CN107992510A - Wisdom study computational methods based on multi-source heterogeneous data analysis - Google Patents
Wisdom study computational methods based on multi-source heterogeneous data analysis Download PDFInfo
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- CN107992510A CN107992510A CN201710963823.8A CN201710963823A CN107992510A CN 107992510 A CN107992510 A CN 107992510A CN 201710963823 A CN201710963823 A CN 201710963823A CN 107992510 A CN107992510 A CN 107992510A
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- 238000000205 computational method Methods 0.000 title claims abstract description 16
- 238000007405 data analysis Methods 0.000 title claims abstract description 9
- 238000000034 method Methods 0.000 claims abstract description 6
- 238000004364 calculation method Methods 0.000 claims abstract description 5
- 238000000605 extraction Methods 0.000 claims abstract description 4
- 235000013399 edible fruits Nutrition 0.000 claims 1
- 230000010354 integration Effects 0.000 description 5
- 238000005516 engineering process Methods 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013075 data extraction Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 238000000547 structure data Methods 0.000 description 1
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/907—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract
The invention discloses the wisdom based on multi-source heterogeneous data analysis to learn computational methods, includes the following steps：Extraction step：The extracting metadata from each database；Obtaining step：The critical field information and data structure of each metadata are obtained, the data structure includes completing result；The critical field information includes several bytes, each byte includes at least one character；Matching step：According to critical field information, with reference to the metadata of matched rule matching respective data structures；Calculation procedure：The average value with the completion result of critical field information matches is calculated, average value is write in the critical field information.The present invention is extracted and integrated by practicing data to the student of disparate databases, corresponding metadata is matched by crucial wording easy to user, so as to be checked and rated to student's practice conditions.
Description
Technical field
The present invention relates to a kind of wisdom based on multi-source heterogeneous data analysis to learn computational methods.
Background technology
At present, parent increasingly payes attention to the Educate Train to child, in each middle and primary schools and some training organizations, for child
The study of son usually has various learning management systems, be stored with structuring and non-structured various data.Want to student
Study situation when being counted, being calculated, it is necessary to extract data from the corresponding database of each system.
But there are following defect for existing technology：
Since data distribution is in different systems, it is difficult to which same maintenance and management, to follow-up data acquisition, calculates and make
Into difficulty.
The content of the invention
For overcome the deficiencies in the prior art, it is an object of the invention to provide a kind of based on multi-source heterogeneous data analysis
Wisdom learns computational methods, it can integrate the student data of disparate databases, facilitates students ' to learn situation.
Wisdom study computational methods based on multi-source heterogeneous data analysis, it is characterised in that include the following steps：
Extraction step：The extracting metadata from each database；
Obtaining step：The critical field information and data structure of each metadata are obtained, the data structure has included
Into result；The critical field information includes several bytes, each byte includes at least one character；
Matching step：According to critical field information, with reference to the metadata of matched rule matching respective data structures；
Calculation procedure：The average value with the completion result of critical field information matches is calculated, average value is write into the key
In field information.
Further, the key message field includes student name, current grade, deadline.
Further, the data structure further includes source database address, data name, data content, training used time.
Further, in matching step, the matched rule is：Obtain and the deadline corresponding to critical field information
Entire data structure in preset time range, obtains the corresponding metadata of entire data structure.
Further, after obtaining step is performed, receiving step is further included：The account information and matching for receiving user refer to
Order, account information include user name.
Further, in calculation procedure, average value and user name are write in critical field information jointly.
Further, the matching instruction includes keyword input by user, and the keyword includes some characters.
Further, in matching step, the critical field information is obtained according to keyword match input by user.
Further, included the following steps according to keyword match critical field information input by user：Judge any one
It whether there is the byte consistent with keyword in a critical field information, if so, then obtaining the critical field information, otherwise, pick up
Critical field information is taken to fail.
Compared with prior art, the beneficial effects of the present invention are：
The present invention is extracted and integrated by practicing data to the student of disparate databases, passes through keyword easy to user
Eye matches corresponding metadata, so as to be checked and rated to student's practice conditions.
Brief description of the drawings
Fig. 1 is that the wisdom based on multi-source heterogeneous data analysis of the present invention learns the flow chart of computational methods.
Embodiment
In the following, with reference to attached drawing and embodiment, the present invention is described further, it is necessary to which explanation is, not
Under the premise of afoul, new implementation can be formed between various embodiments described below or between each technical characteristic in any combination
Example.
The present invention provides the wisdom learning method based on multi-source heterogeneous data analysis, for different databases, open number
According to bank interface, it is possible to achieve read, write-in.In overall architecture, including different each databases, interface, data are extracted
The Data Integration module and applied analysis module handled after metadata in storehouse metadata.Each database includes knot
Structure data and unstructured data.As shown in Figure 1, specifically comprise the following steps：
S1：The extracting metadata from each database；
The step for by Data Integration module by the database interface of unlatching from database by all demands that meet
Metadata Extraction comes out, and is stored in Data Integration module, subsequently to use.
S2：The critical field information and data structure of each metadata are obtained, the data structure includes completing result；
The critical field information includes several bytes, each byte includes at least one character；
Data Integration module is integrated metadata, needs exist for critical field information and data structure to metadata
Carry out collating sort.Need to illustrate real-time, critical field information is often the metadata some keywords, mark word.This hair
The bright each exercise system applied in school, after student practices exercise in exercise system, including when the set exercise, student's practice
Between, student's answer etc. be all metadata content, and name of student etc. is then used as critical field information.In the present invention, may be used
Student name, current grade, deadline are included with preferential critical field information, the deadline is the time for completing the set exercise
Stamp.Data structure includes completing result, source database address, data name, data content, training used time.Data structure is also
The part of corresponding metadata, by Data Integration module, the information that data structure is included sequentially into
Row combination.And critical field information is extracted from metadata, or the later stage write-in, for for user inquiry when pair
The instrument for corresponding metadata of arranging in pairs or groups according to matching.
For example, there are tri- exercise systems of A, B, C in school, student a is sixth-former, it distinguishes in three exercise systems
Practiced, be of that month practice in A systems and B system, C system is practice last month.The exercise wherein practiced is practised including Chinese language
Topic, maths exercises, English Exercises, it is corresponding specific complete that critical field information then includes a, six grades and each exercise
Into the time." six grades ", " a " included by critical field information are then a byte, and " six grades " this byte then includes
Three characters.And so on.
S3：According to critical field information, with reference to the metadata of matched rule matching respective data structures；
In this step, specific matched rule is：And the deadline corresponding to critical field information is obtained in preset time
In the range of entire data structure, obtain the corresponding metadata of entire data structure.
As preferred embodiment, in S2, the critical field information actually by meta-data extraction, all passes
Key field information forms critical field information aggregate, and data structure forms data structure set, therefore is closed receiving
During key word, it is necessary to by critical field information and date structure matching, to get corresponding metadata.Such as above example, a
Student has the of that month contact completed, and the contact for having complete last month, different exercises is corresponding with the different deadlines, according to this
Deadline, such as to check and rate of that month performance, then the preset time range is arranged to of that month, obtains of that month and critical field
The corresponding metadata of entire data structure that information is consistent, that is, the whole exercises completed in A systems and B system.
S4：The average value with the completion result of critical field information match is calculated, average value is write into the critical field
In information.
Such as a set of Chinese language exercise is completed in A systems, two sets of English Exercises are completed in B system, Chinese language is practised
The completion result of topic and the completion result of two sets of English Exercises are averaged, and complete the fractional value that result is namely completed,
After student completes exercise, system can collect automatically completes result.The average value can reflect student's this month to a certain extent
Study condition, teacher and parent can be helped to be better understood by the study situation of student.By average value write-in critical field letter
It is to facilitate subsequent user to input average value as crucial wording to obtain the number of student of corresponding average value, with right in breath
Student's overall condition is investigated.
The present invention further includes S21 between S2 and S3：Receive the account information and matching instruction of user, account information bag
Include user name.The account information for receiving user is security protection to whole system framework, and only meeting account information could be into
Enter system, be written and read operation.After user's login is entered, matching instruction is actively entered, which includes user and input
Keyword, keyword includes some characters.In S3, critical field information is obtained according to keyword match input by user.
Namely user have input keyword, the critical field information that system is adapted according to the keyword Auto-matching.Concrete operations
It is to judge to whether there is the byte consistent with keyword in any one critical field information, if so, then obtaining the critical field
Information, otherwise, the information failure of pickup critical field.Such as user entered keyword " a ", the key that system searching is consistent with " a "
Field information, may have the entitled a of student in different grades, can eject the critical field information of whole a at this time, and user can be with
Voluntarily choose, and if user entered keyword is a and six grade, directly filter out the corresponding keyword of the student of this grade
Segment information, critical field information and data structure have mapping relations in internal system, and getting after critical field information can be with
So as to get corresponding data structure, whole exercises of a student of six grades are got.In addition the preset time of matched rule
Scope is also user's input, is that one in matching instruction includes item, it is assumed that preset time range is this month, then above-mentioned acquisition
To metadata be exactly six grades a student's this month whole exercises.
Preferably, average value and user name can be write in critical field information jointly.Pass through writing user name
Enter operation, whom can get information about and integrated the information.
The above embodiment is only the preferred embodiment of the present invention, it is impossible to the scope of protection of the invention is limited with this,
The change and replacement for any unsubstantiality that those skilled in the art is done on the basis of the present invention belong to institute of the present invention
Claimed scope.
Claims (9)
1. the wisdom study computational methods based on multi-source heterogeneous data analysis, it is characterised in that include the following steps：
Extraction step：The extracting metadata from each database；
Obtaining step：The critical field information and data structure of each metadata are obtained, the data structure includes completing to tie
Fruit；The critical field information includes several bytes, each byte includes at least one character；
Matching step：According to critical field information, with reference to the metadata of matched rule matching respective data structures；
Calculation procedure：The average value with the completion result of critical field information matches is calculated, average value is write into the critical field
In information.
2. wisdom as claimed in claim 1 learns computational methods, it is characterised in that the key message field includes student's surname
Name, current grade, deadline.
3. wisdom as claimed in claim 2 learns computational methods, it is characterised in that the data structure further includes source database
Address, data name, data content, training used time.
4. wisdom as claimed in claim 2 learns computational methods, it is characterised in that in matching step, the matched rule
For：The entire data structure of and deadline corresponding to critical field information in preset time range is obtained, obtains whole numbers
According to the corresponding metadata of structure.
5. wisdom as claimed in claim 1 learns computational methods, it is characterised in that after obtaining step is performed, further includes
Receiving step：The account information and matching instruction of user is received, account information includes user name.
6. wisdom as claimed in claim 5 learns computational methods, it is characterised in that in calculation procedure, by average value and use
Name in an account book writes in critical field information jointly.
7. wisdom as claimed in claim 5 learns computational methods, it is characterised in that the matching instruction includes input by user
Keyword, the keyword include some characters.
8. wisdom as claimed in claim 7 learns computational methods, it is characterised in that in matching step, the critical field letter
Breath is obtained according to keyword match input by user.
9. wisdom as claimed in claim 8 learns computational methods, it is characterised in that is closed according to keyword match input by user
Key field information includes the following steps：Judge to whether there is the byte consistent with keyword in any one critical field information,
If so, the critical field information is then obtained, and otherwise, the information failure of pickup critical field.
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| CN201710963823.8A CN107992510A (en) | 2017-10-17 | 2017-10-17 | Wisdom study computational methods based on multi-source heterogeneous data analysis |
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103412956A (en) * | 2013-08-30 | 2013-11-27 | 北京中科江南软件有限公司 | Data processing method and system for heterogeneous data sources |
| CN104933095A (en) * | 2015-05-22 | 2015-09-23 | 中国电子科技集团公司第十研究所 | Heterogeneous information universality correlation analysis system and analysis method thereof |
| CN105677710A (en) * | 2015-12-28 | 2016-06-15 | 曙光信息产业(北京)有限公司 | Processing method and system of big data |
| CN106528810A (en) * | 2016-11-18 | 2017-03-22 | 党玉龙 | Method for integrating heterogeneous data to facilitate rapid big data analysis |
| CN107193858A (en) * | 2017-03-28 | 2017-09-22 | 福州金瑞迪软件技术有限公司 | Towards the intelligent Service application platform and method of multi-source heterogeneous data fusion |
-
2017
- 2017-10-17 CN CN201710963823.8A patent/CN107992510A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103412956A (en) * | 2013-08-30 | 2013-11-27 | 北京中科江南软件有限公司 | Data processing method and system for heterogeneous data sources |
| CN104933095A (en) * | 2015-05-22 | 2015-09-23 | 中国电子科技集团公司第十研究所 | Heterogeneous information universality correlation analysis system and analysis method thereof |
| CN105677710A (en) * | 2015-12-28 | 2016-06-15 | 曙光信息产业(北京)有限公司 | Processing method and system of big data |
| CN106528810A (en) * | 2016-11-18 | 2017-03-22 | 党玉龙 | Method for integrating heterogeneous data to facilitate rapid big data analysis |
| CN107193858A (en) * | 2017-03-28 | 2017-09-22 | 福州金瑞迪软件技术有限公司 | Towards the intelligent Service application platform and method of multi-source heterogeneous data fusion |
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