CN105701224A - Security information customized service system based on big data - Google Patents
Security information customized service system based on big data Download PDFInfo
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- CN105701224A CN105701224A CN201610028294.8A CN201610028294A CN105701224A CN 105701224 A CN105701224 A CN 105701224A CN 201610028294 A CN201610028294 A CN 201610028294A CN 105701224 A CN105701224 A CN 105701224A
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- G—PHYSICS
- 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
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
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Abstract
The invention discloses a security information customized service system based on big data; a big data processing system receives mass log data sent by user terminals, extracts user equipment information and user behavior information so as to generate an equipment-user matching relation sheet, and sends the matching relation sheet and user browse information of the equipment to a information adaption server; the information adaption server builds a user-information correlation model through user attribute, user behavior attribute and information attribute, thus obtaining adapted customized information for each user; the information adaption server recognizes a client number from the matching relation sheet according to equipment information sent by the user terminal, and pushes the user customized information to the corresponding user terminal. The security information customized service system can fast recognize security browse client, can provide customized information highly associated to the client, thus solving the problems that conventional security software cannot recognize browse clients, and cannot push information content with pertinency; the security information customized service system can improve information push accuracy.
Description
Technical field
The present invention relates to a kind of big data collection and analysis technology, in particular a kind of security information individuation service system based on big data。
Background technology
In recent years, universal along with " big data " concept, in a lot of fields, service provider starts conscious mass users data to carry out Real-time Collection and analysis, thus extracting valuable information。After more valuable informix being utilized, it is pushed to target group's customized information comparatively accurately, is a comprehensive method system based on data mining, natural language processing and Internet technology。Give suitable people by suitable information pushing, be the work of a great challenge。This process needs to make information to analyze fully, the interest of people, behavior is done careful portraying, and both is effectively matched simultaneously。
In recent years, people are more and more higher to the attention rate of securities market。The information that securities broker company provides to security user every day is more, several thousand easily, lacking of property, and current propelling movement mode underaction, provide the user with general information typically via website or user side。Browsing user at present in the majority, when online user is, and whose None-identified online user is, therefore pushes personalized information aspect inefficient。
Summary of the invention
It is an object of the invention to overcome the deficiencies in the prior art, it is provided that a kind of security information individuation service system based on big data, it is possible to quickly identify and browse client, and personalized information is provided。
The present invention is achieved by the following technical solutions, and the present invention includes big data handling system and information adaptation services device；
Described big data handling system, receive the massive logs data that user terminal sends, extract user equipment information and user behavior information, generate equipment and user's mapping table, then the information that the user of described mapping table and this equipment browsed is sent to information adaptation services device
Described information adaptation services device, the related degree model of user and information is set up by user property, user behavior attribute and information attribute, obtain the personalized information after every user's adaptation, then the facility information sent according to user terminal, after identifying customer ID from described mapping table, give corresponding user terminal by the personalized message push of this user。
Described big data handling system receives mobile phone terminal and the destructuring daily record data of PC end transmission, described destructuring daily record data includes cell-phone number, IMEI number, customer ID, MAC Address, browses securities information, landing time and number of times, and generate equipment and user's mapping table regular update according to described destructuring daily record data。
The generation method of described mapping table, comprises the following steps:
(11) from mobile phone daily record data, extract user and log in the cell-phone number of cell phone system, IMEI number and customer ID data, from PC daily record data, extract user log in MAC Address and the customer ID data of PC system；
(12) all customer IDs logged on each cell-phone number, IMEI number, MAC Address are added up respectively；
(13) if only one of which customer ID logs on a cell-phone number, IMEI number or MAC Address, or have multiple customer ID log in but only one of which customer ID login times or ratio exceed threshold values, then this cell-phone number, IMEI number or MAC Address are corresponded on this customer ID, in write device and user's mapping table；
(14) if having multiple customer ID to log on a cell-phone number, IMEI number or MAC Address, and more than one customer ID login times or ratio exceed threshold values, then this cell-phone number, IMEI number or MAC Address are corresponded on the customer ID exceeding threshold values of the last login, in write device and user's mapping table。
Described user property includes personal share position in storehouse, personal share liveness, the personal share attribute held position, and user behavior attribute includes self-selected stock, browses stock, adds self-selected stock time, number of visits；Information attribute includes ageing, the corresponding personal share of information importance degree, information, corresponding industry, column priority。
The method for building up of described related degree model is as follows:
(21) by the information classification of propelling movement be personal share information, industry Zone Information and macroscopic view information；
(22) calculate the information weighted score under each classification respectively and sort；
(23) information of N name before the information weighted score under each classification is pushed to corresponding user terminal respectively。
In described step (22), the personal share information weighted score=personal share position in storehouse score+personal share liveness score+interpolation self-selected stock natural law+number of visits score+personal share information importance degree score+ageing score of personal share information+personal share column preference score。
In described step (22), the industry Zone Information weighted score=industry existing position ratio score+industry historical analysis score+area position ratio+concept position ratio+ageing score of industry Zone Information importance degree score+industry Zone Information+industry column preference score。
In described step (22), the macroscopic view information weighted score=macroscopic view information importance degree score+ageing score of macroscopic view information+macroscopic view column preference score。
The described facility information sent according to user terminal, the method identifying user from described mapping table is as follows:
(24) information sent when starting according to user terminal, is judged it is mobile terminal or PC terminal by information adaptation services device, if comprising the cell-phone number after encryption or IMEI number in data, is then judged to mobile terminal, otherwise is PC terminal；
(25) if user terminal is mobile terminal, first according to the customer ID that cell-phone number inquiry is corresponding, if successful inquiring, return customer ID, if inquiring about unsuccessfully, further according to the customer ID that IMEI number inquiry is corresponding, if successful inquiring, return customer ID, if inquiring about unsuccessfully, exiting inquiry and returning Universal Subscriber mark；
(26) if user terminal is PC terminal, according to the customer ID that MAC Address inquiry is corresponding, if successful inquiring, return customer ID, if inquiring about unsuccessfully, exiting inquiry and returning Universal Subscriber mark。
After described information adaptation services device identifies customer ID, the up-to-date personalized information obtained by related degree model, is pushed to the user terminal at user place, and the user for Universal Subscriber mark pushes general information, after receiving new information, related degree model is repeatedly updated calculating every day。
The present invention has the advantage that the present invention extracts from big data compared to existing technology and analyzes user profile, can quickly identify that security browse client, adaptation is carried out according to user profile and backstage information service device, and the personalized information with client's highlights correlations is provided, overcome tradition security software None-identified and browse client, and propelling movement information content does not have specific aim problem, improve information content precision。
Accompanying drawing explanation
Fig. 1 is the flow chart of the present invention。
Detailed description of the invention
Below embodiments of the invention being elaborated, the present embodiment is carried out under premised on technical solution of the present invention, gives detailed embodiment and concrete operating process, but protection scope of the present invention is not limited to following embodiment。
As it is shown in figure 1, the present embodiment includes big data handling system and information adaptation services device；
Described big data handling system, receive the massive logs data that user terminal sends, the data volume of every day is about 50G, 80000000000 row, extract user equipment information and user behavior information, generation equipment and user's mapping table, the information that then user of described mapping table and this equipment browsed is sent to information adaptation services device
Described information adaptation services device, the related degree model of user and information is set up by user property, user behavior attribute and information attribute, obtain the personalized information after every user's adaptation, then the facility information sent according to user terminal, after identifying customer ID from described mapping table, give corresponding user terminal by the personalized message push of this user。
The big data handling system platform of the present embodiment uses Hadoop framework, internal employing HDFS and MapReduce at least 3 station servers, and information adaptation services device uses oracle database。
The user terminal of the present embodiment includes mobile phone terminal and PC end, big data handling system receives mobile phone terminal and the destructuring daily record data of PC end transmission, described destructuring daily record data includes cell-phone number, IMEI number, customer ID, MAC Address, browses securities information, landing time and number of times, and generate equipment and user's mapping table regular update according to described destructuring daily record data。
Customer ID in the present embodiment is the user name for logging in security that each user is stored in securities system, has uniqueness。IMEI number is unique mark of cell phone apparatus, and MAC Address is unique mark of PC equipment, and is written in daily record data。
The generation method of mapping table, comprises the following steps:
(11) from mobile phone daily record data, extract user and log in the cell-phone number of cell phone system, IMEI number and customer ID data, from PC daily record data, extract user log in MAC Address and the customer ID data of PC system；
(12) all customer IDs logged on each cell-phone number, IMEI number, MAC Address are added up respectively；
(13) if only one of which customer ID logs on a cell-phone number, IMEI number or MAC Address, or there are the login of multiple customer ID but only one of which customer ID login times or ratio more than 3 times, then this cell-phone number, IMEI number or MAC Address are corresponded on this customer ID, in write device and user's mapping table；
(14) if having multiple customer ID to log on a cell-phone number, IMEI number or MAC Address, and more than one customer ID login times or ratio are more than 3 times, then this cell-phone number, IMEI number or MAC Address are corresponded on the customer ID more than 3 times of the last login, in write device and user's mapping table。
User property includes personal share position in storehouse, personal share liveness, the personal share attribute held position, and user behavior attribute includes self-selected stock, browses stock, adds self-selected stock time, number of visits；Information attribute includes ageing, the corresponding personal share of information importance degree, information, corresponding industry, column priority。
The personal share attribute held position is: industry, concept, plate, personal share liveness are ups and downs ratio。The personal share of user matches with the personal share in information and trade information with industry, just can push targetedly。
The method for building up of related degree model is as follows:
(21) by the information classification of propelling movement be personal share information, industry Zone Information and macroscopic view information；
(22) calculate the information weighted score under each classification respectively and sort；
The personal share information weighted score=personal share position in storehouse score+personal share liveness score+interpolation self-selected stock natural law+number of visits score+personal share information importance degree score+ageing score of personal share information+personal share column preference score,
Industry Zone Information weighted score=industry existing position ratio score+industry historical analysis score+area position ratio+concept position ratio+ageing the score of industry Zone Information importance degree score+industry Zone Information+industry column preference score,
The macroscopic view information weighted score=macroscopic view information importance degree score+ageing score of macroscopic view information+macroscopic view column preference score,
(23) information of N name before the information weighted score under each classification is pushed to corresponding user terminal respectively, in the present embodiment, for avoiding the too many client of information to be not able to watch over, selects front 30 message push of highest scoring。
In the present embodiment, each weighted score is as shown in table 1。
Each weight score-sheet of table 1
According to the facility information that user terminal sends, the method identifying user from described mapping table is as follows:
(24) information sent when starting according to user terminal, is judged it is mobile terminal or PC terminal by information adaptation services device, if comprising the cell-phone number after encryption or IMEI number in data, is then judged to mobile terminal, otherwise is PC terminal；
(25) if user terminal is mobile terminal, first according to the customer ID that cell-phone number inquiry is corresponding, if successful inquiring, return customer ID, if inquiring about unsuccessfully, further according to the customer ID that IMEI number inquiry is corresponding, if successful inquiring, return customer ID, if inquiring about unsuccessfully, exiting inquiry and returning Universal Subscriber mark；
(26) if user terminal is PC terminal, according to the customer ID that MAC Address inquiry is corresponding, if successful inquiring, return customer ID, if inquiring about unsuccessfully, exiting inquiry and returning Universal Subscriber mark。
Information adaptation services device identification browses client's accuracy more than 95%, after identifying customer ID, and the up-to-date personalized information that information related degree model is obtained, it is pushed to the user terminal at user place。After information adaptation services device receives new information, related degree model repeatedly updates calculating every day。From starting client, to identifying customer ID and pushing personalized information, the time was less than 3 seconds。
For the user terminal of None-identified customer ID, i.e. the user terminal of Universal Subscriber mark, push general information。General information be get rid of after personal attribute by the calculated information of above-mentioned related degree model, the personal share that such as amount of increase and amount of decrease is bigger, and important industry and macroscopical information。
The foregoing is only presently preferred embodiments of the present invention, not in order to limit the present invention, all any amendment, equivalent replacement and improvement etc. made within the spirit and principles in the present invention, should be included within protection scope of the present invention。
Claims (10)
1. the security information individuation service system based on big data, it is characterised in that include big data handling system and information adaptation services device；
Described big data handling system, receive the massive logs data that user terminal sends, extract user equipment information and user behavior information, generate equipment and user's mapping table, then the information that the user of described mapping table and this equipment browsed is sent to information adaptation services device
Described information adaptation services device, the related degree model of user and information is set up by user property, user behavior attribute and information attribute, obtain the personalized information after every user's adaptation, then the facility information sent according to user terminal, after identifying customer ID from described mapping table, give corresponding user terminal by the personalized message push of this user。
2. a kind of security information individuation service system based on big data according to claim 1, it is characterized in that, described big data handling system receives mobile phone terminal and the destructuring daily record data of PC end transmission, described destructuring daily record data includes cell-phone number, IMEI number, customer ID, MAC Address, browses securities information, landing time and number of times, and generate equipment and user's mapping table regular update according to described destructuring daily record data。
3. a kind of security information individuation service system based on big data according to claim 1 and 2, it is characterised in that the generation method of described mapping table, comprises the following steps:
(11) from mobile phone daily record data, extract user and log in the cell-phone number of cell phone system, IMEI number and customer ID data, from PC daily record data, extract user log in MAC Address and the customer ID data of PC system；
(12) all customer IDs logged on each cell-phone number, IMEI number, MAC Address are added up respectively；
(13) if only one of which customer ID logs on a cell-phone number, IMEI number or MAC Address, or have multiple customer ID log in but only one of which customer ID login times or ratio exceed threshold values, then this cell-phone number, IMEI number or MAC Address are corresponded on this customer ID, in write device and user's mapping table；
(14) if having multiple customer ID to log on a cell-phone number, IMEI number or MAC Address, and more than one customer ID login times or ratio exceed threshold values, then this cell-phone number, IMEI number or MAC Address are corresponded on the customer ID exceeding threshold values of the last login, in write device and user's mapping table。
4. a kind of security information individuation service system based on big data according to claim 1, it is characterised in that described user property includes personal share position in storehouse, personal share liveness, the personal share attribute held position；User behavior attribute includes self-selected stock, browses stock, adds self-selected stock time, number of visits；Information attribute includes ageing, the corresponding personal share of information importance degree, information, corresponding industry, column priority。
5. a kind of security information individuation service system based on big data according to claim 4, it is characterised in that the method for building up of described related degree model is as follows:
(21) by the information classification of propelling movement be personal share information, industry Zone Information and macroscopic view information；
(22) calculate the information weighted score under each classification respectively and sort；
(23) information of N name before the information weighted score under each classification is pushed to corresponding user terminal respectively。
6. a kind of security information individuation service system based on big data according to claim 5, it is characterized in that, in described step (22), the personal share information weighted score=personal share position in storehouse score+personal share liveness score+interpolation self-selected stock natural law+number of visits score+personal share information importance degree score+ageing score of personal share information+personal share column preference score。
7. a kind of security information individuation service system based on big data according to claim 5, it is characterized in that, in described step (22), the industry Zone Information weighted score=industry existing position ratio score+industry historical analysis score+area position ratio+concept position ratio+ageing score of industry Zone Information importance degree score+industry Zone Information+industry column preference score。
8. a kind of security information individuation service system based on big data according to claim 5, it is characterized in that, in described step (22), the macroscopic view information weighted score=macroscopic view information importance degree score+ageing score of macroscopic view information+macroscopic view column preference score。
9. a kind of security information individuation service system based on big data according to claim 1, it is characterised in that the described facility information sent according to user terminal, the method identifying user from described mapping table is as follows:
(24) information sent when starting according to user terminal, is judged it is mobile terminal or PC terminal by information adaptation services device, if comprising the cell-phone number after encryption or IMEI number in data, is then judged to mobile terminal, otherwise is PC terminal；
(25) if user terminal is mobile terminal, first according to the customer ID that cell-phone number inquiry is corresponding, if successful inquiring, return customer ID, if inquiring about unsuccessfully, further according to the customer ID that IMEI number inquiry is corresponding, if successful inquiring, return customer ID, if inquiring about unsuccessfully, exiting inquiry and returning Universal Subscriber mark；
(26) if user terminal is PC terminal, according to the customer ID that MAC Address inquiry is corresponding, if successful inquiring, return customer ID, if inquiring about unsuccessfully, exiting inquiry and returning Universal Subscriber mark。
10. a kind of security information individuation service system based on big data according to claim 9, it is characterized in that, after described information adaptation services device identifies customer ID, the up-to-date personalized information that related degree model is obtained, it is pushed to the user terminal at user place, user for Universal Subscriber mark pushes general information, and after receiving new information, related degree model is repeatedly updated calculating every day。
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Cited By (5)
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| CN106327331A (en) * | 2016-08-18 | 2017-01-11 | 北京富盈通科技有限公司 | Intelligent transaction system |
| CN107491533A (en) * | 2017-08-22 | 2017-12-19 | 安徽简道科技有限公司 | Security information individuation service system based on big data |
| CN108270842A (en) * | 2017-06-09 | 2018-07-10 | 广州市动景计算机科技有限公司 | Push method, system and the server of equity task |
| CN108628949A (en) * | 2018-03-30 | 2018-10-09 | 北京金堤科技有限公司 | A kind of processing method and processing device that information is shown |
| CN109166039A (en) * | 2018-08-10 | 2019-01-08 | 大智慧信息技术有限公司 | The preparation method and system of free index |
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| CN106327331A (en) * | 2016-08-18 | 2017-01-11 | 北京富盈通科技有限公司 | Intelligent transaction system |
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| CN105701224B (en) | 2017-02-08 |
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