CN106777367A - A kind of user behavior analysis method and system excavated based on big data - Google Patents
A kind of user behavior analysis method and system excavated based on big data Download PDFInfo
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- CN106777367A CN106777367A CN201710052503.7A CN201710052503A CN106777367A CN 106777367 A CN106777367 A CN 106777367A CN 201710052503 A CN201710052503 A CN 201710052503A CN 106777367 A CN106777367 A CN 106777367A
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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
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/25—Integrating or interfacing systems involving database management systems
- G06F16/258—Data format conversion from or to a database
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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
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/242—Query formulation
- G06F16/2433—Query languages
- G06F16/244—Grouping and aggregation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2216/00—Indexing scheme relating to additional aspects of information retrieval not explicitly covered by G06F16/00 and subgroups
- G06F2216/03—Data mining
Abstract
The present embodiments relate to communication technical field, a kind of user behavior analysis method and system excavated based on big data are disclosed.Wherein, the method includes：In the embodiment of the present invention, the Temperature numerical that monitoring multi-point thermo detector is received determines whether the Temperature numerical meets pre-conditioned；If the Temperature numerical meets described pre-conditioned, real time temperature is sent to Surveillance center.Implement the embodiment of the present invention, temperature can be reported Surveillance center, temperature regime is checked whenever and wherever possible by mobile device by user.
Description
Technical field
The present invention relates to Internet technical field, more particularly to a kind of user behavior analysis method excavated based on big data
And system.
Background technology
In this field of the Internet, applications, user behavior analysis refer to statistics and analysis user access network and service full mistake
Cheng Dangzhong (including access and browse webpage, interact formula operation, use APP etc.) produce real-time and history user
Behavioural information.In the middle of the action process of user access network service, comprising a large amount of valuable information.According to measuring and calculating, user
3-4 part commodity are averagely paid close attention to during a shopping online, 5-7 website is accessed, the page of more than 40 is browsed.With
Family behavioural information includes but is not limited to herein below：The access times of network service, visiting frequency, access residence time, behaviour
Make active time, user input keyword, user clicks on links, user interactive (such as pay attention in, cancel concern, marking, protect
Save as bookmark, add shopping cart, take out shopping cart, formed order, cancel an order, pay the bill, reimbursement etc.).By to user's row
It is the research of information, can therefrom finds the rule distribution that user shows when access network is serviced, and for lifting is used
Family experience, efficient information are pushed and promote target marketing to provide science, accurate objective basis.For user behavior research with
Using, maximally effective means are to record whole user behavior information that all behaviors of user bring, and to whole user's rows
Counted for information, analyzed.
Big data technology is the phase for the total data resource of any system as object and therefrom finding to be showed between data
The information processing technology of sexual intercourse is closed, process optimization, targeted message and the advertisement that internet is had been widely used at present are pushed away
Give, user individual service with the aspect such as improve, become the powerful background support in network service behind.Based on big data platform
The analysis and utilization to whole user behavior information are realized, the in large scale, data form of user behavior information itself has been adapted to multiple
The characteristics of miscellaneous diversification, arithmetic speed requirement high, disclosure satisfy that the actual demand of all types of network services.
For the analysis of user behavior, many researchs were done both at home and abroad, but there are problems that：First, it is mostly focused on
Excavate WEB daily records, but these daily records e insufficient to describe in time scene when user accesses website；Secondly, large-scale website is general
Possess huge online user, the real-time behavior of generation and contextual information amount are huge, therefore, the storage capacity of system and calculating
Speed is stronger, analysis result could be fed back into user in time.And it is current, most of user behavior analysis systems use relation
Database technology and traditional data processing method, it is impossible to meet the efficient analysis of mass data very well.
The content of the invention
A kind of non intelligent air conditioning monitoring method and system based on Internet of Things are the embodiment of the invention provides, can be monitored non-
The various parameters information of intelligent air condition, and non intelligent air-conditioning is adjusted according to parameter information, it is possible to achieve check that air-conditioning humiture sets
Put whether rationally, or according to period automatic control air conditioner switching on and shutting down, it is to avoid unnecessary low-temperature receiver is wasted.
Embodiment of the present invention first aspect discloses a kind of user behavior analysis method excavated based on big data, including：
Collection user behavior data；
User behavior data is pre-processed and be polymerized using concurrent operation model；
According to the user behavior data after polymerization, user behavior data ontology model is set up, and store in database.
Used as a kind of optional implementation method, methods described also includes,
User behavior data ontology model is made inferences, the newest interesting data of user is found out.
Used as a kind of optional implementation method, the user behavior data includes user behavior main body, time of origin, generation
The page, the scroll-up/down page, movement or click on mouse, page residence time, collect, print, preserving, accessing the same page time
Text operation, the search condition of active user, the corresponding title of search key are pasted in number, duplication.
Used as a kind of optional implementation method, the pretreatment includes：Removal deficiency of data, deleting duplicated data, figure
Piece, page animation；Printing, collection, preservation, the down operation carried out to the page, after the acquisition, are converted into corresponding data
Form is stored in database；
The data aggregate includes：It is poly- using rule-based user behavior to correct but invalid user behavior information
Hop algorithm is filtered, integrated.
It is described to set up user behavior data ontology model as a kind of optional implementation method, specifically include：
User behavior data ontology model is set up using OWL-DL description languages, and ontology model is decomposed, it is described
Database is using the non-relational distributed data base increased income.
The face of the embodiment of the present invention second discloses a kind of user behavior analysis system excavated based on big data, including：
Collecting unit, for gathering user behavior data；
Pretreatment unit, for user behavior data to be pre-processed and be polymerized using concurrent operation model；
Modeling unit, for according to the user behavior data after polymerization, setting up user behavior data ontology model, and store
In database.
Used as a kind of optional implementation method, the system also includes：
Reasoning element, for being made inferences to user behavior data ontology model, finds out the newest interesting data of user.
Used as a kind of optional implementation method, the user behavior data includes user behavior main body, time of origin, generation
The page, the scroll-up/down page, movement or click on mouse, page residence time, collect, print, preserving, accessing the same page time
Text operation, the search condition of active user, the corresponding title of search key are pasted in number, duplication.
Used as a kind of optional implementation method, the pretreatment includes：Removal deficiency of data, deleting duplicated data, figure
Piece, page animation；Printing, collection, preservation, the down operation carried out to the page, after the acquisition, are converted into corresponding data
Form is stored in database；
The data aggregate includes：It is poly- using rule-based user behavior to correct but invalid user behavior information
Hop algorithm is filtered, integrated.
As a kind of optional implementation method, the modeling unit specifically for：Set up using OWL-DL description languages and used
Family behavioral data ontology model, and ontology model is decomposed, the database is using the non-relational distribution number increased income
According to storehouse.
As can be seen from the above technical solutions, the embodiment of the present invention has advantages below：
In the embodiment of the present invention, user behavior data is gathered；User behavior data is carried out using concurrent operation model pre-
Process and be polymerized；According to the user behavior data after polymerization, user behavior data ontology model is set up, and store in database
In.As can be seen here, implement the embodiment of the present invention, by the powerful disposal ability and mass data storage ability of cloud computing technology,
Body and its reasoning, Methods of Knowledge Discovering Based are combined, and analysis mass users behavioral data, obtains user interest in time in real time, from
And realize effectively being pushed with accurately user.
Brief description of the drawings
Technical scheme in order to illustrate more clearly the embodiments of the present invention, below will be to that will make needed for embodiment description
Accompanying drawing is briefly introduced, it should be apparent that, drawings in the following description are only some embodiments of the present invention, for this
For the those of ordinary skill in field, without having to pay creative labor, it can also be obtained according to these accompanying drawings
His accompanying drawing.
Fig. 1 is a kind of flow of the user behavior analysis method excavated based on big data disclosed in first embodiment of the invention
Schematic diagram；
Fig. 2 is a kind of flow of the user behavior analysis method excavated based on big data disclosed in second embodiment of the invention
Schematic diagram；
Fig. 3 is a kind of structure of the user behavior analysis system excavated based on big data disclosed in third embodiment of the invention
Schematic diagram；
Fig. 4 is a kind of structure of the user behavior analysis system excavated based on big data disclosed in fourth embodiment of the invention
Schematic diagram；
Fig. 5 is a kind of structure of the user behavior analysis terminal excavated based on big data disclosed in fifth embodiment of the invention
Schematic diagram.
Specific embodiment
In order that the object, technical solutions and advantages of the present invention are clearer, below in conjunction with accompanying drawing the present invention is made into
One step ground is described in detail, it is clear that described embodiment is only some embodiments of the invention, rather than whole implementation
Example.Based on the embodiment in the present invention, what those of ordinary skill in the art were obtained under the premise of creative work is not made
All other embodiment, belongs to the scope of protection of the invention.
Term " first ", " second " in description and claims of this specification and above-mentioned accompanying drawing etc. are for distinguishing
Different object, rather than for describing particular order.Additionally, term " comprising " and " having " and their any deformations, meaning
Figure is to cover non-exclusive including.For example contain process, method, system, product or the equipment of series of steps or unit
The step of having listed or unit are not limited to, but alternatively also include the step of not listing or unit, or alternatively also
Including for these processes, method or other intrinsic steps of equipment or unit.
Referenced herein embodiment is it is meant that the special characteristic, structure or the characteristic that describe can be included in conjunction with the embodiments
In at least one embodiment of the present invention.The phrase occur in each position of specification might not each mean identical reality
Example is applied, nor the independent or alternative embodiment with other embodiment mutual exclusion.Those skilled in the art are explicitly and implicitly
Ground understands that embodiment described herein can be combined with other embodiment.
A kind of user behavior analysis method excavated based on big data is the embodiment of the invention provides, by cloud computing technology
Powerful disposal ability and mass data storage ability, body and its reasoning, Methods of Knowledge Discovering Based are combined, and magnanimity is analyzed in real time
User behavior data, obtains user interest in time, so as to realize effectively being pushed with accurately user.
Fig. 1 is referred to, Fig. 1 is a kind of user behavior analysis excavated based on big data disclosed in first embodiment of the invention
The schematic flow sheet of method.Wherein, the user behavior analysis method excavated based on big data shown in Fig. 1, can include following
Step：
101st, user behavior data is gathered；
In the embodiment of the present invention, the user behavior data include user behavior main body, time of origin, occur the page,
The scroll-up/down page, movement are clicked on mouse, page residence time, collect, print, preserving, access same page number of times, replicate
Paste text operation, the search condition of active user, the corresponding title of search key.
102nd, user behavior data is pre-processed and is polymerized using concurrent operation model；
In the embodiment of the present invention, the pretreatment includes：Removal deficiency of data, deleting duplicated data, picture, the page are moved
Draw；Printing, collection, preservation, the down operation carried out to the page, after the acquisition, are converted into corresponding data form and preserve
In database.
The data aggregate includes：It is poly- using rule-based user behavior to correct but invalid user behavior information
Hop algorithm is filtered, integrated.
103rd, according to the user behavior data after polymerization, user behavior data ontology model is set up, and store in database
In.
In the embodiment of the present invention, user behavior data ontology model is set up using OWL-DL description languages, and to body mould
Type is decomposed, and the database is using the non-relational distributed data base increased income.
104th, user behavior data ontology model is made inferences, finds out the newest interesting data of user.
In the embodiment of the present invention, the user behavior data after polymerization is added in user behavior data ontology model, it is right
The user behavior data ontology model data stored in database make inferences, and find out the newest interesting data of user.
In the method described by Fig. 1, user behavior data is gathered；User behavior data is entered using concurrent operation model
Row is pre-processed and is polymerized；According to the user behavior data after polymerization, user behavior data ontology model is set up, and store in data
In storehouse.As can be seen here, the embodiment of the present invention is implemented, by the powerful disposal ability and mass data storage energy of cloud computing technology
Power, body and its reasoning, Methods of Knowledge Discovering Based are combined, and analysis mass users behavioral data, obtains user interest in time in real time,
So as to realize effectively being pushed with accurately user.
It is below present system embodiment, present system embodiment is used to perform the realization of the inventive method embodiment one
Method, for convenience of description, illustrate only the method related to the embodiment of the present invention, it is specific to calculate what details was not disclosed, please
With reference to the embodiment of the present invention one to two.
Fig. 2 is referred to, Fig. 2 is a kind of user behavior analysis excavated based on big data disclosed in second embodiment of the invention
The structure chart of system.As shown in Fig. 2 the system can include：
Collecting unit 201, for gathering user behavior data；
The user behavior data includes user behavior main body, time of origin, the page for occurring, the scroll-up/down page, shifting
It is dynamic or click on mouse, page residence time, collect, print, preserving, access same page number of times, replicate paste text operation, when
The corresponding title of the search condition of preceding user, search key.
Pretreatment unit 202, for user behavior data to be pre-processed and be polymerized using concurrent operation model.
The pretreatment includes：Removal deficiency of data, deleting duplicated data, picture, page animation；The page is carried out
Printing, collection, preservation, down operation, after the acquisition, are converted into corresponding data form and are stored in database；
The data aggregate includes：It is poly- using rule-based user behavior to correct but invalid user behavior information
Hop algorithm is filtered, integrated.
Modeling unit 203, for according to the user behavior data after polymerization, setting up user behavior data ontology model, and
Storage is in database.
In the embodiment of the present invention, user behavior data ontology model is set up using OWL-DL description languages, and to body mould
Type is decomposed, and the database is using the non-relational distributed data base increased income.
Reasoning element 204, for being made inferences to user behavior data ontology model, finds out the newest interesting data of user.
In the embodiment of the present invention, the user behavior data after polymerization is added in user behavior data ontology model, it is right
The user behavior data ontology model data stored in database make inferences, and find out the newest interesting data of user.
In the system described by Fig. 2, collecting unit collection user behavior data；Pretreatment unit is to user behavior data
Pre-processed and be polymerized using concurrent operation model；Modeling unit sets up user's row according to the user behavior data after polymerization
It is body of data model, and stores in database.As can be seen here, the embodiment of the present invention is implemented, by the powerful of cloud computing technology
Disposal ability and mass data storage ability, body and its reasoning, Methods of Knowledge Discovering Based are combined, and mass users are analyzed in real time
Behavioral data, obtains user interest in time, so as to realize effectively being pushed with accurately user.
The embodiment of the present invention also provides a kind of computer-readable storage medium, wherein, the computer-readable storage medium can be stored with journey
Sequence, including the part of the monitoring method of any service processes or full step in the above method embodiment when program is performed.
It should be noted that for foregoing each method embodiment, in order to be briefly described, therefore it is all expressed as a series of
Combination of actions, but those skilled in the art should know, the present invention not by described by sequence of movement limited because
According to the present invention, some steps can sequentially or simultaneously be carried out using other.Secondly, those skilled in the art should also know
Know, the embodiment described by specification China belongs to preferred embodiment, involved action and unit not necessarily this hair
Necessary to bright.
The not enough order of the method for the embodiment of the present invention can according to actual needs be adjusted, merges or delete.This hair
The unit of the terminal of bright embodiment can according to actual needs be integrated, further divide or delete.
In the above-described embodiments, the description to each embodiment all emphasizes particularly on different fields, and does not have the portion described in detail in certain embodiment
Point, the associated description of other embodiment can be participated in.
In several embodiments provided herein, it should be understood that disclosed system, can be in other way
Realize, for example, system embodiment described above is schematical, such as the division of described unit is a kind of logic function
Divide, there can be other dividing mode when actually realizing, such as multiple units or component can be combined or be desirably integrated into
Another system, or some features can be ignored, or not perform.It is another, shown or discussed coupling each other or
Direct-coupling or communication connection can be that the brief introduction coupling or communication connection of device or unit, can be electricity by some interfaces
Property or other form.
The unit that is illustrated as separating component can be or may not be it is physically separate, it is aobvious as unit
The part for showing can be or can also be physical location, you can with positioned at a place, or can also be distributed to many
On individual NE.Some or all of unit therein can be according to the actual needs selected to realize this embodiment scheme
Purpose.
In addition, during each functional unit in each embodiment of the invention can be integrated in a processing unit, it is also possible to
It is that unit is individually physically present, it is also possible to which two or more units are integrated in a unit.Above-mentioned integrated list
Unit can both be realized in the form of hardware, it would however also be possible to employ the form of SFU software functional unit is realized.
It is worth noting that, in above-mentioned multi-point thermo detector reporting system and terminal device embodiment based on Internet of Things, institute
Including unit be to be divided according to function logic, but above-mentioned division is not limited to, as long as can realize
Corresponding function；In addition, the specific name of each functional unit is also only to facilitate mutually differentiation, is not limited to this
The protection domain of invention.
In addition, one of ordinary skill in the art will appreciate that all or part of step in the various methods of above-described embodiment
Program be can be by instruct the hardware of correlation to complete, the program can be stored in a computer-readable recording medium,
Storage medium include read-only storage (Read-Only Memory, ROM), random access memory (Random Access Memory,
RAM), programmable read only memory (Programmable Read-only Memory, PROM), erasable programmable is read-only deposits
Reservoir (Erasable Programmable Read OnlyMemory, EPROM), disposable programmable read-only storage (One-
Time Programmable Read-Only Memory, OTPROM), the electronics formula of erasing can make carbon copies read-only storage
(Electrically-Erasable Programmable Read-Only Memory, EEPROM), read-only optical disc (Compact
Disc Read-OnlyMemory, CD-ROM) or other disk storages, magnetic disk storage, magnetic tape storage or can use
In carrying or computer-readable any other medium of data storage.
The present invention preferably specific embodiment is these are only, but protection scope of the present invention is not limited thereto, it is any
Those familiar with the art the change that can readily occur in or replaces in the technical scope that the embodiment of the present invention is disclosed
Change, should all be included within the scope of the present invention.Therefore, protection scope of the present invention should be with the protection model of claim
Enclose and be defined.
Claims (10)
1. it is a kind of based on big data excavate user behavior analysis method, it is characterised in that including：
Collection user behavior data；
User behavior data is pre-processed and be polymerized using concurrent operation model；
According to the user behavior data after polymerization, user behavior data ontology model is set up, and store in database.
2. method according to claim 1, it is characterised in that methods described also includes,
User behavior data ontology model is made inferences, the newest interesting data of user is found out.
3. method according to claim 1, it is characterised in that
The user behavior data include user behavior main body, time of origin, occur the page, the scroll-up/down page, movement or
Mouse, page residence time are clicked on, collected, printed, preserving, accessing same page number of times, replicating and paste text operation, current use
The corresponding title of the search condition at family, search key.
4. method according to claim 1, it is characterised in that
The pretreatment includes：Removal deficiency of data, deleting duplicated data, picture, page animation；To beating that the page is carried out
Print, collection, preservation, down operation, after the acquisition, are converted into corresponding data form and are stored in database；
The data aggregate includes：To correct but invalid user behavior information, it is polymerized using rule-based user behavior and is calculated
Method is filtered, integrated.
5. method according to claim 4, it is characterised in that described to set up user behavior data ontology model, specifically includes：
User behavior data ontology model is set up using OWL-DL description languages, and ontology model is decomposed, the data
Storehouse is using the non-relational distributed data base increased income.
6. it is a kind of based on big data excavate user behavior analysis system, it is characterised in that
Collecting unit, for gathering user behavior data；
Pretreatment unit, for user behavior data to be pre-processed and be polymerized using concurrent operation model；
Modeling unit, for according to the user behavior data after polymerization, setting up user behavior data ontology model, and stores in number
According in storehouse.
7. system according to claim 6, it is characterised in that the system also includes：
Reasoning element, for being made inferences to user behavior data ontology model, finds out the newest interesting data of user.
8. system according to claim 7, it is characterised in that the user behavior data includes user behavior main body, hair
Mouse, page residence time, collection, printing, preservation, visit are clicked in raw time, the page for occurring, the scroll-up/down page, movement
Same page number of times is asked, is replicated and is pasted text operation, the search condition of active user, the corresponding title of search key.
9. the system stated according to claim 7, it is characterised in that
The pretreatment includes：Removal deficiency of data, deleting duplicated data, picture, page animation；To beating that the page is carried out
Print, collection, preservation, down operation, after the acquisition, are converted into corresponding data form and are stored in database；
The data aggregate includes：To correct but invalid user behavior information, it is polymerized using rule-based user behavior and is calculated
Method is filtered, integrated.
10. system according to claim 6, it is characterised in that
The modeling unit specifically for：User behavior data ontology model is set up using OWL-DL description languages, and to body
Model is decomposed, and the database is using the non-relational distributed data base increased income.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108829704A (en) * | 2018-04-28 | 2018-11-16 | 安徽瑞来宝信息科技有限公司 | A kind of big data distributed libray Analysis Service technology |
| WO2020000207A1 (en) * | 2018-06-26 | 2020-01-02 | 深圳市爱的网络科技有限公司 | User interest acquisition method, device, computer device and computer readable storage medium |
| CN112990291A (en) * | 2021-03-10 | 2021-06-18 | 东北大学 | User behavior analysis system and method based on data mining technology |
| CN115718846A (en) * | 2022-12-22 | 2023-02-28 | 云南炳暖蔡网络科技有限公司 | Big data mining method and system for intelligent interactive network |
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| CN103793465A (en) * | 2013-12-20 | 2014-05-14 | 武汉理工大学 | Cloud computing based real-time mass user behavior analyzing method and system |
| CN104462213A (en) * | 2014-12-05 | 2015-03-25 | 成都逸动无限网络科技有限公司 | User behavior analysis method and system based on big data |
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| CN103793465A (en) * | 2013-12-20 | 2014-05-14 | 武汉理工大学 | Cloud computing based real-time mass user behavior analyzing method and system |
| CN104462213A (en) * | 2014-12-05 | 2015-03-25 | 成都逸动无限网络科技有限公司 | User behavior analysis method and system based on big data |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108829704A (en) * | 2018-04-28 | 2018-11-16 | 安徽瑞来宝信息科技有限公司 | A kind of big data distributed libray Analysis Service technology |
| WO2020000207A1 (en) * | 2018-06-26 | 2020-01-02 | 深圳市爱的网络科技有限公司 | User interest acquisition method, device, computer device and computer readable storage medium |
| CN112990291A (en) * | 2021-03-10 | 2021-06-18 | 东北大学 | User behavior analysis system and method based on data mining technology |
| CN115718846A (en) * | 2022-12-22 | 2023-02-28 | 云南炳暖蔡网络科技有限公司 | Big data mining method and system for intelligent interactive network |
| CN115718846B (en) * | 2022-12-22 | 2023-10-27 | 北京国联视讯信息技术股份有限公司 | Big data mining method and system for intelligent interaction network |
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Application publication date: 20170531 |