CN106339456A - Push method based on data mining - Google Patents
Push method based on data mining Download PDFInfo
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- CN106339456A CN106339456A CN201610731521.3A CN201610731521A CN106339456A CN 106339456 A CN106339456 A CN 106339456A CN 201610731521 A CN201610731521 A CN 201610731521A CN 106339456 A CN106339456 A CN 106339456A
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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
- G06F16/245—Query processing
- G06F16/2457—Query processing with adaptation to user needs
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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
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2465—Query processing support for facilitating data mining operations in structured databases
Abstract
The invention discloses a push method based on data mining. The push method comprises the steps of summarizing learning plan data and teaching resource data of a user through a cloud computing platform; collecting original data from all sensors of student mobile devices; performing data preprocessing on the original data and obtaining a data sequence; obtaining a lingering point sequence according to a lingering point detection method; performing cluster analysis on the lingering point sequence to obtain a site historical sequence; performing teaching resource search on each piece of data in the site historical sequence, and marking site history; matching and generating a message which is based on time, position and teaching resource data according to the data sequence, the marked site history and the learning plan data, and pushing the message to the user. The push method has the effect of pushing rich, in-time, accurate and individual teaching information to learners.
Description
Technical field
The present invention relates to technical field of data processing, specifically disclose a kind of method for pushing based on data mining.
Background technology
In recent years, become the popular vocabulary of Internet information technique industry with big data, education is considered as gradually big
The important applied field that data can be fully developed talents, big data will bring revolutionary change to education.
Data display, mobile Internet netizen's speedup is swift and violent.Global pc, functional mobile phone and panel computer shipment amount scale pair
Than in, intelligent mobile terminal shipment amount has exceeded pc.In foreseeable future, mobile terminal will become main Internet portal.
Meanwhile, mobile terminal is portable and the functional characteristics of instantaneity, and the also collection for data is provided convenience condition.
Put forth effort on and make based on the intelligent terminal tutoring system such as mobile, by the analysis of the big data to magnanimity scale with dig
Pick, subdivision of user behavior etc., support strategy by a series of learning management, complete the support precisely learning to guide, and then
Obtain abundant, instant, accurate, personalized education resource for student to provide the necessary technical support, improve the quality of teaching.But
Not yet there is one at present effectively, based on data mining, be that students push abundant, instant, accurate, personalized teaching
The method of information.
Content of the invention
The invention is intended to providing a kind of method for pushing based on data mining, to solve the above problems.
The method for pushing based on data mining for one of this programme, comprising: using cloud computing platform by the study of user
Planning data and teaching resource data summarization；
Each sensor collection initial data from user's mobile device；
Data prediction is carried out to initial data and obtains data sequence；
Resident point sequence is obtained according to dwell point detection mode；
Cluster analysis is carried out to described resident point sequence, obtains place historical series；
Teaching resource search is carried out to each data in the historical series of place, and place history is marked；
According to the place history after data sequence, mark and study plan data, coupling generates based on time, position and religion
The message learning resource data is pushed to user.
Further, described initial data includes location data.
Further, described location data include cell tower triangle polyester fibre data, wi-fi node data library inquiry data and
Gps location data.
Further, the described data characteristicses according to each sensor and energy consumption feature carry out data prediction simultaneously to initial data
The step obtaining data sequence includes: carries out coordinate transform to the location data collected；Coordinate after conversion is carried out in the school
Geographical index；By in user id, longitude and latitude, timestamp, in the school geographical index result and record id write into Databasce.
Further, described study plan data, the course selected when learning cycle starts including user, the current institute of student
The list that technical ability, books, data must be needed of curricula-variable journey.
Further, described teaching resource data, including course, class hour arrangement, teacher arranges, classroom arranges, course figure
Letter breath, currently available seat, currently available lab resources.
The present invention may operate on the smart mobile phone that most people is all carried with daily, have preferable flexibility and
Portable；To collect initial data from the built-in various sensors of mobile device, behavior pattern that can effectively to user
Information is made identification and is inferred, and then automatically pushes scheme for the personalized education informations of user's generation；This push scheme will
Action trail for user carries out corresponding optimization processing, except can formulate study plan for user, also with good grounds
The behavior pattern information of user pointedly generates the pushed information based on time, position and all kinds of teaching resource, and with
The change of family behavior pattern can adaptively carry out the adjustment that education informations push scheme, without extra configuration；And,
The software that the program is realized can interact the affairs prompt energy so that generating using the corresponding interface and the built-in annoyware of system
, in the other equipment of user, more convenient, Consumer's Experience is good for enough automatic synchronizations.
Brief description
Fig. 1 is the method flow diagram of data mining in the embodiment of the present invention；
Fig. 2 is the software basic framework schematic diagram involved by inventive embodiments method；
Fig. 3 is the schematic diagram of the preprocessing process of location data；
Fig. 4 is dwell point detection process schematic diagram.
Specific embodiment
Below by specific embodiment, the present invention is further detailed explanation:
Generally all it is built-in with various sensors in mobile device, they have recorded substantial amounts of initial data, need therefrom to excavate more
Valuable information.At present, a large number of users is got used to carrying with smart mobile phone or panel computer daily, and its sensing data is very
Have recorded well the behavior pattern of user.In the present invention, from mobile device each sensor collection to initial data start with,
For the feature of different sensors, set up the model of corresponding data processing.
First data is pre-processed, then carry out data mining, therefrom extract user's row relevant with Learning in School
For pattern, and then can be using the behavior pattern information obtaining, in conjunction with the study plan in the user section time and school
The teaching resource of itself is targeted to user to push all kinds of education informations.
The present embodiment is used for most of mobile intelligent terminal at present, therefore has preferable universality.
Software is c-s framework, develops client, develop its server in publicly-owned cloud platform on mobility device
End.First, server end collects the study plan data of user and the teaching data resource data of school；
Software should wait sensor collection information by the built-in gps of mobile device, accelerometer, gyroscope, microphone, distance perspective, knot
Close process monitoring to obtain user profile and upload onto the server.
On the one hand, server end can be according to user's course selected when learning cycle starts, the currently selected course of user
Must need technical ability list information, and the teaching resource information related to first two information, to user push customize letter
Breath, including course, class hour arrangement, teacher's arrangement, classroom arrangement, course book information, currently available seat, currently available reality
Test room resource etc..
On the other hand, the information that server end comprehensive analysis are obtained, the information of evolution data collection, constantly near this user
Behavior pattern, progressively train after can automatically be user generation be pushed away based on the personalization of time, position and all kinds of teaching resource
Deliver letters breath, and automatically write built-in annoyware.
Fig. 1 is the method for the data mining of the embodiment of the present invention, as shown in figure 1, the method includes:
S101, from each sensor collection initial data of mobile device；
S102, carries out data prediction to initial data and obtains data sequence；
S103, obtains resident point sequence according to dwell point detection mode；
S104, carries out cluster analysis to resident point sequence, obtains place historical series；
S105, carries out teaching resource search to each data in the historical series of place, and place history is marked；
As shown in Fig. 2, software basic framework involved by present invention method, under the framework of ios operating system
For:
Server is responsible for persisting user data, so that user is conveniently used distinct device and carries out Data Collection；
coremotion
Framework is responsible for obtaining the data of the sensors such as accelerometer, gyroscope and the electronic compass of user；Corelocation frame
Frame is responsible for obtaining the position data of user from cell tower, wi-fi access point and gps satellite；Sharekit framework obtains
User society
Hand over the text message that network account sends and be uploaded to sae server and preserved.When the data collecting q.s
Afterwards, visitor
Locally processed and analyzed after family end request downloading data.
In s101, the smart mobile phone of ios operating system adopts corelocation framework to collect location data, positioning
Data includes cell tower triangle polyester fibre data, wi-fi node data library inquiry data and gps location data.According to different
Ambient conditions uses one or more of these three modes, thus while ensureing degree of precision.By coremotion
Framework can also collect the motion state initial data from sensors such as accelerometer, gyroscope, electronic compass.
In embodiments of the present invention, the preprocessing process of location data is as shown in figure 3, original to the positioning collected first
Data carries out coordinate transform；Then the coordinate after conversion is carried out geographical index in the school, in order to auxiliary judgment；Finally, by user
Id, longitude and latitude, in timestamp, in the school geographical index result and record id write into Databasce.Will be directed in particular therein below
It is illustrated in detail.
In being embodied as, the geographic coordinate data that gps is collected is designated as (latitude, longitude).Due to this
Data is based on wgs-84 coordinate system, and needs according to State Bureau of Surveying and Mapping, geographic coordinate information to be carried out at non-linear biasing
Reason, to meet the Encryption Standard algorithm of survey office of state.Coordinate system after conversion is gcj-02 coordinate system (guojia cehuiju-
02coordinate system), the coordinate after conversion is designated as (latitude ', longitude ')；To the coordinate after conversion
(latitude ', longitude ') carry out geographical index in the school, thus the information more enriched, as this coordinate position institute
The classroom number belonging to, teaching building is designated as (roomno, building), and similar index can also be road, playground etc. in the school；These
The effect of auxiliary is played in the analysis to later data for the information and the judgement to customer location；And by user id, conversion after warp
Latitude, timestamp, geographical index result is together with record id together write into Databasce in the school.
In this enforcement, middle smart mobile phone updates an initial data in every 10 seconds；
After obtaining a user position update, coordinate transform is carried out with regard to request server pair warp and weft degree immediately.Every record comprises
Record id, user id, the longitude and latitude after conversion, timestamp and the data such as geographical index in the school.Establish in server end and comprise
The database of user message table data record sheet, in order to store the relevant information of user.
Below s103 is expanded on further.
In embodiments of the present invention, dwell point (stay point) probe algorithm has been carried out improving so as in single use
In the scene that the many days sensing datas in family are processed can effectively to user not same date sensing data sequence disposably
Processed.Fig. 4 is dwell point detection process schematic diagram.
It is achieved that dwell point (stay point) detection being applied to the many day data of single user is calculated in the embodiment of the present invention
Method, disposably to process to the data of many days.The input of improved dwell point monitoring algorithm is geographic coordinate information, defeated
Go out for resident point coordinates and corresponding timestamp, dwell point sequence information is stored in the local file of terminal.Consider in actual feelings
In condition, user collects whole day data and is usually started by morning and gets up, when terminating at shutdown before evening sleep.In original dwell point
In detection, if the last data point exactly user that collects of mobile device is to when family, then due to user without departing from
Distance threshold in this algorithm, therefore last dwell point will be lost.In the detection process of dwell point, to not same date
Data makes a distinction, and has finally carried out independent judgement with the presence or absence of dwell point in data sequence, efficiently avoid resident
The disappearance of point data.Dwell point detection is carried out to the geographical coordinate after conversion, and then generates resident point sequence.
Below s104 is described in detail.
Due to consider be unique user sensing data cluster analysis it is not desired to obtain hierarchical clustering result,
And in the scene described in the embodiment of the present invention, the point in data acquisition system is possible to constitute various irregular shapes, in data
Also some noises are inevitably comprised.Consider the factor of the aspects such as these problems and amount of calculation, here using suitable
Close dbscan cluster (the density-based spatial clustering of processing these problems
Applicationswith noise) algorithm carries out cluster analysis to dwell point, be equivalent to input data point has been carried out single
The division of aspect.
However, because this algorithm uses same parameter epsilon and minimumpoints to each dimension, therefore
Need the data on different dimensions is carried out " normalization " and process so that the data energy of different pieces of information scope even not commensurate
Enough carry out cluster analysis effectively under identical parameter and standard.Dbscan cluster analysis is actually concentrated all of to data
Point has actually carried out a division, or these points belong to some cluster of algorithm generation, or just for noise.To dbscan
The output result of algorithm is processed further, and the mean value calculating the longitude of point in each cluster and latitude respectively is as each
Cluster center point coordinate.Each point in cluster is ranked up according to the timestamp in record, calculates each point subscript in array in cluster
The mark of the point of median, as the mark of this cluster central point.
In three dimensions, cluster analysis is carried out to data point, these three dimensions are respectively longitude (latitude), latitude
And arrival time (arrivingtime) (longitude).Because temporal information is not floating point type, here has first carried out pre-
Process, defined feature value is to calculate characteristic value the considering as time dimension numerical values recited of each point timestamp.Obtain after cluster
The center of each cluster and corresponding timestamp information, are deposited into local file.
In addition, the specific implementation process of s105 is as follows:
First, point centered on the gcj-02 coordinate after each resident point transformation, is marked with its corresponding timestamp and in the school geography
Drawing with information such as user identity is foundation, initiates searching request to server accordingly, and server end obtains currently in the school
After reason index corresponding teaching resource result within the corresponding time period, asynchronous for result is returned to client；Client handle is searched
The name of hitch fruit is referred to as the mark of the history (location history) of this dwell point.
In inventive embodiments, by teaching resource information, to infer user's current behavior.In conjunction with user profile (as institute
The course of learn specialty, selecting when admission time and learning cycle start, currently selected course must need technical ability list etc.),
When inferring user behavior using different strategies, thus improving degree of accuracy when inferring behavior again so that automatically generating
Pushed information is more accurate.
With reference to the method that the embodiment of the present invention is provided, several potential application scenarios are illustrated.
A. the generation customizing information pushing and automatic processing prompting based on study plan
When user starts in learning cycle, after having made the study plans such as curriculum schedule upload, server is according in curriculum schedule
Timing node (include operation/report submit node), classroom the Automatic generation of information prompting message such as arranges to upload apple to take
Business device is thus realize automatic synchronization in the distinct device of user.
Server, after the information of certain course arrangement change receiving in curriculum schedule, can push information to user, remind visitor
Family notes, is uploaded to the prompting message of apple server before changing simultaneously.
B. the generation of the information pushing based on when and where and automatic processing prompting
Interact using the eventkit framework reminders built-in with ios system is soft.It is user's system according to user profile
Fixed corresponding reminded contents；Set up inference rule storehouse, its distinguishing rule includes the timestamp information of data point, reverse geographic coding
All kinds of information being obtained with analysis such as information, user's specialized information.
For example, if user passes by library, him can be reminded to borrow in course when this user reaches near library
Required books, data, and recall books numbering in teaching resource database, can use；After borrowing, this borrows information being serviced
Device record is simultaneously automatically generated and gives back prompting and upload to apple server, thus realize in the distinct device of user automatically with
Step.
C. personalized course/available resources Push Service
Can be by analyzing the sensing data of user, thus obtaining behavioural habits and the personal preference of user, such as certain is used
Family have the time after school go library reading custom, can more targetedly be formulated according to these information and push books
The new book in shop, new periodical information.
And for example, certain user likes participating in all kinds of training/public lectures in the time after school, or its curriculum requirements grasps some skills
Can, can more targetedly formulate and push the up-to-date associative skills training session opening up in the school or nearby according to these information
The information of journey/public lecture.
For another example, customer habits are in removing school public computer floor/department's computer room, can according to the custom of user,
Certain time period is to some computer floor/rooms being free position of lead referral, and whether user has making of these computer floor/rooms
Use authority.
Above-described is only embodiments of the invention, and in scheme, the general knowledge here such as known concrete structure and characteristic is not made
Excessive description, before one skilled in the art know the applying date or priority date, technical field that the present invention belongs to is all of
Ordinary technical knowledge, can know all of prior art in this field, and has normal experiment hand before this date of application
The ability of section, one skilled in the art can improve in conjunction with self-ability and implement under the enlightenment that the application is given
This programme, some typical known features or known method should not become one skilled in the art and implement the application
Obstacle.It should be pointed out that for a person skilled in the art, on the premise of without departing from present configuration, can also make
Go out some deformation and improve, these also should be considered as protection scope of the present invention, these effects implemented all without the impact present invention
Fruit and practical applicability.This application claims protection domain should be defined by the content of its claim, the tool in specification
Body embodiment etc. records the content that can be used for explaining claim.
Claims (6)
1. a kind of method for pushing based on data mining is it is characterised in that include: using cloud computing platform by the study meter of user
Draw data and teaching resource data summarization；
Each sensor collection initial data from student's mobile device；
Data prediction is carried out to initial data and obtains data sequence；
Resident point sequence is obtained according to dwell point detection mode；
Cluster analysis is carried out to described resident point sequence, obtains place historical series；
Teaching resource search is carried out to each data in the historical series of place, and place history is marked；
According to the place history after data sequence, mark and study plan data, coupling generates based on time, position and religion
The message learning resource data is pushed to user.
2. the method for pushing based on data mining according to claim 1 it is characterised in that: it is fixed that described initial data includes
Position data.
3. the method for pushing based on data mining according to Claims 2 or 3 it is characterised in that: described location data bag
Include cell tower triangle polyester fibre data, wi-fi node data library inquiry data and gps location data.
4. the method for pushing based on data mining according to claim 4 it is characterised in that: data is carried out to initial data
The step pre-processing and obtaining data sequence includes: carries out coordinate transform to the location data collected；By the coordinate after conversion
Carry out geographical index in the school；By user id, longitude and latitude, timestamp, in the school geographical index result and record id write into Databasce
In.
5. the method for pushing based on data mining according to claim 1 it is characterised in that: described study plan data,
The course selected when learning cycle starts including user, the row that technical ability, books, data must be needed of the currently selected course of student
Table.
6. the method for pushing based on data mining according to claim 1 it is characterised in that: described teaching resource data,
Including course, class hour arrangement, teacher's arrangement, classroom arrangement, course book information, currently available seat, currently available experiment
Room resource.
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| CN201610731521.3A CN106339456A (en) | 2016-08-26 | 2016-08-26 | Push method based on data mining |
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Cited By (8)
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| CN107731034A (en) * | 2017-11-09 | 2018-02-23 | 北京市农林科学院 | A kind of remote education terminal, service end and Distance Education Resources recommend method |
| CN107809488A (en) * | 2017-11-08 | 2018-03-16 | 广东小天才科技有限公司 | The recommendation method and electronic equipment of a kind of education resource |
| CN107967572A (en) * | 2017-12-15 | 2018-04-27 | 华中师范大学 | A kind of intelligent server based on education big data |
| CN108574771A (en) * | 2017-03-10 | 2018-09-25 | 峰范（北京）科技有限公司 | Collecting and processing of information system and its voice playing device, processing method |
| CN108681560A (en) * | 2018-04-17 | 2018-10-19 | 西安交通大学 | A kind of university student's mobile location information analysis method towards Intelligent campus |
| CN110689804A (en) * | 2019-10-10 | 2020-01-14 | 百度在线网络技术（北京）有限公司 | Method and apparatus for outputting information |
| CN112418599A (en) * | 2020-10-15 | 2021-02-26 | 重庆市科学技术研究院 | Enterprise growth path planning method and system based on index set |
| US11468536B2 (en) | 2018-05-18 | 2022-10-11 | Beijing Didi Infinity Technology And Development Co., Ltd. | Systems and methods for recommending a personalized pick-up location |
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN108574771A (en) * | 2017-03-10 | 2018-09-25 | 峰范（北京）科技有限公司 | Collecting and processing of information system and its voice playing device, processing method |
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| CN107731034A (en) * | 2017-11-09 | 2018-02-23 | 北京市农林科学院 | A kind of remote education terminal, service end and Distance Education Resources recommend method |
| CN107967572A (en) * | 2017-12-15 | 2018-04-27 | 华中师范大学 | A kind of intelligent server based on education big data |
| CN108681560A (en) * | 2018-04-17 | 2018-10-19 | 西安交通大学 | A kind of university student's mobile location information analysis method towards Intelligent campus |
| US11468536B2 (en) | 2018-05-18 | 2022-10-11 | Beijing Didi Infinity Technology And Development Co., Ltd. | Systems and methods for recommending a personalized pick-up location |
| CN110689804A (en) * | 2019-10-10 | 2020-01-14 | 百度在线网络技术（北京）有限公司 | Method and apparatus for outputting information |
| CN112418599A (en) * | 2020-10-15 | 2021-02-26 | 重庆市科学技术研究院 | Enterprise growth path planning method and system based on index set |
| CN112418599B (en) * | 2020-10-15 | 2023-02-10 | 重庆市科学技术研究院 | Enterprise growth path planning method and system based on index set |
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Application publication date: 20170118 |