CN104680398A - Acquisition and storage method for mass behavior data of E-commerce users - Google Patents
Acquisition and storage method for mass behavior data of E-commerce users Download PDFInfo
- Publication number
- CN104680398A CN104680398A CN201510108086.4A CN201510108086A CN104680398A CN 104680398 A CN104680398 A CN 104680398A CN 201510108086 A CN201510108086 A CN 201510108086A CN 104680398 A CN104680398 A CN 104680398A
- Authority
- CN
- China
- Prior art keywords
- user
- visitor
- acquisition
- message queue
- information
- 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
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Information Transfer Between Computers (AREA)
Abstract
The invention discloses an acquisition and storage method for mass behavior data of E-commerce users, and belongs to the field of data collection. The method comprises the following steps: monitoring the life cycle of a user conversation by a sound monitor, analyzing every click behavior of the user in the life cycle of the conversation, caching in a message queue, carrying out batch persistence on user behavior information when the size of the caching area of the message queue exceeds an appointed value, and providing support for user behavior analysis of E-commerce enterprises. Compared with the prior art, the method has the advantages that under the premise of not influencing the user experience, the user behavior data needed by the E-commerce enterprises is collected, and the method has good practicability and popularization value.
Description
Technical field
The present invention relates to data collecting field, specifically a kind of acquisition for electricity commercial family magnanimity behavioral data and storage means.
Background technology
For electric firm industry, the importance of data is unquestionable, has become key to win and the profit focus of commercial business's industry of not sending a telegram here round large Data Collection, storage, excavation and analysis.But user behavior collection is an operation of comparing consumption of natural resource, when especially calling party increases, real-time analysis record causes great pressure to system, affects Consumer's Experience greatly.
How to make the operation of business be based upon to segment market, customers, most suitable business and product are sold on most suitable opportunity the client needed most with the most appropriate way of promotion, realize the optimum matching of business and client, become the important goal of electric commercial business industry.
Summary of the invention
Technical assignment of the present invention is for above-mentioned the deficiencies in the prior art, provides a kind of acquisition for electricity commercial family magnanimity behavioral data and storage means.The method makes traditional Single-Server processing mode the processing mode of server cluster into, can use computer resource to greatest extent, effectively carries out horizontal extension.The basic composition of data conversion is step, and passes through the application of server cluster technology, each step in conversion can be placed on execution parallel inside independent server, will greatly improve the efficiency of data processing.
Technical assignment of the present invention realizes in the following manner: a kind of acquisition for electricity commercial family magnanimity behavioral data and storage means, comprise the steps:
Step one: use audiomonitor to follow the tracks of user's request;
Step 2: analyze user and ask at every turn, screening effective information is put in message queue;
Step 3: judge message queue buffer size, batch perdurable data.
As preferably, effective information described in step 2 comprises visitor's essential information, visitor's session information, guest request information.
Described visitor's essential information comprises the IP of visitor, operating system, browser, screen resolution, and source place (this source place is exactly the address that advertiser or search engine chain are taken over), visitor's creation-time.
Further, following information can be obtained according to basic data:
1. the IP of visitor: can count the actual area that IP is corresponding, that is can find out geographic area user sessions;
2. the source place of visitor's essential information: can obtain, visitor clicks our website from which website, and can also obtain visitor is that search engine clicks on our website, and can obtain, the keyword of search;
3. the source place of session: this time session from which web site url is come, if be empty, represents that this user enters website not through any advertisement or search engine;
4. session source place+visitor source place: this combination relatively can show visitor from which advertiser or search engine chain takes over the earliest, and can obtain frequent customer's quantity in each source place;
5. account ID+the source place of visitor's session information: visitor's registration rate that each source place can be checked, and order production rate;
6. guest request URL: the rate of people logging in that can count each page, column, commodity, information; The keyword of site search, the utilization rate of website collection;
7. visitor's mouse is clicked: can count the access habits of visitor at some page;
8. guest request URL+ request time+session start time: can portal page be counted, the outlet page.
Described visitor's session information comprises the time of session start, the source place of this time session, this time the account ID of session guest login.
The solicited message of described visitor comprises the URL address of request, the time of request, and this time requesting client opens the time of the page.
As preferably, the concrete grammar of step 3 is: arrange message queue buffer zone and specify size, judge whether message queue buffer size exceedes threshold values, exceed then mass then by user behavior data persistence.
The invention provides a kind of acquisition for electricity commercial family magnanimity behavioral data and storage means, compared with prior art, the method has following outstanding beneficial effect:
One, can be comparatively complete obtain detailed user behavior data;
Two, owing to using asynchronous persistence, under the prerequisite not affecting Consumer's Experience, the user behavior data that electric commercial business industry needs can be gathered.
Accompanying drawing explanation
Accompanying drawing 1 the present invention is directed to the acquisition of electric commercial family magnanimity behavioral data and the process flow diagram of storage means.
Embodiment
Acquisition for electricity commercial family magnanimity behavioral data of the present invention and storage means are described in detail below with specific embodiment with reference to Figure of description.
Embodiment:
As shown in Figure 1, the acquisition for electricity commercial family magnanimity behavioral data of the present invention and storage means comprise the steps:
Step one: user's access websites initiates request
Step 2: audiomonitor receives user's request
Step 3: analyze user and ask at every turn, screening effective information is put in message queue
Described effective information comprises visitor's essential information, visitor's session information, guest request information.
Wherein, visitor's essential information comprises the IP of visitor, operating system, browser, screen resolution, and source place (this source place is exactly the address that advertiser or search engine chain are taken over), visitor's creation-time.
Following information can be obtained according to above-mentioned basic data:
1. the IP of visitor: can count the actual area that IP is corresponding, that is can find out geographic area user sessions;
2. the source place of visitor's essential information: can obtain, visitor clicks our website from which website, and can also obtain visitor is that search engine clicks on our website, and can obtain, the keyword of search;
3. the source place of session: this time session from which web site url is come, if be empty, represents that this user enters website not through any advertisement or search engine;
4. session source place+visitor source place: this combination relatively can show visitor from which advertiser or search engine chain takes over the earliest, and can obtain frequent customer's quantity in each source place;
5. account ID+the source place of visitor's session information: visitor's registration rate that each source place can be checked, and order production rate;
6. guest request URL: the rate of people logging in that can count each page, column, commodity, information; The keyword of site search, the utilization rate of website collection;
7. visitor's mouse is clicked: can count the access habits of visitor at some page;
8. guest request URL+ request time+session start time: can portal page be counted, the outlet page.
Described visitor's session information comprises the time of session start, the source place of this time session, this time the account ID of session guest login.
The solicited message of described visitor comprises the URL address of request, the time of request, and this time requesting client opens the time of the page.
Step 4: judge message queue buffer size, batch perdurable data
Arrange message queue buffer zone specify size, judge whether message queue buffer size exceedes threshold values, exceed then mass then by user behavior data persistence.
Claims (3)
1., for acquisition and the storage means of electricity commercial family magnanimity behavioral data, it is characterized in that comprising the steps:
Step one: use audiomonitor to follow the tracks of user's request;
Step 2: analyze user and ask at every turn, screening effective information is put in message queue;
Step 3: judge message queue buffer size, batch perdurable data.
2. the acquisition for electricity commercial family magnanimity behavioral data according to claim 1 and storage means, it is characterized in that, effective information described in step 2 comprises visitor's essential information, visitor's session information, guest request information.
3. the acquisition for electricity commercial family magnanimity behavioral data according to claim 1 and storage means, it is characterized in that, the concrete grammar of step 3 is: arrange message queue buffer zone and specify size, judge whether message queue buffer size exceedes threshold values, exceed then mass then by user behavior data persistence.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510108086.4A CN104680398A (en) | 2015-03-12 | 2015-03-12 | Acquisition and storage method for mass behavior data of E-commerce users |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510108086.4A CN104680398A (en) | 2015-03-12 | 2015-03-12 | Acquisition and storage method for mass behavior data of E-commerce users |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN104680398A true CN104680398A (en) | 2015-06-03 |
Family
ID=53315401
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510108086.4A Pending CN104680398A (en) | 2015-03-12 | 2015-03-12 | Acquisition and storage method for mass behavior data of E-commerce users |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104680398A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108009226A (en) * | 2017-11-27 | 2018-05-08 | 深圳市丰巢科技有限公司 | Promotion content display implementation method based on intelligent terminal application and intelligent terminal |
| CN110334074A (en) * | 2019-07-09 | 2019-10-15 | 西安点告网络科技有限公司 | Data processing method, device, server and storage medium |
| CN110933165A (en) * | 2019-11-27 | 2020-03-27 | 中国银行股份有限公司 | Operation behavior tracking method and device |
| CN111770030A (en) * | 2019-05-17 | 2020-10-13 | 北京京东尚科信息技术有限公司 | Message persistence processing method, device and storage medium |
| CN113839923A (en) * | 2021-08-28 | 2021-12-24 | 西安交通大学 | Multi-node-oriented high-performance processing method |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1959717A (en) * | 2006-10-09 | 2007-05-09 | 北京道达天际软件技术有限公司 | System and method for preprocessing mass remote sensing data collection driven by order form |
| KR20090013270A (en) * | 2007-02-28 | 2009-02-05 | 주식회사 케이티프리텔 | Method and system for providing data storage service, and event promotion method |
| CN102761454A (en) * | 2011-04-28 | 2012-10-31 | 中兴通讯股份有限公司 | Method and system for monitoring internet of things |
| CN103916463A (en) * | 2014-03-18 | 2014-07-09 | 北京京东尚科信息技术有限公司 | Network access statistical analysis method and system |
| CN104065741A (en) * | 2014-07-04 | 2014-09-24 | 用友软件股份有限公司 | Data collection system and method |
| CN104317877A (en) * | 2014-10-21 | 2015-01-28 | 上海交通大学 | Netuser behavior data real-time processing method based on distributed computation |
-
2015
- 2015-03-12 CN CN201510108086.4A patent/CN104680398A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1959717A (en) * | 2006-10-09 | 2007-05-09 | 北京道达天际软件技术有限公司 | System and method for preprocessing mass remote sensing data collection driven by order form |
| KR20090013270A (en) * | 2007-02-28 | 2009-02-05 | 주식회사 케이티프리텔 | Method and system for providing data storage service, and event promotion method |
| CN102761454A (en) * | 2011-04-28 | 2012-10-31 | 中兴通讯股份有限公司 | Method and system for monitoring internet of things |
| CN103916463A (en) * | 2014-03-18 | 2014-07-09 | 北京京东尚科信息技术有限公司 | Network access statistical analysis method and system |
| CN104065741A (en) * | 2014-07-04 | 2014-09-24 | 用友软件股份有限公司 | Data collection system and method |
| CN104317877A (en) * | 2014-10-21 | 2015-01-28 | 上海交通大学 | Netuser behavior data real-time processing method based on distributed computation |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108009226A (en) * | 2017-11-27 | 2018-05-08 | 深圳市丰巢科技有限公司 | Promotion content display implementation method based on intelligent terminal application and intelligent terminal |
| CN108009226B (en) * | 2017-11-27 | 2021-12-07 | 深圳市丰巢科技有限公司 | Promotion content display implementation method based on intelligent terminal application and intelligent terminal |
| CN111770030A (en) * | 2019-05-17 | 2020-10-13 | 北京京东尚科信息技术有限公司 | Message persistence processing method, device and storage medium |
| CN110334074A (en) * | 2019-07-09 | 2019-10-15 | 西安点告网络科技有限公司 | Data processing method, device, server and storage medium |
| CN110334074B (en) * | 2019-07-09 | 2021-09-17 | 西安点告网络科技有限公司 | Data processing method, device, server and storage medium |
| CN110933165A (en) * | 2019-11-27 | 2020-03-27 | 中国银行股份有限公司 | Operation behavior tracking method and device |
| CN113839923A (en) * | 2021-08-28 | 2021-12-24 | 西安交通大学 | Multi-node-oriented high-performance processing method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104680398A (en) | Acquisition and storage method for mass behavior data of E-commerce users | |
| AU2013204865B2 (en) | Methods and apparatus to share online media impressions data | |
| WO2020248508A1 (en) | Method, device and apparatus for evaluating advertising channel, and storage medium | |
| US20220150292A1 (en) | Personalized Recommendation Method and System, and Terminal Device | |
| JP5313910B2 (en) | Large-scale aggregation and reporting of advertising data | |
| CN106227832A (en) | Application method of Internet big data technology architecture in business analysis in enterprise | |
| US20140068411A1 (en) | Methods and apparatus to monitor usage of internet advertising networks | |
| US20150254685A1 (en) | Methods and systems for compiling marketing information for a client | |
| US20140149418A1 (en) | Method and system for measuring social influence and receptivity of users | |
| Heymann et al. | Turkalytics: analytics for human computation | |
| CN104881803B (en) | Method and device for analyzing advertisement click link | |
| AU2013204878A1 (en) | Determining audience reach for internet media | |
| CN102314455A (en) | Method and system for calculating click flow of web page | |
| CN104601408B (en) | Website data statistics and analysis method and system for non-open network environment | |
| CN107590691B (en) | Information publishing method and device, storage medium and terminal | |
| WO2018223672A1 (en) | Data processing method and device | |
| CN107578263A (en) | A kind of detection method, device and the electronic equipment of advertisement abnormal access | |
| CN104063411A (en) | Enterprise intelligence gathering method based on Michael Porter's Five Forces Model | |
| CN101226550A (en) | Method and system for processing electric bank website client action and information | |
| CN105069087A (en) | Web log data mining based website optimization method | |
| CN102291251A (en) | User state tracking method and system for internet website | |
| CN104217353A (en) | Webpage advertisement directional pushing system | |
| CN101383713B (en) | Internet advertisement information processing method | |
| WO2021093423A1 (en) | Method and device for tagging user | |
| CN107590681A (en) | A kind of big data analysis system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20150603 |
|
| WD01 | Invention patent application deemed withdrawn after publication |