CN105516928A - Position recommending method and system based on position crowd characteristics - Google Patents
Position recommending method and system based on position crowd characteristics Download PDFInfo
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- CN105516928A CN105516928A CN201610030493.2A CN201610030493A CN105516928A CN 105516928 A CN105516928 A CN 105516928A CN 201610030493 A CN201610030493 A CN 201610030493A CN 105516928 A CN105516928 A CN 105516928A
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- 238000000034 method Methods 0.000 title claims abstract description 27
- 230000011664 signaling Effects 0.000 claims abstract description 15
- 230000000694 effects Effects 0.000 claims description 10
- 238000003064 k means clustering Methods 0.000 claims description 3
- 235000012054 meals Nutrition 0.000 claims description 3
- 230000005855 radiation Effects 0.000 claims description 3
- 238000002372 labelling Methods 0.000 abstract 1
- 238000005516 engineering process Methods 0.000 description 6
- 238000004458 analytical method Methods 0.000 description 4
- 230000009286 beneficial effect Effects 0.000 description 4
- 238000004891 communication Methods 0.000 description 2
- 238000011835 investigation Methods 0.000 description 2
- 238000010295 mobile communication Methods 0.000 description 2
- PEDCQBHIVMGVHV-UHFFFAOYSA-N Glycerine Chemical compound OCC(O)CO PEDCQBHIVMGVHV-UHFFFAOYSA-N 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 238000005065 mining Methods 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000007794 visualization technique Methods 0.000 description 1
Classifications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/021—Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
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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
- G06F16/40—Information retrieval; Database structures therefor; File system structures therefor of multimedia data, e.g. slideshows comprising image and additional audio data
- G06F16/48—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
- G06F16/487—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using geographical or spatial information, e.g. location
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
Abstract
The invention relates to a position recommending method and system based on position crowd characteristics. The method comprises the following steps: S1, meshing all base station sectors in a region to be detected and marking grids; S2, acquiring total user real-time signaling data of the region to be detected, and finding out mobile users appearing in the meshed region according to the signaling data; S3, labeling the mobile users appearing in each grid, and counting up the quantity of the users with various types of labels of each grid under each network mark; S4, clustering the mobile users in each base station sector according to a statistical result of the step S3, so as to obtain the position crowd characteristics of the base station sectors; S5, providing position recommending information for site selection of marketing campaigns according to the position crowd characteristics. With the adoption of the position recommending method and system based on the position crowd characteristics, provided by the invention, the problems in the prior art that data needs to be manually acquired offline so that the efficiency is low and the accuracy is not high are solved.
Description
Technical field
The present invention relates to marketing activity addressing, be specifically related to a kind of position recommend method and system of position-based crowd characteristic.
Background technology
For a series of planning scheme activities such as addressing under marketing activity, line, crowd's clusters, conventional method is all take market survey method, namely by the market factor gathering several microcosmic artificial under line, comprise and measure crowd density, group characteristic, investigation the income level of consumption and crowd's preference etc.But the usual length consuming time of investigation method, manpower and materials consumption is serious, and some market factor is difficult to ensure that accurately coverage rate is low.Along with popularizing rapidly of mobile Internet and developing rapidly of information technology, this category information can treatment and processing, application model, mining analysis.
In the prior art, a kind of is the body templates obtained according to the information scanning in standardized human body's template database in current frame video image, then judge that the front line direction of the body templates got is towards first direction or second direction, when judging that before above-mentioned body templates, first direction counting is added one as during first direction by line direction, when judging that before above-mentioned body templates, second direction counting is added one as during second direction by line direction, can dealing number accurately in Statistical monitor passage through above-mentioned steps, statistical error can not be caused because flow of the people is comparatively large, do not need to destroy ground and reduce monitoring cost simultaneously yet.And this method, topmost shortcoming needs dedicated video capture device, and entirety has high input, and the implementation cycle is long, is unfavorable for spread simultaneously.Moreover this technology only simply solves the problem of stream of people's quantity statistics, cannot analyze for the individual behavior in the stream of people.
Another kind is by generalized information system functional characteristics and utilization in practice, in conjunction with the developing state of supermarket in CHINESE REGION and the keen competition faced.Analyze the intuitive of generalized information system to supermarket addressing, the convenience of amount of information statistics.The thinking of solution site selection model that the addressing marketing model proposing chain-supermarket proposes, namely under the support of GIS GIS-Geographic Information System, to the model visualization method of the index extracted and foundation come clear, solve location problem intuitively.
Addressing recommendation is carried out in this application by GIS technology, the quality contrast of all geographical location information can be represented intuitively, but it is progressively fierce in current commercial competition, in even perfervid situation, do not carry out comprehensive analysis and judgement in conjunction with the daily behavior of audience or potential customers and consumption habit, its precision of recommending can very low.
Summary of the invention
Technical problem to be solved by this invention is to provide a kind of position recommend method and system of position-based crowd characteristic, solve exist in prior art need artificial image data under line, cause efficiency low and the not high problem of accuracy.
The technical scheme that the present invention solves the problems of the technologies described above is as follows: a kind of position recommend method of position-based crowd characteristic, comprising:
S1, by base station section griddings all in region to be measured, and identifies grid;
S2, gathers the real-time signaling data in region to be measured, and finds out the mobile subscriber occurred in gridding region according to described signaling data;
S3, stamps label to the mobile subscriber occurred in each grid, and under adding up each Marking the cell, described each grid has the number of users of all kinds of label;
S4, according to the statistics of S3 by the mobile subscriber's cluster in each described base station section, obtains the position crowd characteristic of described base station section;
S5, according to described position crowd characteristic for marketing activity addressing provides position recommendation information.
The invention has the beneficial effects as follows: by gathering information of mobile communication base station, obtain client's real time position, by statistics, can obtain the flow of the people situation of certain place or region fast, position-based stamps label; Mobile subscriber is carried out cluster, forms the crowd characteristic of this position; Based on the crowd characteristic of this position, be supplied to business recommended foundation, can not limit by regional extent.
On the basis of technique scheme, the present invention can also do following improvement:
Further, described step S3 stamps being implemented as follows of label to the mobile subscriber occurred in each grid:
S31, obtains the Internet daily record of the described mobile subscriber occurred in gridding region, finds out the preference data of described mobile subscriber;
S32, is combined the preference data of described mobile subscriber with the related data prestored in Operator Specific Service support system, forming position feature tag collection;
S33, stamps respective labels to the mobile subscriber that each grid occurs according to described position feature tally set.
The beneficial effect of above-mentioned further scheme is adopted to be: the location data of telecom operators and internet behavior data to be combined, simultaneously in conjunction with the communication service data in the past of user and the relevant information of use mobile phone terminal, can in conjunction with the daily the Internet internet behavior of audience or potential customers and consumption habit, comprehensive analysis and judgement are carried out from time and space and audience feature three dimensions, the three-dimensional method with recommended location of portraying, the precision that position is recommended is high.
Further, preference data described in described S31 comprises described mobile subscriber message reference preference on the internet and search concern preference.
Further, the described pass data prestored in Operator Specific Service support system in described step S32 comprise essential information, label data and code table.
Further, described essential information comprises sex, age, terminal related information, set meal and business use amount;
Described label data comprises high flow capacity user, demand of changing planes user and travelling merchants personage;
Described code table comprises base station section coding, physical location, longitude and latitude and radiation radius.
Further, described position feature tally set comprises high flow capacity class label, identity class label, income class label and preference class label.
Further, k-means clustering method is adopted to carry out cluster in described step S4.
The another kind of technical scheme that the present invention solves the problems of the technologies described above is as follows: a kind of position commending system of position-based crowd characteristic, comprising:
Gridding module, for by base station section griddings all in region to be measured, and identifies grid;
Acquisition module, for gathering the real-time signaling data in region to be measured, and finds out the mobile subscriber occurred in gridding region according to described signaling data;
Mark module, for stamping label to the mobile subscriber occurred in each grid, and under adding up each Marking the cell, described each grid has the number of users of all kinds of label;
Cluster module, for according to the statistics of S3 by the mobile subscriber's cluster in each described base station section, obtain the position crowd characteristic of described base station section;
Position recommending module, for according to described position crowd characteristic for marketing activity addressing provides position recommendation information.
The invention has the beneficial effects as follows: by gridding module by geographic area gridding, acquisition module gathers information of mobile communication base station, obtain client's real time position, by statistics, can obtain the flow of the people situation of certain place or region fast, mark module position-based stamps the various above labels of individual consumer; Individual consumer is carried out cluster by cluster module, forms the crowd characteristic of this position; Thus based on the crowd characteristic of this position, be supplied to business recommended foundation, can realize not limiting by regional extent.
On the basis of technique scheme, the present invention can also do following improvement:
Further, described mark module comprises:
Preference data acquiring unit, for obtaining the Internet daily record of the described mobile subscriber occurred in gridding region, finds out the preference data of described mobile subscriber;
Tally set acquiring unit, for the preference data of described mobile subscriber is combined with the related data prestored in Operator Specific Service support system, forming position feature tag collection.
The beneficial effect of above-mentioned further scheme is adopted to be: the location data of telecom operators and internet behavior data combine by tally set acquiring unit, simultaneously in conjunction with the communication service data in the past of user and the relevant information of use mobile phone terminal, can in conjunction with the daily the Internet internet behavior of audience or potential customers and consumption habit, comprehensive analysis and judgement are carried out from time and space and audience feature three dimensions, the three-dimensional method with recommended location of portraying, the precision that position is recommended is high.
Further, described position feature tally set comprises high flow capacity class label, identity class label, income class label and preference class label.
Accompanying drawing explanation
Fig. 1 is the schematic flow sheet of the position recommend method of a kind of position-based crowd characteristic of the present invention;
Fig. 2 is the structural representation of the position commending system of a kind of position-based crowd characteristic of the present invention.
Embodiment
Be described principle of the present invention and feature below in conjunction with accompanying drawing, example, only for explaining the present invention, is not intended to limit scope of the present invention.
As shown in Figure 1, a kind of position recommend method of position-based crowd characteristic, comprising:
S1, by base station section griddings all in region to be measured, and identifies grid;
S2, gathers the real-time signaling data of mobile subscriber in region to be measured, and finds out the mobile subscriber occurred in gridding region according to described signaling data; Wherein, in units of day, analyze signaling data, find out the mobile subscriber occurred in gridding region;
S3, stamps label to the mobile subscriber occurred in each grid, and under adding up each Marking the cell, described each grid has the number of users of all kinds of label;
S4, according to the statistics of S3 by the mobile subscriber's cluster in each described base station section, obtains the position crowd characteristic of described base station section;
S5, according to described position crowd characteristic for marketing activity addressing provides position recommendation information.
Described step S3 stamps being implemented as follows of label to the mobile subscriber occurred in each grid: S31, obtains the Internet daily record of the described mobile subscriber occurred in gridding region, find out the preference data of described mobile subscriber; Wherein, in units of the moon, obtain the Internet daily record of the mobile subscriber occurred in gridding region and DPI is analyzed; Preference data described in described step S31 comprises described mobile subscriber message reference preference on the internet and preference is paid close attention in search.
S32, is combined the preference data of described mobile subscriber with the related data prestored in Operator Specific Service support system, forming position feature tag collection; The described pass data prestored in Operator Specific Service support system in described step S32 comprise essential information, label data and code table.
Described essential information comprises sex, age, the relevant information of terminal, set meal and business use amount; The relevant information of terminal can comprise: the parameters such as the price of terminal and model;
Described label data comprises high flow capacity user, demand of changing planes user and travelling merchants personage; Wherein, high flow capacity user refers to the user also needing additionally to handle flow bag outside the flow that comprises at the packaged service oneself handled every month; Such as: outside specified flow, later stage every month also needs the user being dominated reason flow oiling bag by note.
Described code table comprises base station section coding, physical location, longitude and latitude and radiation radius.Code table be the related data of mobile subscriber for the ease of prestoring in Operator Specific Service support system corresponding with the user of the preference data of acquisition on, avoid occur mistake information matches.
S33, stamps respective labels to the mobile subscriber that each grid occurs according to described position feature tally set.
Described position feature tally set comprises high flow capacity class label, identity class label, income class label and preference class label.
K-means clustering method is adopted to carry out cluster in described step S4.
Based on foregoing invention, position feature tally set is input to addressing application data base, user in use, can in web front-end input position feature tag and the band of position scope of delimiting a fair-sized, system reads the sector of most matched position feature tag in this region, thus in web terminal display, for marketing activity addressing provides recommended location.
As shown in Figure 2, a kind of position commending system of position-based crowd characteristic, comprising:
Gridding module, for by base station section griddings all in region to be measured, and identifies grid;
Acquisition module, the real-time signaling data of the mobile subscriber for gathering region to be measured, and the mobile subscriber occurred in gridding region is found out according to described signaling data;
Mark module, for stamping label to the mobile subscriber occurred in each grid, and under adding up each Marking the cell, described each grid has the number of users of all kinds of label;
Cluster module, for according to the statistics of S3 by the mobile subscriber's cluster in each described base station section, obtain the position crowd characteristic of described base station section;
Position recommending module, for according to described position crowd characteristic for marketing activity addressing provides position recommendation information.
Described mark module comprises:
Preference data acquiring unit, for obtaining the Internet daily record of the described mobile subscriber occurred in gridding region, finds out the preference data of described mobile subscriber;
Tally set acquiring unit, for the preference data of described mobile subscriber is combined with the related data prestored in Operator Specific Service support system, forming position feature tag collection.
Described position feature tally set comprises high flow capacity class label, identity class label, income class label and preference class label.
The foregoing is only preferred embodiment of the present invention, not in order to limit the present invention, within the spirit and principles in the present invention all, any amendment done, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.
Claims (10)
1. a position recommend method for position-based crowd characteristic, is characterized in that, comprising:
S1, by base station section griddings all in region to be measured, and identifies grid;
S2, gathers the real-time signaling data in region to be measured, and finds out the mobile subscriber occurred in gridding region according to described signaling data;
S3, stamps label to the mobile subscriber occurred in each grid, and under adding up each Marking the cell, described each grid has the number of users of all kinds of label;
S4, according to the statistics of S3 by the mobile subscriber's cluster in each described base station section, obtains the position crowd characteristic of described base station section;
S5, according to described position crowd characteristic for marketing activity addressing provides position recommendation information.
2. the position recommend method of a kind of position-based crowd characteristic according to claim 1, is characterized in that, described step S3 stamps being implemented as follows of label to the mobile subscriber occurred in each grid:
S31, obtains the Internet daily record of the described mobile subscriber occurred in gridding region, finds out the preference data of described mobile subscriber;
S32, is combined the preference data of described mobile subscriber with the related data prestored in Operator Specific Service support system, forming position feature tag collection;
S33, stamps respective labels to the mobile subscriber that each grid occurs according to described position feature tally set.
3. the position recommend method of a kind of position-based crowd characteristic according to claim 2, is characterized in that, preference data described in described step S31 comprises described mobile subscriber message reference preference on the internet and preference is paid close attention in search.
4. the position recommend method of a kind of position-based crowd characteristic according to claim 2, it is characterized in that, the described pass data prestored in Operator Specific Service support system in described step S32 comprise essential information, label data and code table.
5. the position recommend method of a kind of position-based crowd characteristic according to claim 4, it is characterized in that, described essential information comprises sex, age, terminal related information, set meal and business use amount;
Described label data comprises high flow capacity user, demand of changing planes user and travelling merchants personage;
Described code table comprises base station section coding, physical location, longitude and latitude and radiation radius.
6. the position recommend method of a kind of position-based crowd characteristic according to claim 2, is characterized in that, described position feature tally set comprises high flow capacity class label, identity class label, income class label and preference class label.
7. the position recommend method of a kind of position-based crowd characteristic according to claim 1, is characterized in that, adopt k-means clustering method to carry out cluster in described step S4.
8. a position commending system for position-based crowd characteristic, is characterized in that, comprising:
Gridding module, for by base station section griddings all in region to be measured, and identifies grid;
Acquisition module, for gathering the real-time signaling data in region to be measured, and finds out the mobile subscriber occurred in gridding region according to described signaling data;
Mark module, for stamping label to the mobile subscriber occurred in each grid, and under adding up each Marking the cell, described each grid has the number of users of all kinds of label;
Cluster module, for according to the statistics of S3 by the mobile subscriber's cluster in each described base station section, obtain the position crowd characteristic of described base station section;
Position recommending module, for according to described position crowd characteristic for marketing activity addressing provides position recommendation information.
9. the position commending system of a kind of position-based crowd characteristic according to claim 8, it is characterized in that, described mark module comprises:
Preference data acquiring unit, for obtaining the Internet daily record of the described mobile subscriber occurred in gridding region, finds out the preference data of described mobile subscriber;
Tally set acquiring unit, for the preference data of described mobile subscriber is combined with the related data prestored in Operator Specific Service support system, forming position feature tag collection.
10. the position commending system of a kind of position-based crowd characteristic according to claim 9, is characterized in that, described position feature tally set comprises high flow capacity class label, identity class label, income class label and preference class label.
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Cited By (18)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN106156804A (en) * | 2016-08-16 | 2016-11-23 | 浙江工业大学 | A kind of movement doubtful population at risk sorting technique based on K means cluster |
| CN106547894A (en) * | 2016-11-03 | 2017-03-29 | 浙江夏农信息技术有限公司 | The system and method that location tags are lived in duty is excavated based on mobile communication signaling big data |
| CN108573265A (en) * | 2017-03-10 | 2018-09-25 | 中兴通讯股份有限公司 | People flow rate statistical method and statistical system |
| CN108632746A (en) * | 2018-03-21 | 2018-10-09 | 电信科学技术第十研究所有限公司 | A kind of method of determining region flow of the people |
| CN108876526A (en) * | 2018-06-06 | 2018-11-23 | 北京京东尚科信息技术有限公司 | Method of Commodity Recommendation, device and computer readable storage medium |
| CN109255538A (en) * | 2018-09-12 | 2019-01-22 | 中国联合网络通信集团有限公司 | The appraisal procedure and system of bank branches, server, storage medium |
| CN109657883A (en) * | 2019-01-28 | 2019-04-19 | 重庆邮电大学 | A kind of bank branches recommended method based on multi-source data driving |
| CN110019568A (en) * | 2019-04-12 | 2019-07-16 | 深圳市和讯华谷信息技术有限公司 | Site selecting method, device, computer equipment and storage medium based on space clustering |
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