CN111899060A - Advertisement management method and system based on big data - Google Patents
Advertisement management method and system based on big data Download PDFInfo
- Publication number
- CN111899060A CN111899060A CN202010829840.4A CN202010829840A CN111899060A CN 111899060 A CN111899060 A CN 111899060A CN 202010829840 A CN202010829840 A CN 202010829840A CN 111899060 A CN111899060 A CN 111899060A
- Authority
- CN
- China
- Prior art keywords
- access
- authentication
- authentication element
- subscription
- behavior
- 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.)
- Withdrawn
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0241—Advertisements
- G06Q30/0251—Targeted advertisements
- G06Q30/0269—Targeted advertisements based on user profile or attribute
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Development Economics (AREA)
- Finance (AREA)
- Accounting & Taxation (AREA)
- Strategic Management (AREA)
- General Physics & Mathematics (AREA)
- Economics (AREA)
- Marketing (AREA)
- General Business, Economics & Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Game Theory and Decision Science (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- General Engineering & Computer Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Information Transfer Between Computers (AREA)
Abstract
The embodiment of the invention provides an advertisement management method and system based on big data, which comprises the steps of obtaining non-access behavior authentication information and access behavior authentication information, matching the access behavior authentication information by using the behavior characteristic information of a subscription update object of each preset access authentication element, marking an authentication element distribution map of the access authentication element and a continuous update interval of the access authentication element, calculating by using the continuous update interval of the access authentication element and a plurality of subscription update data sources, traversing a target access authentication element, and calculating an associated authentication map of an associated authentication space of the access authentication element, so that an advertisement management label of the access authentication element is added in a plurality of subscription update objects by using the authentication element distribution map, the continuous update interval and the associated authentication map of the access authentication element. Therefore, the accuracy of the advertisement management result based on the big data can be effectively improved by considering the relation between the access authentication element and the data source.
Description
Technical Field
The invention relates to the technical field of advertisement management, in particular to an advertisement management method and system based on big data.
Background
At present, the relation between some access authentication elements and data sources is not considered in the classification process of the advertisement subscription service, so that the accuracy of the classification process is low.
Disclosure of Invention
In view of this, embodiments of the present invention provide an advertisement management method and system based on big data, which can effectively improve the accuracy of the advertisement management result based on big data.
According to an aspect of an embodiment of the present invention, there is provided a big data-based advertisement management method applied to a server, the method including:
acquiring a plurality of subscription update contents of an advertisement subscription service, and extracting a plurality of subscription update objects and a plurality of subscription update data sources from the plurality of subscription update contents;
extracting the behavior characteristic information of the subscription updating object from the plurality of subscription updating objects, and acquiring non-access behavior authentication information and access behavior authentication information according to the behavior characteristic information of the subscription updating object;
matching the access behavior authentication information by using the subscription updating object behavior characteristic information of each preset access authentication element, and marking an authentication element distribution map of the access authentication element and a continuous updating interval of the access authentication element;
calculating by using the continuous updating interval of the access authentication element and the plurality of subscription updating data sources, traversing a target access authentication element, and calculating an associated authentication map of an associated authentication space of the access authentication element;
and adding the advertisement management label of the access authentication element in the plurality of subscription update objects by using the authentication element distribution map of the access authentication element, the continuous update interval of the access authentication element and the associated authentication map of the associated authentication space of the access authentication element.
In a possible example, the step of obtaining the non-access behavior authentication information and the access behavior authentication information according to the subscription update object behavior feature information includes:
and inputting the behavior characteristic information of the subscription updating object into a preset access behavior authentication splitting model to acquire the non-access behavior authentication information and the access behavior authentication information.
In a possible example, the preset access behavior certification splitting model is obtained by training a training set and a test set of dynamic detection obtained in advance, and specifically includes:
and performing cluster analysis on the subscription update object behavior characteristic information of each access authentication element and the subscription update object behavior characteristic information of the non-access authentication element, and determining the subscription update object behavior characteristic information of the access authentication element and the non-access authentication element so as to train and obtain the access behavior authentication splitting model.
In one possible example, the extracting subscription update object behavior feature information from the plurality of subscription update objects comprises:
and performing behavior characteristic detection on each subscription update object item in the plurality of subscription update objects to obtain the behavior characteristic information of the subscription update object item.
In a possible example, the step of matching the access behavior authentication information by using the subscription update object behavior feature information of each preset access authentication element, and marking an authentication element distribution map of the access authentication element and a continuous update interval of the access authentication element includes:
analyzing the behavior characteristic information of the subscription update object of the determined access authentication element, matching the behavior characteristic information of the subscription update object of the access authentication element in a similar time period among different subscription update object items, and determining the data source characteristics of the access authentication element appearing in each subscription update object item to mark the authentication element distribution map of the access authentication element and the continuous update interval of the access authentication element.
According to another aspect of the embodiments of the present invention, there is provided a big data based advertisement management system applied to a server, the system including:
the system comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for acquiring a plurality of subscription update contents of the advertisement subscription service and extracting a plurality of subscription update objects and a plurality of subscription update data sources from the plurality of subscription update contents;
the extraction module is used for extracting the behavior characteristic information of the subscription updating object from the plurality of subscription updating objects and acquiring non-access behavior authentication information and access behavior authentication information according to the behavior characteristic information of the subscription updating object;
the matching and marking module is used for matching the access behavior authentication information by using the subscription updating object behavior characteristic information of each preset access authentication element, and marking an authentication element distribution map of the access authentication element and a continuous updating interval of the access authentication element;
the traversal calculation module is used for calculating by utilizing the continuous updating interval of the access authentication element and the plurality of subscription updating data sources, traversing a target access authentication element and calculating an associated authentication map of an associated authentication space of the access authentication element;
and the adding module is used for adding the advertisement management tags of the access authentication elements in the plurality of subscription updating objects by utilizing the authentication element distribution map of the access authentication elements, the continuous updating interval of the access authentication elements and the associated authentication map of the associated authentication space of the access authentication elements.
According to another aspect of the embodiments of the present invention, there is provided a readable storage medium, having a computer program stored thereon, where the computer program is executed by a processor, and the computer program is capable of executing the steps of the big data based advertisement management method.
Compared with the prior art, the advertisement management method and system based on big data provided by the embodiment of the invention extract the behavior feature information of the subscription update object from the plurality of subscription update objects, acquire the non-access behavior authentication information and the access behavior authentication information according to the behavior feature information of the subscription update object, match the access behavior authentication information by using the behavior feature information of the subscription update object of each preset access authentication element, mark the authentication element distribution map of the access authentication element and the continuous update interval of the access authentication element, calculate by using the continuous update interval of the access authentication element and the plurality of subscription update data sources, traverse the target access authentication element, and calculate the association authentication map of the association authentication space of the access authentication element, thereby using the authentication element distribution map of the access authentication element, The continuous updating interval and the associated authentication map add the advertisement management label of the access authentication element in a plurality of subscription updating objects. Therefore, the accuracy of the advertisement management result based on the big data can be effectively improved by considering the relation between the access authentication element and the data source.
In order to make the aforementioned objects, features and advantages of the embodiments of the present invention comprehensible, embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 illustrates a component diagram of a server provided by an embodiment of the invention;
FIG. 2 is a flow chart of a big data based advertisement management method according to an embodiment of the present invention;
FIG. 3 shows a functional block diagram of a big data based advertisement management system provided by an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood by the scholars in the technical field, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," "third," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Fig. 1 shows an exemplary component schematic of a server 100. The server 100 may include one or more processors 104, such as one or more Central Processing Units (CPUs), each of which may implement one or more hardware threads. The server 100 may also include any storage media 106 for storing any kind of information, such as code, settings, data, etc. For example, and without limitation, storage medium 106 may include any one or more of the following in combination: any type of RAM, any type of ROM, flash memory devices, hard disks, optical disks, etc. More generally, any storage medium may use any technology to store information. Further, any storage medium may provide volatile or non-volatile retention of information. Further, any storage medium may represent a fixed or removable component of server 100. In one case, when the processor 104 executes the associated instructions stored in any storage medium or combination of storage media, the server 100 may perform any of the operations of the associated instructions. The server 100 further comprises one or more drive units 108 for interacting with any storage medium, such as a hard disk drive unit, an optical disk drive unit, etc.
The server 100 also includes input/output 110 (I/O) for receiving various inputs (via input unit 112) and for providing various outputs (via output unit 114)). One particular output mechanism may include a presentation device 116 and an associated Graphical User Interface (GUI) 118. The server 100 may also include one or more network interfaces 120 for exchanging data with other devices via one or more communication units 122. One or more communication buses 124 couple the above-described components together.
The communication unit 122 may be implemented in any manner, such as over a local area network, a wide area network (e.g., the internet), a point-to-point connection, etc., or any combination thereof. The communication unit 122 may include any combination of hardwired links, wireless links, routers, gateway functions, name servers 100, and so forth, governed by any protocol or combination of protocols.
Fig. 2 is a flowchart illustrating a big data based advertisement management method according to an embodiment of the present invention, which can be executed by the server 100 shown in fig. 1, and the detailed steps of the big data based advertisement management method are described as follows.
Step S110, obtaining a plurality of subscription update contents of the advertisement subscription service, and extracting a plurality of subscription update objects and a plurality of subscription update data sources from the plurality of subscription update contents.
Step S120, extracting the subscription update object behavior feature information from the plurality of subscription update objects, and acquiring non-access behavior authentication information and access behavior authentication information according to the subscription update object behavior feature information.
Step S130, matching the access behavior authentication information with the subscription update object behavior feature information of each preset access authentication element, and marking an authentication element distribution map of the access authentication element and a continuous update interval of the access authentication element.
Step S140, performing calculation by using the continuous update interval of the access authentication element and the plurality of subscription update data sources, traversing the target access authentication element, and calculating an associated authentication map of an associated authentication space of the access authentication element.
Step S150, adding an advertisement management tag of the access authentication element in the plurality of subscription update objects by using the authentication element distribution map of the access authentication element, the continuous update interval of the access authentication element, and the association authentication map of the association authentication space of the access authentication element.
Based on the above steps, the present embodiment extracts the behavior feature information of the subscription update object from the plurality of subscription update objects, and acquires the non-access behavior authentication information and the access behavior authentication information according to the behavior feature information of the subscription update object, then matching the access behavior authentication information by using the subscription updating object behavior characteristic information of each preset access authentication element, marking an authentication element distribution map of the access authentication element and a continuous updating interval of the access authentication element, then, the continuous updating interval of the access authentication element and a plurality of subscription updating data sources are used for calculation, the target access authentication element is traversed, the association authentication map of the association authentication space of the access authentication element is calculated, and adding the advertisement management label of the access authentication element in the plurality of subscription updating objects by using the authentication element distribution map, the continuous updating interval and the associated authentication map of the access authentication element. Therefore, the accuracy of the advertisement management result based on the big data can be effectively improved by considering the relation between the access authentication element and the data source.
In a possible example, for step S120, the present embodiment may specifically input the behavior feature information of the subscription update object into a preset access behavior authentication splitting model, and acquire the non-access behavior authentication information and the access behavior authentication information.
In a possible example, the preset access behavior authentication splitting model is obtained by training a training set and a test set of dynamic detection obtained in advance, for example, the access behavior authentication splitting model is obtained by performing cluster analysis on the subscription update object behavior feature information of each access authentication element and the subscription update object behavior feature information of the non-access authentication element to determine the subscription update object behavior feature information of the access authentication element and the non-access authentication element.
In a possible example, for step S120, the present embodiment may specifically perform behavior characteristic detection on each subscription update object item in the plurality of subscription update objects, so as to obtain the subscription update object behavior characteristic information of each subscription update object item.
In a possible example, for step S130, specifically, the present embodiment may analyze the subscription update object behavior feature information of the determined access authentication element, match the subscription update object behavior feature information of the access authentication element in a close time period between different subscription update object items, and determine a data source feature of the access authentication element appearing in each subscription update object item to mark an authentication element distribution map of the access authentication element and a continuous update interval of the access authentication element.
Fig. 3 is a functional block diagram of a big data based advertisement management system 200 according to an embodiment of the present invention, where the functions implemented by the big data based advertisement management system 200 may correspond to the steps executed by the above method. The big data based advertisement management system 200 may be understood as the server 100, or a processor of the server 100, or may be understood as a component that is independent from the server 100 or the processor and implements the functions of the present invention under the control of the server 100, as shown in fig. 3, and the functions of the functional modules of the big data based advertisement management system 200 are described in detail below.
The obtaining module 210 is configured to obtain a plurality of subscription update contents of the advertisement subscription service, and extract a plurality of subscription update objects and a plurality of subscription update data sources from the plurality of subscription update contents.
An extracting module 220, configured to extract the subscription update object behavior feature information from the multiple subscription update objects, and obtain non-access behavior authentication information and access behavior authentication information according to the subscription update object behavior feature information.
The matching and marking module 230 is configured to match the access behavior authentication information with the subscription update object behavior feature information of each preset access authentication element, and mark an authentication element distribution map of the access authentication element and a continuous update interval of the access authentication element.
And a traversal calculation module 240, configured to perform calculation by using the continuous update interval of the access authentication element and the plurality of subscription update data sources, traverse the target access authentication element, and calculate an association authentication graph of an association authentication space of the access authentication element.
An adding module 250, configured to add an advertisement management tag of an access authentication element in the plurality of subscription update objects by using an authentication element distribution map of the access authentication element, a persistent update interval of the access authentication element, and an association authentication map of an association authentication space of the access authentication element.
In one possible example, the extraction module 220 obtains the non-access behavior authentication information and the access behavior authentication information by:
and inputting the behavior characteristic information of the subscription updating object into a preset access behavior authentication splitting model to acquire the non-access behavior authentication information and the access behavior authentication information.
In a possible example, the preset access behavior certification splitting model is obtained by training a training set and a test set of dynamic detection obtained in advance, and the specific method includes:
and performing cluster analysis on the subscription update object behavior characteristic information of each access authentication element and the subscription update object behavior characteristic information of the non-access authentication element, and determining the subscription update object behavior characteristic information of the access authentication element and the non-access authentication element so as to train and obtain the access behavior authentication splitting model.
In one possible example, the manner for extracting the subscription update object behavior feature information from the plurality of subscription update objects includes:
and performing behavior characteristic detection on each subscription update object item in the plurality of subscription update objects to obtain the behavior characteristic information of the subscription update object item.
In one possible example, the matching and marking module 230 may match the access behavior authentication information with the subscription update object behavior feature information of each preset access authentication element by marking an authentication element distribution map of the access authentication element and a continuous update interval of the access authentication element:
analyzing the behavior characteristic information of the subscription update object of the determined access authentication element, matching the behavior characteristic information of the subscription update object of the access authentication element in a similar time period among different subscription update object items, and determining the data source characteristics of the access authentication element appearing in each subscription update object item to mark the authentication element distribution map of the access authentication element and the continuous update interval of the access authentication element.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus and method embodiments described above are illustrative only, as the flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, the functional modules in the embodiments of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
Alternatively, all or part of the implementation may be in software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any drawing credit or debit acknowledgement in the claims should not be construed as limiting the claim concerned.
Claims (2)
1. A big data-based advertisement management method is applied to a server and comprises the following steps:
acquiring a plurality of subscription update contents of an advertisement subscription service, and extracting a plurality of subscription update objects and a plurality of subscription update data sources from the plurality of subscription update contents;
extracting the behavior characteristic information of the subscription updating object from the plurality of subscription updating objects, and acquiring non-access behavior authentication information and access behavior authentication information according to the behavior characteristic information of the subscription updating object;
matching the access behavior authentication information by using the subscription updating object behavior characteristic information of each preset access authentication element, and marking an authentication element distribution map of the access authentication element and a continuous updating interval of the access authentication element;
calculating by using the continuous updating interval of the access authentication element and the plurality of subscription updating data sources, traversing a target access authentication element, and calculating an associated authentication map of an associated authentication space of the access authentication element;
adding advertisement management tags of the access authentication elements in the plurality of subscription update objects by using the authentication element distribution map of the access authentication elements, the continuous update interval of the access authentication elements and the associated authentication map of the associated authentication space of the access authentication elements;
the step of obtaining non-access behavior authentication information and access behavior authentication information according to the subscription update object behavior feature information includes:
inputting the behavior feature information of the subscription updating object into a preset access behavior authentication splitting model to acquire the non-access behavior authentication information and the access behavior authentication information;
the preset access behavior authentication splitting model is obtained by training a training set and a testing set of dynamic detection acquired in advance, and specifically comprises the following steps:
performing cluster analysis on the subscription update object behavior characteristic information of each access authentication element and the subscription update object behavior characteristic information of the non-access authentication element, and determining the subscription update object behavior characteristic information of the access authentication element and the non-access authentication element so as to train and obtain the access behavior authentication splitting model;
the extracting the subscription update object behavior feature information from the plurality of subscription update objects comprises:
performing behavior characteristic detection on each subscription update object item in the plurality of subscription update objects to obtain the behavior characteristic information of the subscription update object item of each subscription update object item;
the step of matching the access behavior authentication information by using the subscription update object behavior feature information of each preset access authentication element, and marking an authentication element distribution map of the access authentication element and a continuous update interval of the access authentication element includes:
analyzing the behavior characteristic information of the subscription update object of the determined access authentication element, matching the behavior characteristic information of the subscription update object of the access authentication element in a similar time period among different subscription update object items, and determining the data source characteristics of the access authentication element appearing in each subscription update object item to mark the authentication element distribution map of the access authentication element and the continuous update interval of the access authentication element.
2. A big data-based advertisement management system, applied to a server, the system comprising:
the system comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for acquiring a plurality of subscription update contents of the advertisement subscription service and extracting a plurality of subscription update objects and a plurality of subscription update data sources from the plurality of subscription update contents;
the extraction module is used for extracting the behavior characteristic information of the subscription updating object from the plurality of subscription updating objects and acquiring non-access behavior authentication information and access behavior authentication information according to the behavior characteristic information of the subscription updating object;
the matching and marking module is used for matching the access behavior authentication information by using the subscription updating object behavior characteristic information of each preset access authentication element, and marking an authentication element distribution map of the access authentication element and a continuous updating interval of the access authentication element;
the traversal calculation module is used for calculating by utilizing the continuous updating interval of the access authentication element and the plurality of subscription updating data sources, traversing a target access authentication element and calculating an associated authentication map of an associated authentication space of the access authentication element;
an adding module, configured to add an advertisement management tag of an access authentication element in the plurality of subscription update objects by using an authentication element distribution map of the access authentication element, a persistent update interval of the access authentication element, and an association authentication map of an association authentication space of the access authentication element;
the extraction module acquires non-access behavior authentication information and access behavior authentication information in the following ways:
inputting the behavior feature information of the subscription updating object into a preset access behavior authentication splitting model to acquire the non-access behavior authentication information and the access behavior authentication information;
the preset access behavior authentication splitting model is obtained by training a training set and a testing set of dynamic detection acquired in advance, and the specific mode comprises the following steps:
performing cluster analysis on the subscription update object behavior characteristic information of each access authentication element and the subscription update object behavior characteristic information of the non-access authentication element, and determining the subscription update object behavior characteristic information of the access authentication element and the non-access authentication element so as to train and obtain the access behavior authentication splitting model;
the manner for extracting the behavior feature information of the subscription update object from the plurality of subscription update objects comprises the following steps:
performing behavior characteristic detection on each subscription update object item in the plurality of subscription update objects to obtain the behavior characteristic information of the subscription update object item of each subscription update object item;
the matching and marking module matches the access behavior authentication information by using the subscription updating object behavior characteristic information of each preset access authentication element in the following way, and marks an authentication element distribution map of the access authentication element and a continuous updating interval of the access authentication element:
analyzing the behavior characteristic information of the subscription update object of the determined access authentication element, matching the behavior characteristic information of the subscription update object of the access authentication element in a similar time period among different subscription update object items, and determining the data source characteristics of the access authentication element appearing in each subscription update object item to mark the authentication element distribution map of the access authentication element and the continuous update interval of the access authentication element.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202010829840.4A CN111899060A (en) | 2020-08-18 | 2020-08-18 | Advertisement management method and system based on big data |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202010829840.4A CN111899060A (en) | 2020-08-18 | 2020-08-18 | Advertisement management method and system based on big data |
Publications (1)
Publication Number | Publication Date |
---|---|
CN111899060A true CN111899060A (en) | 2020-11-06 |
Family
ID=73230427
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202010829840.4A Withdrawn CN111899060A (en) | 2020-08-18 | 2020-08-18 | Advertisement management method and system based on big data |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN111899060A (en) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN112508656A (en) * | 2020-12-24 | 2021-03-16 | 常熟市祺迹网络信息科技有限公司 | Guest-obtaining information processing method and device |
-
2020
- 2020-08-18 CN CN202010829840.4A patent/CN111899060A/en not_active Withdrawn
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN112508656A (en) * | 2020-12-24 | 2021-03-16 | 常熟市祺迹网络信息科技有限公司 | Guest-obtaining information processing method and device |
CN112508656B (en) * | 2020-12-24 | 2024-04-26 | 天窗智库文化传播(苏州)有限公司 | Method and device for processing passenger acquisition information |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN113222554A (en) | Intelligent office cooperation method and system based on big data | |
CN111899060A (en) | Advertisement management method and system based on big data | |
CN111368413B (en) | Clothing production plan tracking management method and system | |
CN111695880A (en) | Production process monitoring method and system | |
CN109710634B (en) | Method and device for generating information | |
CN111948967B (en) | Power data acquisition method and system based on big data | |
US9928303B2 (en) | Merging data analysis paths | |
CN112019632A (en) | Information management method and system of Internet cloud platform | |
CN113901304A (en) | Virtual client information processing method and system | |
CN113282482A (en) | Compatibility test method and system for software package | |
CN113901487A (en) | Digital information encryption method and system based on cloud computing service | |
CN113282412A (en) | Artificial intelligence-based digital service resource allocation method and system | |
CN113901100A (en) | Member information management method and device | |
CN113253261B (en) | Information early warning method and system based on radar camera | |
CN113286156B (en) | Live broadcast cargo-carrying client information tracing query method and system | |
CN113742399B (en) | Cloud edge collaboration-based data tracing method and system | |
CN113075422A (en) | Acceleration sensor testing method and system | |
CN113157546A (en) | Virtual simulation test method and system based on video stream | |
CN112287099A (en) | Supply chain management method and device | |
CN114385448A (en) | Sampler operation test method and system | |
CN112948598A (en) | Pattern learning information embedding method and system | |
CN114414986A (en) | Stability detection method and system in chip detection process | |
CN113900387A (en) | Heating control method and system of vacuum brazing furnace | |
CN113282481A (en) | Software performance testing method and system | |
CN113902502A (en) | Clothing mall shopping information pushing method and device |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
WW01 | Invention patent application withdrawn after publication |
Application publication date: 20201106 |
|
WW01 | Invention patent application withdrawn after publication |