CN106055657B - Viewing index assessment system for specific crowd - Google Patents
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- CN106055657B CN106055657B CN201610386127.0A CN201610386127A CN106055657B CN 106055657 B CN106055657 B CN 106055657B CN 201610386127 A CN201610386127 A CN 201610386127A CN 106055657 B CN106055657 B CN 106055657B
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
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- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
- G06F16/78—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
- G06F16/7867—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using information manually generated, e.g. tags, keywords, comments, title and artist information, manually generated time, location and usage information, user ratings
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Abstract
The present invention relates to the system that one kind can obtain specific crowd viewing evaluation number, specifically a kind of viewing index assessment systems for specific crowd.By the identity information and attribute information of the network user, target group are filtered out, it is weighted to calculate the user's viewing index for obtaining a certain film in the film comment made by these target group.It can be used for instructing the work such as the production, publicity, distribution of film.
Description
Technical field
The present invention relates to the systems that one kind can obtain specific crowd viewing evaluation number, specifically a kind of to be used for particular person
The viewing index assessment system of group.
Background technique
Hot attraction a large amount of capital of the hot exception of film market in recent years, market enters video display industry, everybody attention
Also following.People also more pay close attention to the development in film market future thus, it is desirable to be able to market needs are catered to, instantly
Or future has a share.The viewing data for pointedly collecting, arranging various different groups are required, thus with more
Careful data, which are analyzed, provides guiding opinion for the creation and the market promotion of film.Pass through nearly crowd's educational culture journey of booking in 2 years
Degree statistics can significantly find out that main force viewing crowd is the academic crowd of training undergraduate course or more.Especially student enrollment is not to
The development and Chinese forming for viewing group habit for carrying out movie market in China have great importance.
Summary of the invention
The purpose of the present invention is providing a kind of viewing index assessment system for specific crowd for film worker, make it
It can instruct the work such as the production, publicity, distribution of film.
Viewing index assessment system of the present invention for specific crowd, characterized by comprising:
System database, including the User Information Database for storing userspersonal information and for storing user's
The customer attribute information database of attribute information is established mapping and is closed between User Information Database and customer attribute information database
System；
The filter of improper user, for reading the attribute of user from customer attribute information database, extraction is wherein accorded with
The data of special group attribute are closed, while extracting corresponding userspersonal information from User Information Database, are obtained specific
The userspersonal information library of group；
Data grabber processor, for grabbing the user of the special group from web film and film social media
Each user is to the historical review data of any film in people's information bank, using normal distribution principle identify normal users and it is non-just
Common family, is identified as normal users for the user of historical review data fit normal distribution principle, is otherwise improper user, and
Improper user is rejected from the userspersonal information library of special group；
User's Screening Treatment device, the society of each user from the userspersonal information library for grabbing special group in Internet resources
The attribute information of object is handed over, the social object and statistical magnitude for wherein meeting special group attribute are chosen, when the quantity of statistics is super
When crossing given threshold, selected special group user is marked the user as, the step is repeated, until the user of special group
Whole users screening in personal information library finishes；Then the active state of selected special group user is obtained from Internet resources
Information, wherein active state meets the user of mechanics for selection, labels it as any active ues of special group；For specific
Any active ues of group, user's Screening Treatment device compares its userspersonal information, for meeting the user of consistency criterion,
It is defined as repeating account, any active ues for repeating the corresponding multiple special groups of account is merged into one, until all specific
The corresponding customer attribute information of any active ues of group meets unicity judgment criteria, and by the active use of these special groups
Family information is stored in sample of users database；
Sample of users database meets unicity judgment criteria by what the screening of user's Screening Treatment device obtained for storing
Special group any active ues information；
Film comment message handler, any active ues for obtaining each special group in sample of users database are issued
Film comment information obtain the quantitative information table of the user, and will be complete and by the various quantification of targets of the film comment information
The quantitative information table of any active ues of body special group is stored in film review quantitative information library；
Film review quantitative information library, any active ues of all special groups for storing the acquisition of film comment message handler
Quantitative information table.
Evaluation index generator, the quantitative information table that any active ues are extracted from quantitative information library formulate the viewing of the user
Characteristic model, the quantitative information library are the group of people for meeting specific viewing population characteristic and associated film comment
The set of information；The film comment information of the user is compared with viewing characteristic model, obtains the active use using weighting algorithm
Any active ues whole in quantitative information library are added the attention rate numerical value of film by family to the attention rate numerical value of same portion's film,
Specific viewing group is obtained to the attention rate of the film.
The various indexs of the film comment information include but is not limited to type, performer, director, country, standard, date,
The quantization of so-called index, which refers to, to be judged as matching for the information in film comment in relation to These parameters and mismatches two kinds as a result, simultaneously
Every kind of result is given into specific weighted value.
The film comment information includes at least type, performer, director, country, standard, working days several indexs, described to add
Weighing algorithm is attention rate of any active ues to film that the special group is obtained with following formula,
A=(2 (g+s+r+c+t+d)-(Gg+Ss+Rr+Cc+Tt+Dd)) * X,
Wherein
A is attention rate of any active ues to film of the special group
G indicates whether type matches, and 1 represents matching, and 0 represents mismatch, and g represents weight
S indicates whether performer matches, and 1 represents matching, and 0 represents mismatch, behalf weight
R indicates whether director matches, and 1 represents matching, and 0 representative mismatches, and r represents weight
C indicates whether country matches, and 1 represents matching, and 0 representative mismatches, and c represents weight
Whether T presentation format matches, and 1 represents matching, and 0 represents mismatch, and t represents weight
D indicates whether the working days match, and 1 represents matching, and 0 represents mismatch, and d represents weight
X represents the quantization score value of film evaluation, and front comment is 1, and negative reviews are -1, and neutrality comment is 0.
The personal information of the user is the information or code of user identity for identification, including user name, account, is stepped on
Record address, No. IP, identification number, telephone number, duty paragraph, one of Social Security Number or a variety of；The category of the user
Property information refers to the characteristic information for distinguishing user crowd, including the age, gender, occupation, hobby, education level, nationality,
One of religious belief, group, political parties and groups, languages, blood group, the colour of skin are a variety of.
The user includes the title of evaluation object to the historical review data of any film, the type of evaluation object, comments
Valence content, the time for making evaluation, the character quantity of evaluation content, evaluation number.
The mechanics of the user refers to that the regularity of distribution of user's surf time section and user make the time of evaluation
The regularity of distribution of section.
Any active ues by its corresponding multiple special group, which are merged into one and referred to, merges multiple personal information
New personal information is formed afterwards, while forming new attribute information after multiple attribute informations are merged；The consistency judgement mark
Standard refers to user name in userspersonal information, account, entry address, No. IP, identification number, telephone number, duty paragraph, society
One of social security number or taxid or a variety of with uniformity or correlation.
Due to the adoption of the above technical scheme, the present invention obtains the film review of the specific viewing crowds such as university student by Internet resources
Data, and the Data Analysis Services are obtained into this specific crowd to the quantizating index of the attention rate of film, for instructing film
The work such as production, publicity, distribution.
Detailed description of the invention
Fig. 1 is the flow diagram that the data of one embodiment of the invention are extracted.
Specific embodiment
As shown in Figure 1, the viewing index assessment system of the present invention for specific crowd, characterized by comprising:
System database, including the User Information Database 1 for storing userspersonal information and for storing user
Attribute information customer attribute information database 2, established between User Information Database 1 and customer attribute information database 2
Mapping relations；
The personal information of the user is the information or code of user identity for identification, including user name, account, is stepped on
Record address, No. IP, identification number, telephone number, duty paragraph, one of Social Security Number or a variety of；The category of the user
Property information refers to the characteristic information for distinguishing user crowd, including the age, gender, occupation, hobby, education level, nationality,
One of religious belief, group, political parties and groups, languages, blood group, the colour of skin are a variety of.
The filter of improper user, for reading the attribute of user from customer attribute information database, extraction is wherein accorded with
The data of special group attribute are closed, while extracting corresponding userspersonal information from User Information Database, are obtained specific
The userspersonal information library 3 of group；
Data grabber processor, for grabbing the user of the special group from web film and film social media
Each user is to the historical review data 4 of any film in people's information bank 3, identifies normal users and non-using normal distribution principle
The user of historical review data fit normal distribution principle is identified as normal users, is otherwise improper user by normal users
5, and improper user is rejected from the userspersonal information library of special group；Normal users comment film information have with
Lower feature can be in normal distribution trend, various types of comment relative distribution, without concentrations for the scoring of film
The case where.Corpse account and navy account number are that the purpose that the improper user of representative posts is that film is fried to fire or is belittled, and are commented
Divide and mostly concentrate on high sectional and low sectional, neutrality comment is seldom.Most of deadlock can be filtered out using such method
Corpse and navy account number.
The user includes the title of evaluation object, the type of evaluation object, comments to the historical review data 4 of any film
Valence content, the time for making evaluation, the character quantity of evaluation content, evaluation number.
User's Screening Treatment device, each user from the userspersonal information library 3 for grabbing special group in Internet resources
The attribute information 6 of social object chooses the social object and statistical magnitude for wherein meeting special group attribute, when the quantity of statistics
When more than given threshold, selected special group user 7 is marked the user as, the step is repeated, until special group
Whole users screening in userspersonal information library 3 finishes；The social object of any special group is usually all with same type
User based on, for example general university student's account can pay close attention to the accounts such as classmate, teacher, school.By this method may be used
To further confirm that the identity of user, the interference of false account information is rejected.Then selected particular cluster is obtained from Internet resources
The moving state information of body user 7, wherein active state meets the user of mechanics for selection, labels it as special group
Any active ues 8；The mechanics of the user refer to user's surf time section the regularity of distribution and user make evaluation when
Between section the regularity of distribution.Special group often has relatively-stationary mechanics, such as general student users due to work and rest
The limitation of time, online period frequently appear in night or day off.Vest, corpse, navy account number then more multi-activity in work
Make the time of day.
For any active ues of special group, user's Screening Treatment device compares its userspersonal information, consistent for meeting
Property judgment criteria user, be defined as repeating account, any active ues for repeating the corresponding multiple special groups of account merged into
One, until the corresponding customer attribute information of any active ues of whole special groups meets unicity judgment criteria, and by this
Any active ues information of a little special groups is stored in sample of users database；
Any active ues by its corresponding multiple special group, which are merged into one and referred to, merges multiple personal information
New personal information is formed afterwards, while forming new attribute information after multiple attribute informations are merged；The consistency judgement mark
Standard refers to user name in userspersonal information, account, entry address, No. IP, identification number, telephone number, duty paragraph, society
One of social security number or taxid or a variety of with uniformity or correlation.
General ordinary user is the personal information such as the corresponding cell-phone number of an account, and the corresponding hand of multiple accounts
Machine number then probably belongs to vest account situation, only takes a wherein more reasonable user data, and repeated data then can be with
Merging treatment.
It using the information in the information replacement userspersonal information library of sample of users database, and repeats the above steps, directly
To repetition account can not be found；
Sample of users database meets unicity judgment criteria by what the screening of user's Screening Treatment device obtained for storing
Special group any active ues information；
Film comment message handler, any active ues for obtaining each special group in sample of users database are issued
Film comment information obtain the quantitative information table of the user, and will be complete and by the various quantification of targets of the film comment information
The quantitative information table of any active ues of body special group is stored in film review quantitative information library 9；
The various indexs of the film comment information include but is not limited to type, performer, director, country, standard, date,
The quantization of so-called index, which refers to, to be judged as matching for the information in film comment in relation to These parameters and mismatches two kinds as a result, simultaneously
Every kind of result is given into specific weighted value.
Film review quantitative information library, any active ues of all special groups for storing the acquisition of film comment message handler
Quantitative information table.
Evaluation index generator, the quantitative information table that any active ues are extracted from quantitative information library 9 formulate the sight of the user
Shadow characteristic model, the quantitative information library 9 are the group of people and associated film for meeting specific viewing population characteristic
The set of comment information；The film comment information of the user is compared with viewing characteristic model, obtains the work using weighting algorithm
User is jumped to the attention rate numerical value of film, by any active ues whole in quantitative information library 9 to the attention rate numerical value of same portion's film
It is added, obtains specific viewing group to the attention rate of the film.
The film comment information includes at least type, performer, director, country, standard, working days several indexs, type mark
Label can using various classification standards by film be divided into 2D film, 3D film, acrobatic fighting film, love film, historical subject matter, musical film,
Costume film, cartoon etc., performer and director's label are the name of performer and director, including Chinese name and English name respectively；Country
Label is the national title of film making；Standard label is then the data format for shooting film, such as wide screen, high-resolution, HDTV
, DTV, PAL system, NTSC system etc.；Working days label is the period of movie show.
The film comment information includes at least type, performer, director, country, standard, working days several indexs, described to add
Weighing algorithm is attention rate of any active ues to film that the special group is obtained with following formula,
A=(2 (g+s+r+c+t+d)-(Gg+Ss+Rr+Cc+Tt+Dd)) * X,
Wherein
A is attention rate of any active ues to film of the special group
G indicates whether type matches, and 1 represents matching, and 0 represents mismatch, and g represents weight
S indicates whether performer matches, and 1 represents matching, and 0 represents mismatch, behalf weight
R indicates whether director matches, and 1 represents matching, and 0 representative mismatches, and r represents weight
C indicates whether country matches, and 1 represents matching, and 0 representative mismatches, and c represents weight
Whether T presentation format matches, and 1 represents matching, and 0 represents mismatch, and t represents weight
D indicates whether the working days match, and 1 represents matching, and 0 represents mismatch, and d represents weight
X represents the quantization score value of film evaluation, and front comment is 1, and negative reviews are -1, and neutrality comment is 0.Certainly,
It can be using 5 points of systems or the evaluation expression mode of other quantizations.
The basic ideas of this formula are, if a latitude of a film is substantially belonged to match with user tag and be commented
By affirmative is belonged to, the viewing exponential number of weight is doubled for film attention rate.If not only match but front comment,
Increase double numerical value, if comment belongs to negatively, a multiple value is subtracted under match condition, double number is subtracted under mismatch case
Value.
The numerical value of film is finally calculated by the base quantization numerical value and each user for each film that adds up
The viewing index of the specific viewing group of one film.
Claims (7)
1. being used for the viewing index assessment system of specific crowd, characterized by comprising:
System database, including the User Information Database (1) for storing userspersonal information and for storing user's
The customer attribute information database (2) of attribute information, between User Information Database (1) and customer attribute information database (2)
Establish mapping relations；
The filter of improper user, for reading the attribute of user from customer attribute information database, extraction wherein meets spy
Determine the data of group property, while extracting corresponding userspersonal information from User Information Database, obtains special group
Userspersonal information library (3)；
Data grabber processor, the individual subscriber for grabbing the special group from web film and film social media are believed
It ceases in library (3) each user to the historical review data (4) of any film, normal users and non-is identified using normal distribution principle
The user of historical review data fit normal distribution principle is identified as normal users, is otherwise improper user by normal users
(5), it and by improper user is rejected from the userspersonal information library of special group；
User's Screening Treatment device, the society of each user from the userspersonal information library (3) for grabbing special group in Internet resources
The attribute information (6) of object is handed over, the social object and statistical magnitude for wherein meeting special group attribute are chosen, when the quantity of statistics
When more than given threshold, selected special group user (7) are marked the user as, screening step are repeated, until particular cluster
Whole users screening in the userspersonal information library (3) of body finishes；Then selected special group is obtained from Internet resources to use
The moving state information at family (7), wherein active state meets the user of mechanics for selection, labels it as the work of special group
It jumps user (8)；For any active ues of special group, user's Screening Treatment device compares its userspersonal information, for meeting one
The user of cause property judgment criteria is defined as repeating account, and any active ues for repeating the corresponding multiple special groups of account are merged
It is one, until the corresponding customer attribute information of any active ues of whole special groups meets unicity judgment criteria, and general
Any active ues information of these special groups is stored in sample of users database；
Sample of users database, for storing the spy for meeting unicity judgment criteria for passing through the screening of user's Screening Treatment device and obtaining
Any active ues information of grouping body；
Film comment message handler, the electricity that any active ues for obtaining each special group in sample of users database are issued
Shadow comment information, and by the various quantification of targets of the film comment information, the quantitative information table of the user is obtained, and will be all special
The quantitative information table of any active ues of grouping body is stored in film review quantitative information library (9)；
Film review quantitative information library, the amount of any active ues of all special groups for storing the acquisition of film comment message handler
Change information table；
Evaluation index generator formulates the viewing of the user from the quantitative information table for extracting any active ues in quantitative information library (9)
Characteristic model, the quantitative information library (9) are the group of people and associated film for meeting specific viewing population characteristic
The set of comment information；The film comment information of the user is compared with viewing characteristic model, obtains the work using weighting algorithm
User is jumped to the attention rate numerical value of film, by any active ues whole in quantitative information library (9) to the concern degree of same portion's film
Value is added, and obtains specific viewing group to the attention rate of the film.
2. the viewing index assessment system of specific crowd according to claim 1, it is characterised in that: the film comment information
Various indexs include but is not limited to type, performer, director, country, standard, date, the quantization of so-called index refers to film
Information in comment in relation to These parameters is judged as matching and mismatches two kinds as a result, and every kind of result is given specific weighting
Value.
3. being used for the viewing index assessment system of specific crowd according to claim 2, it is characterised in that: the film comment
Information includes at least type, performer, director, country, standard, working days several indexs, and the weighting algorithm is obtained with following formula
Obtain attention rate of any active ues of the special group to film, A=(2 (g+s+r+c+t+d)-(Gg+Ss+Rr+Cc+Tt+Dd)) *
X,
Wherein
A is attention rate of any active ues to film of the special group
G indicates whether type matches, and 1 represents matching, and 0 represents mismatch, and g represents weight
S indicates whether performer matches, and 1 represents matching, and 0 represents mismatch, behalf weight
R indicates whether director matches, and 1 represents matching, and 0 representative mismatches, and r represents weight
C indicates whether country matches, and 1 represents matching, and 0 representative mismatches, and c represents weight
Whether T presentation format matches, and 1 represents matching, and 0 represents mismatch, and t represents weight
D indicates whether the working days match, and 1 represents matching, and 0 represents mismatch, and d represents weight
X represents the quantization score value of film evaluation, and front comment is 1, and negative reviews are -1, and neutrality comment is 0.
4. the viewing index assessment system of specific crowd according to claim 1 or claim 2, it is characterised in that: of the user
People's information is the information or code of user identity for identification, including user name, account, entry address, No. IP, identification
One of number, telephone number, duty paragraph, Social Security Number are a variety of；The attribute information of the user refers to be used for distinguishing
The characteristic information of family crowd, including age, gender, occupation, hobby, education level, nationality, religious belief, group, political parties and groups, language
One of kind, blood group, colour of skin are a variety of.
5. the viewing index assessment system of specific crowd according to claim 1 or claim 2, it is characterised in that: the user to appoint
The historical review data (4) of what film include the title of evaluation object, the type of evaluation object, evaluation content, make evaluation
Time, the character quantity of evaluation content, evaluation number.
6. the viewing index assessment system of specific crowd according to claim 1 or claim 2, it is characterised in that: the work of the user
Dynamic rule refers to that the regularity of distribution of user's surf time section and user make the regularity of distribution of the period of evaluation.
7. the viewing index assessment system of specific crowd according to claim 1 or claim 2, it is characterised in that: described to be corresponded to
Multiple special groups any active ues merge into one refer to will multiple personal information merge after form new personal information, together
When will multiple attribute informations merge after form new attribute information；The consistency criterion, which refers in userspersonal information, to be used
Name in an account book, account, entry address, No. IP, identification number, telephone number, duty paragraph, one of Social Security Number or a variety of tools
There are consistency or correlation.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107256257A (en) * | 2017-06-12 | 2017-10-17 | 上海携程商务有限公司 | Abnormal user generation content identification method and system based on business datum |
| CN108197271A (en) * | 2018-01-04 | 2018-06-22 | 郑州云海信息技术有限公司 | A kind of films and television programs market analysis method based on big data |
| CN108804506A (en) * | 2018-04-13 | 2018-11-13 | 北京猫眼文化传媒有限公司 | A kind of the recommendation method, apparatus and electronic equipment of information |
| CN110472154B (en) * | 2019-08-26 | 2022-03-29 | 秒针信息技术有限公司 | Resource pushing method and device, electronic equipment and readable storage medium |
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| CN103823890A (en) * | 2014-03-10 | 2014-05-28 | 中国科学院信息工程研究所 | Microblog hot topic detection method and device aiming at specific group |
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| CN104951447A (en) * | 2014-03-25 | 2015-09-30 | 上海市玻森数据科技有限公司 | Whole network public opinion monitoring system |
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