresponding is set according to presetting rule
Sequence factor values, including:
According to the corresponding relation between presupposed information quantitative range and ranking factor value, and described coupling mesh
The information content of mark information, determines the ranking factor value that the problem types of described coupling target information is corresponding.
Further, described method also includes:
When the information content of described coupling target information is less than described predetermined threshold value, according to default problem
Corresponding relation between type and ranking factor value, determines the row that the problem types of described target information is corresponding
Sequence factor values.
Further, described described target information is carried out information content coupling, including:
Trigger every preset time period and described target information is carried out information content coupling.
Further, described described target information is carried out information content coupling, including:
The described target information obtained in preset time period is carried out information content coupling.
Disclosed herein as well is a kind of information processor, including:
Factor acquirement unit, is configured to obtain the ranking factor of target information, and described ranking factor includes
The user gradation of described target information, user's vermicelli number, forwarding number, comment number, problem types, emotion
Attribute, etc. at least two in the pending time；
Factor values determines unit, be configured to determine that sequence that the ranking factor of described target information is corresponding because of
Subvalue；
Sensitivity computing unit, is configured to according to described ranking factor value and the weight of ranking factor, meter
Calculate the sensitivity of described target information；
Information sorting unit, is configured to the sensitivity according to described target information and enters described target information
Row sequence.
Further, when the ranking factor of described target information is problem types, described factor values determines list
Unit includes:
Coupling subelement, is configured to described target information is carried out information content coupling；
Statistics subelement, is configured to add up the information content of each coupling target information, wherein, described
Joining target information is the target information with the information content being mutually matched；
Judge subelement, be configured to judge the information content of described coupling target information whether more than or etc.
In predetermined threshold value；
Determine subelement, be configured as described judgement subelement and judge the information of described coupling target information
When quantity is more than or equal to predetermined threshold value, the problem class of described coupling target information is set according to presetting rule
The ranking factor value that type is corresponding.
Further, described determine subelement, be specifically configured to when described judgement subelement judges described
When joining the information content of target information more than or equal to predetermined threshold value, by the problem of described coupling target information
Ranking factor value corresponding to type is set to emergent specificity factor value.
Further, described determine subelement, be additionally configured to when the information content of described coupling target information
During less than described predetermined threshold value, according to the corresponding relation between default problem types and ranking factor value,
Determine the ranking factor value that the problem types of described target information is corresponding.
Compared with prior art, the embodiment of the present application includes advantages below:
The embodiment of the present application is by considering multiple ranking factor such as user gradation, problem types, and root
It is ranked up the weight configuration of the factor according to different actual demands, truly reflects the sensitivity of target information,
Thus improve the precision to target information sequence, it is ensured that and the timely and effective process of information, improve
User satisfaction.
Accompanying drawing explanation
Fig. 1 is the flow chart of steps of a kind of information processing method embodiment of the application；
Fig. 2 is the side that a kind of in the application determines the ranking factor value that the ranking factor of target information is corresponding
The flow chart of steps of method embodiment；
Fig. 3 is the structured flowchart of a kind of information processor embodiment of the application；
Fig. 4 is the structured flowchart that a kind of factor values in the application determines unit embodiment.
Detailed description of the invention
Understandable, below in conjunction with the accompanying drawings for enabling the above-mentioned purpose of the application, feature and advantage to become apparent from
With detailed description of the invention, the application is described in further detail.
With reference to Fig. 1, it is shown that the flow chart of steps of a kind of information processing method embodiment of the application, tool
Body may include steps of:
Step 101, obtains the ranking factor of target information, and this ranking factor includes the user of target information
Grade, user's vermicelli number, forward number, comment number, problem types, emotion attribute, etc. the pending time
In at least two.
In the present embodiment, the information processor performing this information processing method can be an information monitoring system
A part in system itself or this system, this information monitoring system can be specifically public sentiment monitoring system.
In this step, the two or more target informations being ranked up for needs, at this information
First reason device obtains the ranking factor of target information.Wherein, target information is acute pyogenic infection of finger tip, the most permissible
It it is public feelings information etc..Ranking factor is to affect the factor that target information puts in order, in the present embodiment, and institute
The arrangement factor of target information to be obtained includes the user gradation of target information, user's vermicelli number, forwarding
Number, comment number, problem types, emotion attribute, etc. at least two in the pending time.
Wherein, user gradation can be to send this target information first, or forwards this target information, or comments
The grade of the user that this target information of opinion etc. is associated with this target information, user gradation can include especially
Pay close attention to user, enterprise VIP, individual VIP, domestic consumer, black list user, network navy etc..
User's vermicelli number can be to send this target information first, or forwards this target information, or comment should
The vermicelli number of the user that target information etc. are associated with this target information.
Forward number be the number of times that this target information is forwarded, comment number be this target information commented on time
Number.
The grade of this user can be evaluated by network interaction platforms etc., and unites user's vermicelli number
Meter, also can add up the forwarding number of target information and comment number respectively, and this information processor is permissible
Directly obtain this user gradation, user's vermicelli number from network interaction platform, forward number and comment number.
Such as, this information processor can push from the background server of microblogging interface microblogging and subscribe to
Real time information, this device according to push real time information real-time update user profile (user gradation, use
Family vermicelli number) and micro-blog information (if forward microblogging, comment then update former microblogging corresponding forward number and
Comment number).
Can be with pre-set various problems type in this information processor, every kind of problem types correspondence one
Group or organize key word more.Concrete, problem types simply can be divided into excessive risk rank and low-risk
Ranks etc., key word corresponding to excessive risk rank can comprise sensitive politics vocabulary etc..Obtain at this device
After target information, this target information can be carried out such as the analysis means such as semantic analysis, extract semantics recognition
The key word gone out, according between the key word that the key word extracted is corresponding with default various problem typess
Matching degree, it may be determined which kind of problem types is target information belong to.
Emotion attribute is similar with problem types, can be with pre-set multiple emotion in this information processor
Attribute, the most negatively, neutral, front.After this device obtains target information, this target can be believed
Breath carries out sentiment analysis, determines the emotion attribute of target information according to analysis result.
Above-mentioned semantic analysis and sentiment analysis method all can use existing method, such as, divide based on semanteme
Analysis model and sentiment analysis model are analyzed.
Can be set as required etc. the pending time, for example, it is possible to by target information issue time
Between and this device perform the time difference between the time that this target information is processed by this method as this
Target information etc. the pending time.
Certainly, this ranking factor can also include other factors, such as user's service log, user's history
Satisfaction records etc., will not enumerate herein.
Step 102, determines the ranking factor value that the ranking factor of target information is corresponding.
Information processor can determine, according to preset rules, the row that the ranking factor of target information is corresponding
Sequence factor values.
Wherein, this preset rules can be to be previously provided with different numerical value or the numerical range of ranking factor,
Or the ranking factor value of different classes of correspondence.Such as:
For user gradation, can be the highest with the ranking factor value of pre-set user the highest grade correspondence, such as,
User gradation can be followed successively by special concern user, enterprise VIP, individual VIP from high to low, commonly use
Family, black list user, network navy etc., can be set to 1, lowermost level by five-star user gradation
User gradation be set to 0.1, middle user gradation divides in the range of 0.1～1 step by step.
For user's vermicelli number, the corresponding different ranking factor value of different numerical range, numerical value can be set
The biggest ranking factor value is the biggest, such as: 0～1000 vermicelli number correspondence ranking factor values be 0.1,10,000,000 with
Upper vermicelli number correspondence ranking factor value is the multiple vermicelli number numerical rangies between 1,1000 to 1,000 ten thousand
Divide step by step in 0.1～1.
For forwarding number, can be similar with user's vermicelli number, it is also possible to different numerical range correspondence is set not
Same ranking factor value, numerical value the biggest ranking factor value is the biggest, such as: 0～1000 forward the sequence of number correspondences
Factor values be 0.1, more than 10,000,000 forward number correspondence ranking factor values be between 1,1000 to 1,000 ten thousand
Multiple forwarding number numerical rangies divide step by step in 0.1～1.
For comment number, can be similar with forwarding number, it is also possible to it is corresponding different that different numerical range is set
Ranking factor value, numerical value the biggest ranking factor value is the biggest, such as: 0～100 comment number correspondence ranking factor
Value be 0.1, more than 10000 comment number correspondence ranking factor values be 1, multiple between 100 to 10000 comment
Opinion number numerical range divides step by step in 0.1～1.
For problem types, it is the biggest that risk class the highest ranking factor value can be set, such as, excessive risk
The ranking factor value of rank is 1, and the ranking factor value of risk rank is 0.5, the sequence of low-risk rank
Factor values is 0.1.
For emotion attribute, can arrange negative ranking factor value is 0.1, neutral ranking factor value
Being 0.5, the ranking factor value in front is 1.
For etc. the pending time, can be similar with comment number, it is also possible to different numerical range correspondence is set
Different ranking factor values, numerical value the biggest ranking factor value is the biggest, such as, corresponding sequence in 0～10 minute because of
Subvalue is that more than 0.1,6 hours corresponding ranking factor values are when being multiple between 1,10 minutes to 6 hours
Between numerical range divide step by step in 0.1～1.
In this step, information processor obtain target information above-mentioned at least two ranking factor after,
The ranking factor value that each ranking factor of each target information is corresponding can be determined according to this preset rules.Example
As, wherein the ranking factor of a target information be user gradation be individual VIP, user's vermicelli number is
500, forwarding number is 1000, and comment number is 20, and problem types is low-risk rank, during emotion attribute is
Property, waiting the pending time is 1 hour, then may determine that the ranking factor value that each ranking factor is corresponding is:
The ranking factor value of user gradation is 0.5, and the ranking factor value of user's vermicelli number is 0.1, forwards the row of number
Sequence factor values is 0.1, and the ranking factor value of comment number is 0.1, and the ranking factor value of problem types is 0.1,
The ranking factor value of emotion attribute is 0.5, and the ranking factor value waiting the pending time is 0.4.
In other embodiments, this information processor can also be according to the quantity of target information or kind etc.
Factor determines the ranking factor value that the ranking factor of target information is corresponding in real time, specifically refers to subsequent implementation
The description of example.
Step 103, according to ranking factor value and the weight of ranking factor, calculates the sensitivity of target information.
This information processor can be previously provided with the fixing weight of each ranking factor, it is also possible to according to
The situations such as the quantity kind of target information arrange the weight of each ranking factor in real time.
This information processor is knowing ranking factor value and the ranking factor of each ranking factor of target information
Weight after, the sensitivity of this target information can be calculated.
The calculating of concrete sensitivity (Si) can use below equation:
Si=∑ (Wx*Px)
Wherein, Si is the sensitivity of target information i；Wx is the weight of ranking factor x；Px is sequence
The ranking factor value of factor x, ranking factor x can be the user gradation of target information, user's vermicelli number,
Forward number, comment number, problem types, emotion attribute, etc. arbitrary in the ranking factor such as pending time
Individual.
By calculate the product of ranking factor value and the weight of each ranking factor of target information and
Obtain the sensitivity of this target information.After the sensitivity obtaining all target informations, can be ranked up.
Step 104, is ranked up target information according to the sensitivity of target information.
Target information can be ranked up on earth by height by this step according to the sensitivity of target information.Obtaining
After obtaining this sequence, target information can be entered by this information processor or other device according to this ranking results
Row processes.
The embodiment of the present application is by considering multiple ranking factor such as user gradation, problem types, and root
It is ranked up the weight configuration of the factor according to different actual demands, truly reflects the sensitivity of target information,
Thus improve the precision to target information sequence, it is ensured that and the timely and effective process of information, improve
User satisfaction.
And, by the real-time update forwarding the ranking factor such as number, comment number, it is possible to achieve to target
The real-time update of information sensitivity, and then ensure that the high-timeliness that target information sorts.
In another embodiment of the application, when the ranking factor of target information includes problem types, on
State the process of the ranking factor value determining that the ranking factor of target information is corresponding, as in figure 2 it is shown, can enter
One step includes:
Step 201, carries out information content coupling to target information.
In this step, information processor carries out information content coupling between target information, to determine mesh
In mark information, which information has the information content being mutually matched.Wherein, will have the information being mutually matched
The target information of content is designated as mating target information.
This method carrying out information content coupling has multiple, can be specifically to extract the pass in each target information
Keyword, then carries out Keywords matching, or directly calculate between the information content of target information similar
Degree etc., matching degree threshold value or similarity threshold can be set, as long as the matching degree between key word more than
Similarity between degree of joining threshold value or target information more than similarity threshold i.e. it is believed that two target informations
Between there is the information content being mutually matched.
This step can be to trigger every preset time period target information is carried out information content coupling.Example
As, triggered every 10 minutes and target information is carried out information content coupling.
It addition, when information processor carries out information content coupling to target information, can be to time default
Between the target information that obtains in section carry out information content coupling, such as, to 24 hours interior target informations
Carry out information content coupling.
Step 202, adds up the information content of each coupling target information, and wherein, coupling target information is tool
There is the target information of the information content being mutually matched.
After upper step carries out information content coupling, in this step, this information processor adds up each coupling
The information content of target information, such as, has the information content phase of 4 target informations in all target informations
Coupling mutually, then the information content of this coupling target information is 4.
Step 203, it is judged that whether the information content of coupling target information is more than or equal to predetermined threshold value.
Information processor can pre-set a threshold value, when coupling target information information content more than or
During equal to predetermined threshold value, switch to contingency mode, perform step 204；Information when coupling target information
When quantity is less than predetermined threshold value, switch to general mode, perform step 205.
Step 204, arranges the ranking factor corresponding to problem types of coupling target information according to presetting rule
Value.
This step can be directly by ranking factor primary system one corresponding for the problem types of coupling target information
It is set to preset emergent specificity factor value.Can also be according to information content scope and ranking factor value it
Between corresponding relation, and coupling target information information content, determine coupling target information problem
The ranking factor value that type is corresponding.
No matter which kind of mode, the ranking factor value of this coupling target information can be far longer than other sequence because of
The ranking factor value of son, so that the sensitivity with the target information of this problem types is greatly improved, protects
The sorting position demonstrate,proving this target information is forward, is processed by effective concern.
Step 205, according to the corresponding relation between default problem types and ranking factor value, determines mesh
The ranking factor value that the problem types of mark information is corresponding.
When mate target information information content less than predetermined threshold value time, can in the manner previously described, according to
The ranking factor value of correspondence is determined in the problem types of target information.Such as, for problem types, permissible
Arranging risk class the highest ranking factor value the biggest, such as, the ranking factor value of excessive risk rank is 1,
The ranking factor value of risk rank is 0.5, and the ranking factor value of low-risk rank is 0.1.
The present embodiment passes through the information content according to problem types statistical match target information, and according in real time
Scene adaptive adjusts the ranking factor value of problem types, thus realizes the intelligence of high sensitive target information
Identify.
It should be noted that for embodiment of the method, in order to be briefly described, therefore it is all expressed as one it be
The combination of actions of row, but those skilled in the art should know, and the embodiment of the present application is not by described
The restriction of sequence of movement because according to the embodiment of the present application, some step can use other orders or
Person is carried out simultaneously.Secondly, those skilled in the art also should know, embodiment described in this description
Belong to preferred embodiment, necessary to involved action not necessarily the embodiment of the present application.
With reference to Fig. 3, it is shown that the structured flowchart of the application a kind of information processor embodiment, specifically may be used
To include such as lower unit:
Factor acquirement unit 301, is configured to obtain the ranking factor of target information, described ranking factor
Including the user gradation of described target information, user's vermicelli number, forward number, comment number, problem types,
Emotion attribute, etc. at least two in the pending time.
Factor values determines unit 302, is configured to determine that the row that the ranking factor of described target information is corresponding
Sequence factor values.
Sensitivity computing unit 303, is configured to according to described ranking factor value and the weight of ranking factor,
Calculate the sensitivity of described target information.
Information sorting unit 304, is configured to the sensitivity according to described target information and believes described target
Breath is ranked up.
In the embodiment of the present application, this device considers user gradation, problem types etc. by said units
Multiple ranking factor, and the weight configuration of the factor it is ranked up according to different actual demands, truly reflect
The sensitivity of target information, thus improve to target information sequence precision, it is ensured that information and
Shi Youxiao process, improves user satisfaction.
And, by the real-time update forwarding the ranking factor such as number, comment number, it is possible to achieve to target
The real-time update of information sensitivity, and then ensure that the high-timeliness that target information sorts.
In another embodiment of the application, when the ranking factor of target information is problem types, such as figure
Shown in 4, factor values determines that unit 302 may further include:
Coupling subelement 401, is configured to described target information is carried out information content coupling.
Statistics subelement 402, is configured to add up the information content of each coupling target information, wherein, institute
Stating coupling target information is the target information with the information content being mutually matched.
Judge subelement 403, be configured to judge whether the information content of described coupling target information is more than
Or equal to predetermined threshold value.
Determine subelement 404, be configured as described judgement subelement and judge described coupling target information
When information content is more than or equal to predetermined threshold value, asking of described coupling target information is set according to presetting rule
The ranking factor value that topic type is corresponding.
Wherein it is determined that subelement 404, can be specifically configured to when described judgement subelement 403 judges
When the information content of described coupling target information is more than or equal to predetermined threshold value, by described coupling target information
Ranking factor value corresponding to problem types be set to emergent specificity factor value, or, according to presupposed information
Corresponding relation between quantitative range and ranking factor value, and the Information Number of described coupling target information
Amount, determines the ranking factor value that the problem types of described coupling target information is corresponding.
Determine subelement 404, it is also possible to be configured as judging that subelement 403 judges described coupling target
When the information content of information is less than described predetermined threshold value, according to default problem types and ranking factor value it
Between corresponding relation, determine the ranking factor value that the problem types of described target information is corresponding.
The present embodiment determines the unit information according to problem types statistical match target information by factor values
Quantity, and according to the ranking factor value of real-time scene self-adaptative adjustment problem types, thus realize high sensitive
The Intelligent Recognition of degree target information.
In another embodiment of the application, coupling subelement 401 specifically can be configured to every presetting
Time period triggering carries out information content coupling to described target information.
In another embodiment of the application, coupling subelement 401 specifically can be configured to time default
Between the described target information that obtains in section carry out information content coupling.
The embodiment of the present application additionally provides a kind of electronic equipment, including memorizer and processor.
Processor is connected with each other by bus with memorizer；Bus can be isa bus, pci bus or
Eisa bus etc..Described bus can be divided into address bus, data/address bus, control bus etc..
Wherein, memorizer is for one section of program of storage, and specifically, program can include program code, institute
State program code and include computer-managed instruction.Memorizer may comprise high-speed RAM memorizer, it is possible to
Can also include nonvolatile memory (non-volatile memory), for example, at least one disk memory.
Processor is used for reading the program code in memorizer, execution following steps:
Obtaining the ranking factor of target information, described ranking factor includes the user etc. of described target information
Level, user's vermicelli number, forward number, comment number, problem types, emotion attribute, etc. in the pending time
At least two；
Determine the ranking factor value that the ranking factor of described target information is corresponding；
According to described ranking factor value and the weight of ranking factor, calculate the sensitivity of described target information；
According to the sensitivity of described target information, described target information is ranked up.
For device embodiment, due to itself and embodiment of the method basic simlarity, so the comparison described
Simply, relevant part sees the part of embodiment of the method and illustrates.
Each embodiment in this specification all uses the mode gone forward one by one to describe, and each embodiment stresses
Be all the difference with other embodiments, between each embodiment, identical similar part sees mutually
?.
Those skilled in the art are it should be appreciated that the embodiment of the embodiment of the present application can be provided as method, dress
Put or computer program.Therefore, the embodiment of the present application can use complete hardware embodiment, completely
Software implementation or the form of the embodiment in terms of combining software and hardware.And, the embodiment of the present application
Can use and can be situated between with storage at one or more computers wherein including computer usable program code
The upper computer journey implemented of matter (including but not limited to disk memory, CD-ROM, optical memory etc.)
The form of sequence product.
In a typical configuration, described computer equipment includes one or more processor
(CPU), input/output interface, network interface and internal memory.Internal memory potentially includes computer-readable medium
In volatile memory, the shape such as random access memory (RAM) and/or Nonvolatile memory
Formula, such as read only memory (ROM) or flash memory (flash RAM).Internal memory is computer-readable medium
Example.Computer-readable medium includes removable media permanent and non-permanent, removable and non-
Information storage can be realized by any method or technology.Information can be computer-readable instruction,
Data structure, the module of program or other data.The example of the storage medium of computer includes, but
Be not limited to phase transition internal memory (PRAM), static RAM (SRAM), dynamic random are deposited
Access to memory (DRAM), other kinds of random access memory (RAM), read only memory
(ROM), Electrically Erasable Read Only Memory (EEPROM), fast flash memory bank or other in
Deposit technology, read-only optical disc read only memory (CD-ROM), digital versatile disc (DVD) or other
Optical storage, magnetic cassette tape, tape magnetic rigid disk storage other magnetic storage apparatus or any its
His non-transmission medium, can be used for the information that storage can be accessed by a computing device.According to herein
Defining, computer-readable medium does not include the computer readable media (transitory media) of non-standing,
Data signal and carrier wave such as modulation.
The embodiment of the present application is with reference to the method according to the embodiment of the present application, terminal unit (system) and meter
The flow chart of calculation machine program product and/or block diagram describe.It should be understood that can be by computer program instructions
Each flow process in flowchart and/or block diagram and/or square frame and flow chart and/or square frame
Flow process in figure and/or the combination of square frame.Can provide these computer program instructions to general purpose computer,
The processor of special-purpose computer, Embedded Processor or other programmable data processing terminal equipment is to produce
One machine so that performed by the processor of computer or other programmable data processing terminal equipment
Instruction produce for realizing at one flow process of flow chart or multiple flow process and/or one square frame of block diagram or
The device of the function specified in multiple square frames.
These computer program instructions may be alternatively stored in and computer or other programmable datas can be guided to process
In the computer-readable memory that terminal unit works in a specific way so that be stored in this computer-readable
Instruction in memorizer produces the manufacture including command device, and this command device realizes flow chart one
The function specified in flow process or multiple flow process and/or one square frame of block diagram or multiple square frame.
These computer program instructions also can be loaded into computer or other programmable data processing terminals set
Standby upper so that on computer or other programmable terminal equipment, to perform sequence of operations step in terms of producing
The process that calculation machine realizes, thus the instruction performed on computer or other programmable terminal equipment provides and uses
In realizing in one flow process of flow chart or multiple flow process and/or one square frame of block diagram or multiple square frame
The step of the function specified.
Although having been described for the preferred embodiment of the embodiment of the present application, but those skilled in the art being once
Know basic creative concept, then these embodiments can be made other change and amendment.So,
Claims are intended to be construed to include preferred embodiment and fall into the institute of the embodiment of the present application scope
There are change and amendment.
Finally, in addition it is also necessary to explanation, in this article, the relational terms of such as first and second or the like
It is used merely to separate an entity or operation with another entity or operating space, and not necessarily requires
Or imply relation or the order that there is any this reality between these entities or operation.And, art
Language " includes ", " comprising " or its any other variant are intended to comprising of nonexcludability, so that
Process, method, article or terminal unit including a series of key elements not only include those key elements, and
Also include other key elements being not expressly set out, or also include for this process, method, article or
The key element that person's terminal unit is intrinsic.In the case of there is no more restriction, statement " include one
It is individual ... " key element that limits, it is not excluded that including the process of described key element, method, article or end
End equipment there is also other identical element.
Above to a kind of information processing method provided herein and a kind of information processor, carry out
Being discussed in detail, principle and the embodiment of the application are set forth by specific case used herein,
The explanation of above example is only intended to help and understands the present processes and core concept thereof；Meanwhile, right
In one of ordinary skill in the art, according to the thought of the application, in detailed description of the invention and range of application
On all will change, in sum, this specification content should not be construed as the restriction to the application.
Claims (11)
1. an information processing method, it is characterised in that including:
Obtaining the ranking factor of target information, described ranking factor includes the user etc. of described target information
Level, user's vermicelli number, forward number, comment number, problem types, emotion attribute, etc. in the pending time
At least two；
Determine the ranking factor value that the ranking factor of described target information is corresponding；
According to described ranking factor value and the weight of ranking factor, calculate the sensitivity of described target information；
According to the sensitivity of described target information, described target information is ranked up.
Method the most according to claim 1, it is characterised in that when the sequence of described target information
When the factor is problem types, the ranking factor value that the described ranking factor determining described target information is corresponding,
Including:
Described target information is carried out information content coupling；
Adding up the information content of each coupling target information, wherein, described coupling target information is for having mutually
The target information of the information content of coupling；
Judge that whether the information content of described coupling target information is more than or equal to predetermined threshold value；
The most then according to presetting rule arrange sequence corresponding to the problem types of described coupling target information because of
Subvalue.
Method the most according to claim 2, it is characterised in that described according to presetting rule setting
The ranking factor value that the problem types of described coupling target information is corresponding, including:
Ranking factor value corresponding for the problem types of described coupling target information is set to emergent specific because of
Subvalue.
Method the most according to claim 2, it is characterised in that described according to presetting rule setting
The ranking factor value that the problem types of described coupling target information is corresponding, including:
According to the corresponding relation between presupposed information quantitative range and ranking factor value, and described coupling mesh
The information content of mark information, determines the ranking factor value that the problem types of described coupling target information is corresponding.
Method the most according to claim 2, it is characterised in that described method also includes:
When the information content of described coupling target information is less than described predetermined threshold value, according to default problem
Corresponding relation between type and ranking factor value, determines the row that the problem types of described target information is corresponding
Sequence factor values.
Method the most as claimed in any of claims 2 to 5, it is characterised in that described right
Described target information carries out information content coupling, including:
Trigger every preset time period and described target information is carried out information content coupling.
Method the most as claimed in any of claims 2 to 5, it is characterised in that described right
Described target information carries out information content coupling, including:
The described target information obtained in preset time period is carried out information content coupling.
8. an information processor, it is characterised in that including:
Factor acquirement unit, is configured to obtain the ranking factor of target information, and described ranking factor includes
The user gradation of described target information, user's vermicelli number, forwarding number, comment number, problem types, emotion
Attribute, etc. at least two in the pending time；
Factor values determines unit, be configured to determine that sequence that the ranking factor of described target information is corresponding because of
Subvalue；
Sensitivity computing unit, is configured to according to described ranking factor value and the weight of ranking factor, meter
Calculate the sensitivity of described target information；
Information sorting unit, is configured to the sensitivity according to described target information and enters described target information
Row sequence.
Device the most according to claim 8, it is characterised in that when the sequence of described target information
When the factor is problem types, described factor values determines that unit includes:
Coupling subelement, is configured to described target information is carried out information content coupling；
Statistics subelement, is configured to add up the information content of each coupling target information, wherein, described
Joining target information is the target information with the information content being mutually matched；
Judge subelement, be configured to judge the information content of described coupling target information whether more than or etc.
In predetermined threshold value；
Determine subelement, be configured as described judgement subelement and judge the information of described coupling target information
When quantity is more than or equal to predetermined threshold value, the problem class of described coupling target information is set according to presetting rule
The ranking factor value that type is corresponding.
Device the most according to claim 9, it is characterised in that
Described determine subelement, be specifically configured to when described judgement subelement judges described coupling target letter
When the information content of breath is more than or equal to predetermined threshold value, the problem types of described coupling target information is corresponding
Ranking factor value be set to emergent specificity factor value.
11. according to the device described in claim 9 or 10, it is characterised in that
Described determine subelement, be additionally configured to when the information content of described coupling target information is less than described
During predetermined threshold value, according to the corresponding relation between default problem types and ranking factor value, determine described
The ranking factor value that the problem types of target information is corresponding.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510068060.1A CN105989066A (en) | 2015-02-09 | 2015-02-09 | Information processing method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510068060.1A CN105989066A (en) | 2015-02-09 | 2015-02-09 | Information processing method and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN105989066A true CN105989066A (en) | 2016-10-05 |
Family
ID=57041585
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510068060.1A Pending CN105989066A (en) | 2015-02-09 | 2015-02-09 | Information processing method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105989066A (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107368510A (en) * | 2017-04-10 | 2017-11-21 | 口碑控股有限公司 | A kind of shop search ordering method and device |
| CN108170689A (en) * | 2016-12-07 | 2018-06-15 | 富士通株式会社 | The information processing unit and information processing method of semantization are carried out to entity |
| CN110597882A (en) * | 2019-09-19 | 2019-12-20 | 北京明略软件系统有限公司 | Data processing method and device, storage medium and electronic device |
| CN112732766A (en) * | 2020-12-30 | 2021-04-30 | 绿盟科技集团股份有限公司 | Data sorting method and device, electronic equipment and storage medium |
| CN112783468A (en) * | 2019-11-06 | 2021-05-11 | 北京沃东天骏信息技术有限公司 | Target object sorting method and device |
| CN113645508A (en) * | 2021-08-10 | 2021-11-12 | 北京读我科技有限公司 | Message output method, device and system |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102945290A (en) * | 2012-12-03 | 2013-02-27 | 北京奇虎科技有限公司 | Hot microblog topic digging device and method |
| CN102982178A (en) * | 2012-12-17 | 2013-03-20 | 北京奇虎科技有限公司 | Picture searching method, device and system |
| CN103955547A (en) * | 2014-05-22 | 2014-07-30 | 厦门市美亚柏科信息股份有限公司 | Method and system for searching forum hot-posts |
-
2015
- 2015-02-09 CN CN201510068060.1A patent/CN105989066A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102945290A (en) * | 2012-12-03 | 2013-02-27 | 北京奇虎科技有限公司 | Hot microblog topic digging device and method |
| CN102982178A (en) * | 2012-12-17 | 2013-03-20 | 北京奇虎科技有限公司 | Picture searching method, device and system |
| CN103955547A (en) * | 2014-05-22 | 2014-07-30 | 厦门市美亚柏科信息股份有限公司 | Method and system for searching forum hot-posts |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108170689A (en) * | 2016-12-07 | 2018-06-15 | 富士通株式会社 | The information processing unit and information processing method of semantization are carried out to entity |
| CN107368510A (en) * | 2017-04-10 | 2017-11-21 | 口碑控股有限公司 | A kind of shop search ordering method and device |
| CN110597882A (en) * | 2019-09-19 | 2019-12-20 | 北京明略软件系统有限公司 | Data processing method and device, storage medium and electronic device |
| CN112783468A (en) * | 2019-11-06 | 2021-05-11 | 北京沃东天骏信息技术有限公司 | Target object sorting method and device |
| CN112732766A (en) * | 2020-12-30 | 2021-04-30 | 绿盟科技集团股份有限公司 | Data sorting method and device, electronic equipment and storage medium |
| CN113645508A (en) * | 2021-08-10 | 2021-11-12 | 北京读我科技有限公司 | Message output method, device and system |
| CN113645508B (en) * | 2021-08-10 | 2023-09-19 | 北京读我科技有限公司 | Message output method, device and system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| TWI777010B (en) | Prediction of information conversion rate, information recommendation method and device | |
| WO2022141861A1 (en) | Emotion classification method and apparatus, electronic device, and storage medium | |
| JP5736469B2 (en) | Search keyword recommendation based on user intention | |
| US8290927B2 (en) | Method and apparatus for rating user generated content in search results | |
| CN109634698B (en) | Menu display method and device, computer equipment and storage medium | |
| CN105989066A (en) | Information processing method and device | |
| US11042662B2 (en) | Data aggregation system for enabling query operations on restricted data that originates from multiple independent multiple sources | |
| CN110674408B (en) | Service platform, and real-time generation method and device of training sample | |
| CN113688313A (en) | Training method of prediction model, information pushing method and device | |
| CN109447469A (en) | A kind of Method for text detection, device and equipment | |
| US11275748B2 (en) | Influence score of a social media domain | |
| CN110489449B (en) | Chart recommendation method and device and electronic equipment | |
| CN108416616A (en) | The sort method and device of complaints and denunciation classification | |
| CN111680165B (en) | Information matching method and device, readable storage medium and electronic equipment | |
| CN110765348B (en) | Hot word recommendation method and device, electronic equipment and storage medium | |
| CN113535817B (en) | Feature broad table generation and service processing model training method and device | |
| JP2020512651A (en) | Search method, device, and non-transitory computer-readable storage medium | |
| US9582586B2 (en) | Massive rule-based classification engine | |
| CN117076650B (en) | Intelligent dialogue method, device, medium and equipment based on large language model | |
| CN110263817B (en) | Risk grade classification method and device based on user account | |
| CN111782946A (en) | Book friend recommendation method, calculation device and computer storage medium | |
| CN110532773B (en) | Malicious access behavior identification method, data processing method, device and equipment | |
| CN113935788A (en) | Model evaluation method, device, equipment and computer readable storage medium | |
| CN111639269A (en) | Site recommendation method and device | |
| CN114861043A (en) | Model training and recommended position determining method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20161005 |