CN107423385A - User's deep layer label method for digging based on big data - Google Patents
User's deep layer label method for digging based on big data Download PDFInfo
- Publication number
- CN107423385A CN107423385A CN201710588624.3A CN201710588624A CN107423385A CN 107423385 A CN107423385 A CN 107423385A CN 201710588624 A CN201710588624 A CN 201710588624A CN 107423385 A CN107423385 A CN 107423385A
- Authority
- CN
- China
- Prior art keywords
- user
- client
- deep layer
- digging
- big data
- 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
Classifications
-
- 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
- G06F16/2457—Query processing with adaptation to user needs
- G06F16/24573—Query processing with adaptation to user needs using data annotations, e.g. user-defined metadata
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/23—Clustering techniques
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Databases & Information Systems (AREA)
- Computational Linguistics (AREA)
- Library & Information Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Artificial Intelligence (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Biology (AREA)
- Evolutionary Computation (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The present invention provides a kind of user's deep layer label method for digging based on big data, and user's deep layer label method for digging includes：（1）According to the ID card No. of client, the information such as the native place of user, date of birth, sex are extracted；（2）Constellation, the Chinese zodiac, personality are further extrapolated according to the date of birth of client；（3）The species of product is bought according to client and some behavioural characteristics of user speculate the label of addition user；The user that business value is obtained according to the amount of consumption of client, the consumption frequency classifies.The present invention provides a kind of user's deep layer label method for digging based on big data, deeper label excavation is carried out to user, tagging management aspect is deep, to the accuracy of judgement of client.By carrying out labeling to user, the demand of client can be more accurately judged, safeguard and bind client.
Description
Technical field
The present invention relates to big data applied technical field, more particularly to a kind of user's deep layer label based on big data to excavate
Method.
Background technology
The process that user's portrait is established is exactly to add corresponding label, is referred to as labeling in Data Mining.Label is
The highly refined signature identification as obtained from analyzing user profile., can be more accurate by carrying out labeling to user
The true demand for judging client, safeguard and bind client.In the prior art, tagging management aspect is carried out not enough to user
Deep, the judgement to client is accurate not enough.
The content of the invention
It is an object of the invention to provide a kind of user's deep layer label method for digging based on big data, to solve above-mentioned skill
Art problem.
The present invention using following technical scheme in order to solve the above technical problems, realized：
A kind of user's deep layer label method for digging based on big data, it is characterised in that：According to user's social property, habits and customs
The user model of the labeling taken out with the information such as consumer behavior, user's deep layer label method for digging include：
（1）According to the ID card No. of client, the information such as the native place of user, date of birth, sex are extracted；
（2）Constellation, the Chinese zodiac, personality are further extrapolated according to the date of birth of client；
（3）The species of product is bought according to client and some behavioural characteristics of user speculate the label of addition user；According to client
The amount of consumption, consumption the frequency obtain business value user classification.
Preferably, carrying out cluster analysis to user according to These parameters synthesis, different user colony is finally given, each
Colony sets a label.
Preferably, according to the change of customer consumption volume, the consumption frequency and behavioural characteristic, the height of prediction customer loss probability
It is low, according to the height of customer loss probability, mark off different loss probability tags.
The beneficial effects of the invention are as follows：
The present invention provides a kind of user's deep layer label method for digging based on big data, and deeper label digging is carried out to user
Pick, tagging management aspect is deep, to the accuracy of judgement of client.By carrying out labeling to user, can more accurately judge
The demand of client, safeguard and bind client.
Embodiment
In order that the technical means, the inventive features, the objects and the advantages of the present invention are easy to understand, tie below
Specific embodiment is closed, the present invention is expanded on further, but following embodiments are only the preferred embodiments of the present invention, and it is not all.
Based on the embodiment in embodiment, those skilled in the art obtain other realities on the premise of creative work is not made
Example is applied, belongs to protection scope of the present invention.
Embodiment 1
A kind of user's deep layer label method for digging based on big data, it is characterised in that：According to user's social property, habits and customs
The user model of the labeling taken out with the information such as consumer behavior, user's deep layer label method for digging include：
（1）According to the ID card No. of client, the information such as the native place of user, date of birth, sex are extracted；
（2）Constellation, the Chinese zodiac, personality are further extrapolated according to the date of birth of client；
（3）The species of product is bought according to client and some behavioural characteristics of user speculate the label of addition user；According to client
The amount of consumption, consumption the frequency obtain business value user classification.
Embodiment 2
A kind of user's deep layer label method for digging based on big data, it is characterised in that：Practised according to user's social property, life
The information such as used and consumer behavior and the user model of a labeling taken out, user's deep layer label method for digging include：
（1）According to the ID card No. of client, the information such as the native place of user, date of birth, sex are extracted；
（2）Constellation, the Chinese zodiac, personality are further extrapolated according to the date of birth of client；
（3）The species of product is bought according to client and some behavioural characteristics of user speculate the label of addition user；According to client
The amount of consumption, consumption the frequency obtain business value user classification；
（4）Cluster analysis is carried out to user according to These parameters synthesis, finally gives different user colony, each colony sets one
Individual label.
Embodiment 3
A kind of user's deep layer label method for digging based on big data, it is characterised in that：Practised according to user's social property, life
The information such as used and consumer behavior and the user model of a labeling taken out, user's deep layer label method for digging include：
（1）According to the ID card No. of client, the information such as the native place of user, date of birth, sex are extracted；
（2）Constellation, the Chinese zodiac, personality are further extrapolated according to the date of birth of client；
（3）The species of product is bought according to client and some behavioural characteristics of user speculate the label of addition user；According to client
The amount of consumption, consumption the frequency obtain business value user classification；
（4）Cluster analysis is carried out to user according to These parameters synthesis, finally gives different user colony, each colony sets one
Individual label；
（5）According to customer consumption volume, consumption the frequency and behavioural characteristic change, predict customer loss probability height, according to
Family is lost in the height of probability, marks off different loss probability tags.
General principle, principal character and the advantages of the present invention of the present invention has been shown and described above.The technology of the industry
For personnel it should be appreciated that the present invention is not limited to the above embodiments, that described in above-described embodiment and specification is only the present invention
Preference, be not intended to limit the present invention, without departing from the spirit and scope of the present invention, the present invention also have it is various
Changes and improvements, these changes and improvements all fall within the protetion scope of the claimed invention.The claimed scope of the invention is by institute
Attached claims and its equivalent thereof.
Claims (3)
- A kind of 1. user's deep layer label method for digging based on big data, it is characterised in that：According to user's social property, life Custom and the information such as consumer behavior and the user model of a labeling taken out, user's deep layer label method for digging include：（1）According to the ID card No. of client, the information such as the native place of user, date of birth, sex are extracted；（2）Constellation, the Chinese zodiac, personality are further extrapolated according to the date of birth of client；（3）The species of product is bought according to client and some behavioural characteristics of user speculate the label of addition user；According to client The amount of consumption, consumption the frequency obtain business value user classification.
- 2. user's deep layer label method for digging according to claim 1 based on big data, it is characterised in that：According to above-mentioned Index comprehensive carries out cluster analysis to user, finally gives different user colony, and each colony sets a label.
- 3. user's deep layer label method for digging according to claim 1 based on big data, it is characterised in that：According to user The change of the amount of consumption, the consumption frequency and behavioural characteristic, the height of customer loss probability is predicted, according to the height of customer loss probability It is low, mark off different loss probability tags.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710588624.3A CN107423385A (en) | 2017-07-19 | 2017-07-19 | User's deep layer label method for digging based on big data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710588624.3A CN107423385A (en) | 2017-07-19 | 2017-07-19 | User's deep layer label method for digging based on big data |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN107423385A true CN107423385A (en) | 2017-12-01 |
Family
ID=60430116
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710588624.3A Pending CN107423385A (en) | 2017-07-19 | 2017-07-19 | User's deep layer label method for digging based on big data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107423385A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109460511A (en) * | 2018-10-25 | 2019-03-12 | 百度在线网络技术（北京）有限公司 | A kind of method, apparatus, electronic equipment and storage medium obtaining user's portrait |
| CN110197402A (en) * | 2019-06-05 | 2019-09-03 | 中国联合网络通信集团有限公司 | User tag analysis method, device, equipment and storage medium based on user group |
| CN110956188A (en) * | 2018-09-26 | 2020-04-03 | 北京融信数联科技有限公司 | Population behavior track digital coding method based on mobile communication signaling data |
| CN112258209A (en) * | 2020-09-01 | 2021-01-22 | 武汉策微信息科技有限公司 | Intelligent grading and tracking system for clients |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102609471A (en) * | 2012-01-18 | 2012-07-25 | 康睿 | Method and device for precisely analyzing network behaviors of Internet users |
| US20130268317A1 (en) * | 2010-12-07 | 2013-10-10 | Digital Foodie Oy | Arrangement for facilitating shopping and related method |
| CN105279533A (en) * | 2015-10-28 | 2016-01-27 | 上汽通用汽车有限公司 | Vehicle user tag management method and system |
| CN105787071A (en) * | 2016-03-02 | 2016-07-20 | 浪潮通信信息系统有限公司 | Method for carrying out mobile phone user behavior portrait based on informationized label |
-
2017
- 2017-07-19 CN CN201710588624.3A patent/CN107423385A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130268317A1 (en) * | 2010-12-07 | 2013-10-10 | Digital Foodie Oy | Arrangement for facilitating shopping and related method |
| CN102609471A (en) * | 2012-01-18 | 2012-07-25 | 康睿 | Method and device for precisely analyzing network behaviors of Internet users |
| CN105279533A (en) * | 2015-10-28 | 2016-01-27 | 上汽通用汽车有限公司 | Vehicle user tag management method and system |
| CN105787071A (en) * | 2016-03-02 | 2016-07-20 | 浪潮通信信息系统有限公司 | Method for carrying out mobile phone user behavior portrait based on informationized label |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110956188A (en) * | 2018-09-26 | 2020-04-03 | 北京融信数联科技有限公司 | Population behavior track digital coding method based on mobile communication signaling data |
| CN109460511A (en) * | 2018-10-25 | 2019-03-12 | 百度在线网络技术（北京）有限公司 | A kind of method, apparatus, electronic equipment and storage medium obtaining user's portrait |
| CN110197402A (en) * | 2019-06-05 | 2019-09-03 | 中国联合网络通信集团有限公司 | User tag analysis method, device, equipment and storage medium based on user group |
| CN112258209A (en) * | 2020-09-01 | 2021-01-22 | 武汉策微信息科技有限公司 | Intelligent grading and tracking system for clients |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107423385A (en) | User's deep layer label method for digging based on big data | |
| CN104899304B (en) | Name entity recognition method and device | |
| Mew | Phosphate rock costs, prices and resources interaction | |
| US11010768B2 (en) | Character-based attribute value extraction system | |
| CN107862027A (en) | Retrieve intension recognizing method, device, electronic equipment and readable storage medium storing program for executing | |
| CN104978356B (en) | A kind of recognition methods of synonym and device | |
| CN103136327A (en) | Time series signifying method based on local feature cluster | |
| CN106600052A (en) | User attribute and social network detection system based on space-time locus | |
| Li et al. | Cluster analysis of the relationship between carbon dioxide emissions and economic growth | |
| CN103631874B (en) | UGC label classification determining method and device for social platform | |
| CN108932648A (en) | A kind of method and apparatus for predicting its model of item property data and training | |
| CN110321549A (en) | Based on the new concept method for digging for serializing study, relation excavation, Time-Series analysis | |
| Chen et al. | The relationship between business performance, corporate social responsibility, and innovation capital: A case study of Taiwan | |
| CN105138552A (en) | Fashion tendency analysis system mining online sale data | |
| CN109919324B (en) | Transfer learning classification method, system and equipment based on label proportion learning | |
| Lin et al. | Using clustering algorithm to visualize spatial-temporal internet of things data in process of agricultural product circulation | |
| Harash et al. | Impact of Government policies in the Influence of Market practices on Financial Performance of small and medium enterprises (SMEs) in Iraq | |
| CN109767031A (en) | Model classifiers method for building up, device, computer equipment and storage medium | |
| CN106250522A (en) | A kind of online food and drink main label Fast Data Extraction Methodology estimated based on Gauss | |
| CN107506398B (en) | Method for adding label attribute to book | |
| Ali et al. | Foreign Direct Investment and Sustainable Long Run Economic Growth Nexus: A Case Study of Pakistan | |
| Bader et al. | Big data and sustainable supply chain management of hypermarkets in Jordan: An experimental study using structural equation modeling approach | |
| Ranjan et al. | History matched models can mis-lead the forecasting in the brownfield redevelopment projects: HM to prediction transition | |
| Rigopoulos et al. | A decision support system for supervised assignment in banking decisions | |
| CN105608072B (en) | Text is related to ground analysis method and its system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20171201 |