CN108416033A - A kind of data analysing method, device and terminal for automobile research and development - Google Patents
A kind of data analysing method, device and terminal for automobile research and development Download PDFInfo
- Publication number
- CN108416033A CN108416033A CN201810200963.4A CN201810200963A CN108416033A CN 108416033 A CN108416033 A CN 108416033A CN 201810200963 A CN201810200963 A CN 201810200963A CN 108416033 A CN108416033 A CN 108416033A
- Authority
- CN
- China
- Prior art keywords
- data
- sorted
- classification
- development
- automobile
- 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
- 238000000034 method Methods 0.000 title claims abstract description 36
- 238000012827 research and development Methods 0.000 title claims abstract description 34
- 238000007405 data analysis Methods 0.000 claims description 14
- 238000004590 computer program Methods 0.000 claims description 11
- 238000012217 deletion Methods 0.000 claims description 8
- 230000037430 deletion Effects 0.000 claims description 8
- 238000003860 storage Methods 0.000 claims description 8
- 238000000605 extraction Methods 0.000 claims description 4
- 235000013399 edible fruits Nutrition 0.000 claims description 3
- 238000011160 research Methods 0.000 abstract description 14
- 238000012545 processing Methods 0.000 abstract description 11
- 239000000047 product Substances 0.000 description 36
- 238000012857 repacking Methods 0.000 description 16
- 238000005516 engineering process Methods 0.000 description 9
- 238000010586 diagram Methods 0.000 description 8
- 238000011161 development Methods 0.000 description 7
- 230000018109 developmental process Effects 0.000 description 7
- 238000004458 analytical method Methods 0.000 description 6
- 238000013461 design Methods 0.000 description 4
- 230000006872 improvement Effects 0.000 description 4
- 208000037656 Respiratory Sounds Diseases 0.000 description 3
- 230000008859 change Effects 0.000 description 3
- 238000004891 communication Methods 0.000 description 3
- 238000005336 cracking Methods 0.000 description 3
- 238000009472 formulation Methods 0.000 description 3
- 239000000203 mixture Substances 0.000 description 3
- 230000008901 benefit Effects 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000017105 transposition Effects 0.000 description 2
- 206010011376 Crepitations Diseases 0.000 description 1
- 241001269238 Data Species 0.000 description 1
- 244000097202 Rathbunia alamosensis Species 0.000 description 1
- 235000009776 Rathbunia alamosensis Nutrition 0.000 description 1
- 230000001133 acceleration Effects 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 239000006227 byproduct Substances 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000004140 cleaning Methods 0.000 description 1
- 238000005520 cutting process Methods 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 238000007418 data mining Methods 0.000 description 1
- 238000000151 deposition Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 239000002360 explosive Substances 0.000 description 1
- 238000013467 fragmentation Methods 0.000 description 1
- 238000006062 fragmentation reaction Methods 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 230000000717 retained effect Effects 0.000 description 1
- 230000011218 segmentation Effects 0.000 description 1
- 238000012163 sequencing technique Methods 0.000 description 1
- 230000002123 temporal effect Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
- G06F16/3331—Query processing
- G06F16/334—Query execution
- G06F16/3344—Query execution using natural language analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/35—Clustering; Classification
-
- G—PHYSICS
- 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
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/04—Manufacturing
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- Databases & Information Systems (AREA)
- General Engineering & Computer Science (AREA)
- Data Mining & Analysis (AREA)
- General Health & Medical Sciences (AREA)
- Manufacturing & Machinery (AREA)
- Artificial Intelligence (AREA)
- Health & Medical Sciences (AREA)
- Economics (AREA)
- Computational Linguistics (AREA)
- Human Resources & Organizations (AREA)
- Marketing (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention discloses it is a kind of for automobile research and development data analysing method, device and terminal, the method includes：Obtain at least two data to be sorted stored at least one pre-stored data library；According to the Keywords matching rule to prestore, Keywords matching is carried out to data to be sorted described in each, determines the affiliated parts classification of data to be sorted described in each；It determines the corresponding data classification results of each parts classification, and exports.By the data to be analyzed to being got from least one pre-stored data library, Keywords matching is carried out according to the Keywords matching rule to prestore, and then obtains the corresponding data results of each parts classification.Intelligentized realization is classified arrangement to obtaining unordered mixed and disorderly data source in each database, is convenient for the data acquisition of research staff, to instruct designing and developing for automobile, improves product competitiveness；Meanwhile the efficiency and accuracy of data processing are improved, reduce personnel and time cost.
Description
Technical field
The present invention relates to data analysis field more particularly to it is a kind of for automobile research and development data analysing method, device and
Terminal.
Background technology
With the fast development of Internet technology, internet merged with the acceleration of conventional industries, national big data strategy
It proposes, commercial resource of the data as the new era, starts the trend that explosive growth is presented, China is just quickly being pushed to digitize
The development of process.At the same time, automobile industry the energy, traffic, environment, multiple demand pressure under, face industrial transformation
The challenge of upgrading.Impact of the these two aspects factor to orthodox car industry, centered on traditional manufacturer by product will be caused to
Can the business model conversion centered on services client, be bonded consumer demand and go to make the enterprise to face the future and business mould
Formula determines development and the position in industry of 10 years futures enterprise.
Although big data digging technology is rapidly progressed in China, the application in China's automobile industry also compared with
Few, automobile industry mostly carries out the analysis of data in a manual manner at present, the main problems are as follows：
1, lack and obtain complete, correct information means in real time
Orthodox car industry mostly uses artificial mode and browses the mainstreams vapour such as family, easy vehicle net, the Sina for consulting automobile at present
Vehicle website collects surf the net industry dynamic, user demand, user of interconnection and spits the information such as slot, and timeliness is low and is easy to happen omission.
2, data-handling efficiency is low
The processing analysis that data are carried out using manual type, is formed the outputs such as report, spends the time more, and is mostly weight
It returns to work work, labour value is relatively low.
3, enterprise can not extract effective information from mass data in time.
Due to the limitation of the factors such as manpower, time, by artificial mode, enterprise can only be from limited extracting data one
Fixed valuable information the data of magnanimity and can not extract effective information on timely processing internet.
It 4, can not fast responding market variation
The individual demand of client is increasing at present, the canal of R ＆ D design personnel's neither one user in real demand
Road；Existing market variation is rapid, and leadership lacks the foundation for carrying out science decision, to respond the variation in market；Designer is difficult
Carry out design to obtain industry state-of-the-art technology and related data.
Invention content
The present invention provides a kind of data analysing method, device and terminals for automobile research and development, to solve the prior art
In can not to internet data carry out Research ＆ Development of Automobile analysis the problem of.
In order to solve the above technical problems, an embodiment of the present invention provides a kind of data analysing method for automobile research and development,
Including：
Obtain at least two data to be sorted stored at least one pre-stored data library；
According to the Keywords matching rule to prestore, Keywords matching is carried out to data to be sorted described in each, is determined every
One affiliated parts classification of data to be sorted；
It determines the corresponding data classification results of each parts classification, and exports.
Preferably, in each Keywords matching rule, including：First attribute keywords and the second attribute keywords,
Position relationship and first attribute keywords between first attribute keywords and second attribute keywords and
Gap character between second attribute keywords；
Wherein, first attribute keywords are the parts of automobile, and second attribute keywords are to indicate described zero
The Second Type vocabulary of the poor performance of the good first kind vocabulary of the performance of component and/or the expression parts.
Preferably, the step of obtaining at least two data to be sorted stored at least one pre-stored data library include：
At least one primary data is extracted from least one pre-stored data library；
It carries out invalid data deletion successively to the primary data and redundant data is deleted, obtain at least two numbers to be sorted
According to.
Preferably, carrying out the step of invalid data deletion and redundant data are deleted successively to the primary data includes：
It is that empty invalid data is deleted to the body matter in the primary data；
The redundant data repeated to the uniform resource position mark URL in the primary data is deleted.
Preferably, according to the Keywords matching rule to prestore, Keywords matching is carried out to data to be sorted described in each,
Before the step of determining the affiliated parts classification of data to be sorted described in each, the method further includes：
It is according to the corresponding industry attributive classification in each pre-stored data library to prestore, each pre-stored data library is corresponding wherein
A part of data to be sorted carry out industry attributive classification respectively；
It determines the corresponding data to be sorted of each industry attributive classification, and preserves.
Preferably, the method further includes：
Obtain target keyword input by user；
Determine target data corresponding with the target keyword as a result, being exported to the target data result；
Wherein, the target data result includes：Target classification data corresponding with the target keyword and/or with
The corresponding Resolving probiems information of the target classification data.
According to another aspect of the present invention, the embodiment of the present invention additionally provides a kind of data analysis dress for automobile research and development
It sets, including：
First acquisition module, for obtaining at least two data to be sorted stored at least one pre-stored data library；
First determining module, for according to the Keywords matching rule to prestore, being carried out to data to be sorted described in each
Keywords matching determines the affiliated parts classification of data to be sorted described in each；
Second determining module for determining the corresponding data classification results of each parts classification, and exports.
Preferably, in each Keywords matching rule, including：First attribute keywords and the second attribute keywords,
Position relationship and first attribute keywords between first attribute keywords and second attribute keywords and
Gap character between second attribute keywords；
Wherein, first attribute keywords are the parts of automobile, and second attribute keywords are to indicate described zero
The Second Type vocabulary of the poor performance of the good first kind vocabulary of the performance of component and/or the expression parts.
Preferably, the first acquisition module includes：
Extraction unit, for extracting at least one primary data from least one pre-stored data library；
Deleting unit is deleted for carrying out invalid data deletion and redundant data successively to the primary data, is obtained extremely
Few two data to be sorted.
Preferably, deleting unit includes：
First deletes subelement, for being that empty invalid data is deleted to the body matter in the primary data；
Second deletes subelement, the redundant data for being repeated to the uniform resource position mark URL in the primary data
It is deleted.
Preferably, described device further includes：
Sort module, for according to the corresponding industry attributive classification in each pre-stored data library to prestore, by each number that prestores
Industry attributive classification is carried out respectively according to library corresponding a portion data to be sorted；
Third determining module for determining the corresponding data to be sorted of each industry attributive classification, and preserves.
Preferably, described device further includes：
Second acquisition module, for obtaining target keyword input by user；
4th determining module, for determining target data corresponding with the target keyword as a result, to the number of targets
It is exported according to result；
Wherein, the target data result includes：Target classification data corresponding with the target keyword and/or with
The corresponding Resolving probiems information of the target classification data.
On the other hand, the embodiment of the present invention additionally provides a kind of terminal, including processor, memory and is stored in described deposit
On reservoir and the computer program that can run on the processor, the computer program are realized when being executed by the processor
Such as the step of the above-mentioned data analysing method for automobile research and development.
On the other hand, the embodiment of the present invention additionally provides a kind of computer readable storage medium, described computer-readable to deposit
It is stored with computer program on storage media, realizes when the computer program is executed by processor and is researched and developed for automobile as above-mentioned
Data analysing method the step of.
In this way, in the embodiment of the present invention, by the data to be analyzed to being got from least one pre-stored data library,
Keywords matching is carried out according to the Keywords matching rule to prestore, and then obtains the corresponding data analysis knot of each parts classification
Fruit.Intelligentized realization is classified arrangement to obtaining unordered mixed and disorderly data source in each database, is convenient for research staff
Data acquisition improve product competitiveness to instruct designing and developing for automobile；Meanwhile improving the efficiency and standard of data processing
True property, reduces personnel and time cost.
Description of the drawings
In order to illustrate the technical solution of the embodiments of the present invention more clearly, below by institute in the description to the embodiment of the present invention
Attached drawing to be used is needed to be briefly described, it should be apparent that, the accompanying drawings in the following description is only some implementations of the present invention
Example, for those of ordinary skill in the art, without having to pay creative labor, can also be according to these attached drawings
Obtain other attached drawings.
Fig. 1 shows one of the flow charts of data analysing method for automobile research and development of the embodiment of the present invention；
Fig. 2 indicates the flow chart of the step 101 of the embodiment of the present invention；
Fig. 3 indicates the flow chart of the step 1012 of the embodiment of the present invention；
Fig. 4 indicates the two of the flow chart of the data analysing method for automobile research and development of the embodiment of the present invention；
Fig. 5 indicates the three of the flow chart of the data analysing method for automobile research and development of the embodiment of the present invention；
Fig. 6 indicates the structural schematic diagram of the automobile product structure of design of the embodiment of the present invention；
Fig. 7 is indicated in the embodiment of the present invention through bar chart output form to the data in the brake structure of automobile chassis point
The schematic diagram that class result is exported；
Fig. 8 shows the schematic diagrames that the product of Liang Jia different companies is compared in the embodiment of the present invention；
Fig. 9 is the data that a certain refitted car got from internet in the embodiment of the present invention ties up in special time period
Schematic diagram；
Figure 10 is that a certain refitted car that is got from internet ties up in special time period and makes in the embodiment of the present invention
With the schematic diagram of the data of repacking element；
Figure 11 indicates the structural schematic diagram of the data analysis set-up for automobile research and development of the embodiment of the present invention.
Specific implementation mode
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation describes, it is clear that described embodiments are some of the embodiments of the present invention, instead of all the embodiments.Based on this hair
Embodiment in bright, the every other implementation that those of ordinary skill in the art are obtained without creative efforts
Example, shall fall within the protection scope of the present invention.
Referring to Fig.1, an embodiment of the present invention provides a kind of data analysing method for automobile research and development, it is applied to terminal,
Including：
Step 101, at least two data to be sorted stored at least one pre-stored data library are obtained.
Wherein, in the step 101, at least one pre-stored data library refer in advance with the end in the embodiment of the present invention
The database of communication connection is established between end.Communication protocol is established between terminal and at least one pre-stored data library, it is pre- one
Section of fixing time carries out data acquisition (specific time in such as each week obtains primary).These pre-stored data libraries refer to that industry attribute is
The database of the related web site of automobile industry, such as：People's Net, China Association for Automobile Manufacturers, national Automotive Standardization technology committee
The automobile industries dynamic class websites such as member's meeting, automobile sales volume net, the mainstream automotives such as love card automobile, the family of automobile, easy vehicle net, vehicle matter net
Website, the repacking class websites such as cross-country E races, unmatched repacking net.
Wherein, with reference to Fig. 2, step 101 specifically includes：
Step 1011, at least one primary data is extracted from least one pre-stored data library.
At least two data to be sorted can be the total data in each pre-stored data library.Can also be to be inputted with user
The relevant data of the first keyword, which can be a certain particular component on automobile, can also be automobile
The a certain vehicle system of company needs to be B2's to the vehicle system of rival B companies for example, to carry out the research and development of products of a certain vehicle system A
Product carries out data collection, at this point, end side carries the B2 for obtaining B companies by being sent at least one pre-stored data library
The request of data of the total data of vehicle system, at least one pre-stored data library is after the request of data for receiving terminal transmission, extraction
The total data for going out the B2 vehicles system of the B companies is sent to terminal, and terminal is in the data for receiving at least one pre-stored data library transmission
Afterwards, be formed as at least one primary data in above-mentioned steps 1011.
In embodiments of the present invention, which further includes：
Step 1012, it carries out invalid data deletion successively to the primary data and redundant data is deleted, obtain at least two
Item data to be sorted.
Since at least one pre-stored data library is in the data sent to the terminal, it is understood that there may be content repeat data or
Person's invalid data, in order to improve the validity of data, in embodiments of the present invention, with reference to Fig. 3, which specifically includes：
Step 10121, it is that empty invalid data is deleted to the body matter in the primary data；
Step 10122, the redundant data repeated to the uniform resource position mark URL in the primary data is deleted.
Wherein, in step 10121, if primary data only includes the fields such as theme, author, time, but body matter
For sky, then it is assumed that the primary data is invalid data.
In step 10122, the judgement to redundant data is compared by uniform resource position mark URL, if depositing
Uniform resource position mark URL at least two primary datas is identical, then it is assumed that there are redundant data, will at least two it is initial
A data in data is retained, and remaining identical data is deleted.
By invalid data and redundant data delete processing, it can ensure having for the data being stored in the database of terminal
Effect property.
Step 102, according to the Keywords matching rule to prestore, keyword is carried out to data to be sorted described in each
Match, determines the affiliated parts classification of data to be sorted described in each.
Preferably, in embodiments of the present invention, in each Keywords matching rule, including：First attribute keywords
With the second attribute keywords, the position relationship between first attribute keywords and second attribute keywords, Yi Jisuo
State the gap character between the first attribute keywords and second attribute keywords；
Wherein, first attribute keywords are the parts of automobile, and second attribute keywords are to indicate described zero
The Second Type vocabulary of the poor performance of the good first kind vocabulary of the performance of component and/or the expression parts.
In the embodiment of the present invention, first according to the R＆D mode of automobile, set chassis, power, electronic apparatus, vehicle body,
This whole six big ontology of interior exterior trim, product, primary structure is divided by above-mentioned 6 part, and refines extension two-stage (to primary structure
It is divided into secondary structure into a traveling part, tertiary structure is further divided into secondary structure), establish automobile product knot
Structure ultimately forms the automobile product structure shown in fig. 6 just like under.
Wherein, in above-mentioned Keywords matching rule, the first attribute keywords are the product in above-mentioned tertiary structure
Component, first attribute keywords can be in the primary structure of automobile product structure, secondary structure and tertiary structure at least
One.
In above-mentioned Keywords matching rule, the gap character between the first attribute keywords and the second attribute keywords can
Think the interval word (being indicated near) between the first attribute keywords and the second attribute keywords, or crucial for the first attribute
Interval paragraph (being indicated with prg) between word and the second attribute keywords, or closed for the first attribute keywords and the second attribute
Interval sentence (being indicated with aft) between keyword.
According to various forms of combinations of the first attribute keywords and the second attribute keywords, different component structurals are formed
Corresponding multiple Keywords matching rules.Such as：' A/NEAR X B', indicate that the first attribute keywords A is located at the second attribute pass
Before keyword B, and the interval word between the first attribute keywords A and the second attribute keywords B is 10 words.For example, a certain
Keywords matching rule is：' side bar/NEAR 10 deformation '+' side bar/NEAR 10 broken '+' side bar/NEAR 10 damaged '+' side
10 crackles of beam/NEAR '+' side bar/NEAR 10 split '+' crackings of side bar/NEAR 10 ', in the keyword rule, side bar is
First attribute keywords (side bar is tertiary structure), " broken, deformation, breakage, crackle, cracking " is the second attribute keywords,
It is the Second Type vocabulary for the poor performance for indicating first attribute keywords (side bar)；And first attribute keywords (side bar)
Before the second attribute keywords (broken, deformation, breakage, crackle, cracking), " near 10 " refers to first attribute keywords
Interval word between the second attribute keywords is 10 words.
In embodiments of the present invention, by carrying out test of many times in advance, in conjunction with different problems, formed it is a set of it is perfect,
Keywords matching rule based on automobile product structure.It, can be to the sea that is stored in terminal by set Keywords matching rule
It measures data to be sorted and carries out automatic word segmentation processing, make fragmentation of data to be sorted, the structuring of magnanimity, formation can be with structuring
Data.
Step 103, the corresponding data classification results of each parts classification are determined, and are exported.
After by being matched to each Keywords matching rule, the corresponding data classification of each parts classification is determined
As a result, and save it in database, convenient for research staff use.
Wherein, in step 103, for the data classification results determined, different output forms may be used and carry out
Output.Output form is specially：It is exported by forms such as bubble diagram, bar chart, pie chart or line charts, meanwhile, pass through percentage
Or the mode of actual quantity is shown.In 7, the data classification results are exported by the form of bubble diagram, are used
Family can be determined according to the size of bubble in a certain particular series vehicle, by the highest specific product portion of consumer's attention rate
Part.Such as in Fig. 7, to the data classification results in the brake structure of the automobile chassis stored in terminal by way of bar chart
It is shown.
The step of being exported for data classification results be specially：
Obtain the output form selected by user；
According to the output form, data classification results are exported.
It meanwhile in embodiments of the present invention, can also be according to time dimension, region for the output of the data classification results
The dimensions such as dimension, data source export data classification results.For example, according to time dimension to data classification results into
Row output concrete mode be：It is exported according to the time for getting the data to be sorted from least one pre-stored data library.
By collected temporal information, the line chart of problematic amount and time is obtained, can know the measure of being correspondingly improved by trend
Whether effectively；By collecting regional information, the relational graph between problem and region is obtained, for instructing have regional characteristic problem
Processing and spare part scheme formulation.Research staff can compare according to the data classification results in different time sections and analyze, right
The same parts of different series product compare and analyze (as shown in figure 8, left side be our company's product, right side is rival firms
Product), determine that our company's product short slab and other series of products can use for reference the relevant information of reference.Competing product are being referred to, are being improved
While itself disadvantage, the advantage of itself product is played, to promote product competitiveness.
In embodiments of the present invention, it shall be highlighted that the user of terminal is more focused on automobile research staff in the present invention,
Research staff by terminal carry out data classification obtain as a result, it is possible to it is timely understand automobile industry industry development and disappear
The person of expense carries out products perfection to the in-service evaluation of automobile product, and then for data result, improves product competitiveness.
In the above embodiment of the present invention, by the data to be analyzed to being got from least one pre-stored data library, press
Keywords matching is carried out according to the Keywords matching rule to prestore, and then obtains the corresponding data analysis knot of each parts classification
Fruit.Intelligentized realization is classified arrangement to obtaining unordered mixed and disorderly data source in each database, is convenient for research staff
Data acquisition improve product competitiveness to instruct designing and developing for automobile；Meanwhile improving the efficiency and standard of data processing
True property, reduces personnel and time cost.
Preferably, with reference to Fig. 4, in embodiments of the present invention, before the step 102, the method further includes：
Step 104, according to the corresponding industry attributive classification in each pre-stored data library to prestore, by each pre-stored data library pair
A portion data to be sorted answered carry out industry attributive classification respectively；
Step 105 determines the corresponding data to be sorted of each industry attributive classification, and preserves.
Wherein, at step 104, industry attributive classification includes：Trade trend class (including Industry Policy, industry are sold, most
New technology, four group of trade trend), problem find class, customization repacking class, the corresponding industry attributive classification in each pre-stored data library
It is to be determined using attribute according to the database, such as People's Net, China Association for Automobile Manufacturers, national Automotive Standardization skill
The main business of the websites such as the art committee, automobile sales volume net is shown to the associated dynamic of automobile industry, i.e., by the sector
Attribute transposition is trade trend class, and is to be related to zero for the main business of the repacking class websites such as cross-country E races, unmatched repacking net
Part is reequiped, i.e., is customization repacking class by the industry Attribute transposition of such website.
Automobile research staff can be preliminary by being carried out according to the data to be sorted that industry attributive classification preserves in step 105
Inquiry (can be checked according to the sequencing of the information issuing time of data source with acquisition, and support the download of data, receive
Hide, original text is checked), determine the focus of consumer and the height of degree of concern in a certain special time period.And it can tie
The degree height for closing the attention rate carries out trend prediction, is optimized to product, to improve product competitiveness.
Wherein, in embodiments of the present invention, the second attribute keywords in a certain target keyword matching rule are to be somebody's turn to do
When the Second Type vocabulary of the poor performance of parts, the method for the embodiment of the present invention further includes：
The poor performance for solving the problems, such as the parts is searched from the first database for pre-establishing communication connection with terminal
Information is solved, and the target keyword matching rule and the Resolving probiems information are stored.
Wherein, which is periodical literature site databases, patent website database.
Preferably, with reference to Fig. 5, in embodiments of the present invention, the method further includes：
Step 106, target keyword input by user is obtained；
Step 107, target data corresponding with the target keyword is determined as a result, being carried out to the target data result
Output；
Wherein, the target data result includes：Target classification data corresponding with the target keyword and/or with
The corresponding Resolving probiems information of the target classification data.
Wherein, in step 106, user is automobile research staff, and automobile research staff, may before carrying out research and development of products
It needs to carry out investigation and research of products, at this point, user inputs target keyword in terminal, (target keyword can be word input
, can also be according to the product structure of aforementioned division choose successively being formed), terminal is according to the target keyword from number
According to searching corresponding target data result in library.The technical literature that is matched according to target keyword, cutting edge technology, standard law
Rule, similar problems treating method etc. are referred to and are used for engineer, are ranked up by matching attention rate, and push most accurately solves
Scheme.For example, target keyword input by user is：Side bar deforms, then terminal is searched and the target from the data source of storage
Keywords matching and the grouped data Jing Guo Fen Lei and Resolving probiems information corresponding with each grouped data, and press
Arrangement displaying output is carried out according to the sequence of matching degree, pushes most accurate solution.
The above-mentioned data analysing method for automobile research and development of the present invention, can apply in refitted car system, according to refitted car
The title of system, time obtain the repacking trend of certain vehicle system, know repacking temperature；And can according to repacking original paper title and brand,
The temperature of repacking original paper and affiliated brand, formulation and implementation for instructing customization refiting scheme are further obtained, or even can be made
To change the foundation of money and improvement direction.If Fig. 9 is to apply to reequip trend analysis figure in certain xx vehicles system in the embodiment of the present invention, from this
It can be determined in figure and apply be related to the repacking trend of the xx vehicles system on internet to August the June in 2017.Figure 10 is should
Xx vehicles tie up in June, 2017 to the specific repacking element during August, being designed into.
The above method of the embodiment of the present invention, can realize it is comprehensive to internet data, timely, effectively acquisition and structure
Change storage, and can be according to demand variation, configure data source, content and the period of acquisition of acquisition etc., ensure that data obtain
What is taken is efficient, comprehensive；Realize that quickly processing is extracted to the valuable information of user, and in a manner of patterned from mass data
Displaying, improves the efficiency and accuracy of data processing, reduces personnel and time cost.
According to the demand of automobile R ＆ D Enterprises, product tertiary structure is constructed, and summarize and be contemplated that for different components
600 remainder of quality problems, establish solution matching rule, realize problem automatic statistic of classification and further inquiry
Retrieval helps research staff to discover problems and solve them, and improves product.
The information such as real time push and Statistics latest tendency, industry state-of-the-art technology, sales data and technological development direction,
It instructs user to understand in time and understands newest country, code of conduct and development trend of the place about automobile industry, for design
Personnel, developer obtain newest industry technology and dynamic, instruct designing and developing for automobile.
Interworking GateWay is extracted in the repacking information of offroad vehicle, the individual demand of user's repacking is obtained, includes the heat of repacking
Door vehicle system, original paper, brand etc., the formulation and implementation of guidance customization refiting scheme, or even can be used as change money and improvement direction according to
According to.
It realizes itself vehicle to compare with the problem of competition vehicle, finds the strengths and weaknesses of itself and competing product, referring to competing product,
While improving itself disadvantage, the advantage of itself product is played, to promote product competitiveness.
By collecting, analysing in depth extensively and the data resource in integrated multi-party face, has accumulated user behavior and hobby is inclined to
Data, the public sentiment data of data mining cleaning analysis, automobile industry specialized dictionary have gradually formed the number suitable for automobile industry
According to analysis library.In the epoch with data for king, platform accumulates the Data analysis library to be formed, and will become enterprise's great riches application
In the relevant every field of research and development.
According to another aspect of the present invention, the embodiment of the present invention additionally provides a kind of data analysis dress for automobile research and development
It sets, referring to Fig.1 1, including：
First acquisition module 201, for obtaining at least two data to be sorted stored at least one pre-stored data library；
First determining module 202, for according to prestore Keywords matching rule, to data to be sorted described in each into
Row Keywords matching determines the affiliated parts classification of data to be sorted described in each；
Second determining module 203 for determining the corresponding data classification results of each parts classification, and exports.
Preferably, in each Keywords matching rule, including：First attribute keywords and the second attribute keywords,
Position relationship and first attribute keywords between first attribute keywords and second attribute keywords and
Gap character between second attribute keywords；
Wherein, first attribute keywords are the parts of automobile, and second attribute keywords are to indicate described zero
The Second Type vocabulary of the poor performance of the good first kind vocabulary of the performance of component and/or the expression parts.
Preferably, the first acquisition module includes：
Extraction unit, for extracting at least one primary data from least one pre-stored data library；
Deleting unit is deleted for carrying out invalid data deletion and redundant data successively to the primary data, is obtained extremely
Few two data to be sorted.
Preferably, deleting unit includes：
First deletes subelement, for being that empty invalid data is deleted to the body matter in the primary data；
Second deletes subelement, the redundant data for being repeated to the uniform resource position mark URL in the primary data
It is deleted.
Preferably, described device further includes：
Sort module, for according to the corresponding industry attributive classification in each pre-stored data library to prestore, by each number that prestores
Industry attributive classification is carried out respectively according to library corresponding a portion data to be sorted；
Third determining module for determining the corresponding data to be sorted of each industry attributive classification, and preserves.
Preferably, described device further includes：
Second acquisition module, for obtaining target keyword input by user；
4th determining module, for determining target data corresponding with the target keyword as a result, to the number of targets
It is exported according to result；
Wherein, the target data result includes：Target classification data corresponding with the target keyword and/or with
The corresponding Resolving probiems information of the target classification data.
Data analysis set-up provided in an embodiment of the present invention for automobile research and development can realize that the method for Fig. 1 to Fig. 5 is real
Each process that mobile terminal is realized in example is applied, to avoid repeating, which is not described herein again.By to from least one pre-stored data
The data to be analyzed got in library carry out Keywords matching according to the Keywords matching rule to prestore, and then obtain every 1
The corresponding data results of part classification.Intelligentized realize carries out to obtaining unordered mixed and disorderly data source in each database
Taxonomic revision is convenient for the data acquisition of research staff, to instruct the designing and developing of automobile, improves product competitiveness；Meanwhile it carrying
The high efficiency and accuracy of data processing, reduces personnel and time cost.
On the other hand, the embodiment of the present invention additionally provides a kind of terminal, including processor, memory and is stored in described deposit
On reservoir and the computer program that can run on the processor, the computer program are realized when being executed by the processor
Such as the step of the above-mentioned data analysing method for automobile research and development.
On the other hand, the embodiment of the present invention additionally provides a kind of computer readable storage medium, described computer-readable to deposit
It is stored with computer program on storage media, realizes when the computer program is executed by processor and is researched and developed for automobile as above-mentioned
Data analysing method the step of.
Above-described is the preferred embodiment of the present invention, it should be pointed out that the ordinary person of the art is come
It says, can also make several improvements and retouch under the premise of not departing from principle of the present invention, these improvements and modifications also exist
In protection scope of the present invention.
Claims (14)
1. a kind of data analysing method for automobile research and development, which is characterized in that including：
Obtain at least two data to be sorted stored at least one pre-stored data library；
According to the Keywords matching rule to prestore, Keywords matching is carried out to data to be sorted described in each, determines each
The affiliated parts classification of data to be sorted；
It determines the corresponding data classification results of each parts classification, and exports.
2. the data analysing method according to claim 1 for automobile research and development, which is characterized in that each keyword
In matching rule, including：First attribute keywords and the second attribute keywords, first attribute keywords and described second belong to
The interval word between position relationship and first attribute keywords and second attribute keywords between property keyword
Symbol；
Wherein, first attribute keywords are the parts of automobile, and second attribute keywords are to indicate the parts
The good first kind vocabulary of performance and/or indicate the parts poor performance Second Type vocabulary.
3. the data analysing method according to claim 1 for automobile research and development, which is characterized in that obtain at least one pre-
The step of at least two data to be sorted stored in deposit data library includes：
At least one primary data is extracted from least one pre-stored data library；
It carries out invalid data deletion successively to the primary data and redundant data is deleted, obtain at least two data to be sorted.
4. the data analysing method according to claim 3 for automobile research and development, which is characterized in that the primary data
Carrying out the step of invalid data deletion is deleted with redundant data successively includes：
It is that empty invalid data is deleted to the body matter in the primary data；
The redundant data repeated to the uniform resource position mark URL in the primary data is deleted.
5. the data analysing method according to claim 1 for automobile research and development, which is characterized in that according to the key to prestore
Word matching rule carries out Keywords matching to data to be sorted described in each, determines belonging to data to be sorted described in each
Before the step of parts are classified, the method further includes：
It is according to the corresponding industry attributive classification in each pre-stored data library to prestore, each pre-stored data library is wherein one corresponding
Data to be sorted are divided to carry out industry attributive classification respectively；
It determines the corresponding data to be sorted of each industry attributive classification, and preserves.
6. the data analysing method according to claim 1 for automobile research and development, which is characterized in that the method is also wrapped
It includes：
Obtain target keyword input by user；
Determine target data corresponding with the target keyword as a result, being exported to the target data result；
Wherein, the target data result includes：Target classification data corresponding with the target keyword and/or with it is described
The corresponding Resolving probiems information of target classification data.
7. a kind of data analysis set-up for automobile research and development, which is characterized in that including：
First acquisition module, for obtaining at least two data to be sorted stored at least one pre-stored data library；
First determining module, for according to the Keywords matching rule to prestore, being carried out to data to be sorted described in each crucial
Word matches, and determines the affiliated parts classification of data to be sorted described in each；
Second determining module for determining the corresponding data classification results of each parts classification, and exports.
8. the data analysis set-up according to claim 7 for automobile research and development, which is characterized in that each keyword
In matching rule, including：First attribute keywords and the second attribute keywords, first attribute keywords and described second belong to
The interval word between position relationship and first attribute keywords and second attribute keywords between property keyword
Symbol；
Wherein, first attribute keywords are the parts of automobile, and second attribute keywords are to indicate the parts
The good first kind vocabulary of performance and/or indicate the parts poor performance Second Type vocabulary.
9. the data analysis set-up according to claim 7 for automobile research and development, which is characterized in that the first acquisition module packet
It includes：
Extraction unit, for extracting at least one primary data from least one pre-stored data library；
Deleting unit deletes for carrying out invalid data deletion and redundant data successively to the primary data, obtains at least two
Item data to be sorted.
10. the data analysis set-up according to claim 9 for automobile research and development, which is characterized in that deleting unit includes：
First deletes subelement, for being that empty invalid data is deleted to the body matter in the primary data；
Second deletes subelement, and the redundant data for being repeated to the uniform resource position mark URL in the primary data carries out
It deletes.
11. the data analysis set-up according to claim 7 for automobile research and development, which is characterized in that described device is also wrapped
It includes：
Sort module, for according to the corresponding industry attributive classification in each pre-stored data library to prestore, by each pre-stored data library
Corresponding a portion data to be sorted carry out industry attributive classification respectively；
Third determining module for determining the corresponding data to be sorted of each industry attributive classification, and preserves.
12. the data analysis set-up according to claim 7 for automobile research and development, which is characterized in that described device is also wrapped
It includes：
Second acquisition module, for obtaining target keyword input by user；
4th determining module, for determining target data corresponding with the target keyword as a result, to the target data knot
Fruit is exported；
Wherein, the target data result includes：Target classification data corresponding with the target keyword and/or with it is described
The corresponding Resolving probiems information of target classification data.
13. a kind of terminal, which is characterized in that including processor, memory and be stored on the memory and can be at the place
The computer program run on reason device is realized when the computer program is executed by the processor as appointed in claim 1 to 6
Described in one for automobile research and development data analysing method the step of.
14. a kind of computer readable storage medium, which is characterized in that be stored with computer on the computer readable storage medium
Program is realized when the computer program is executed by processor and is researched and developed for automobile as according to any one of claims 1 to 6
Data analysing method the step of.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810200963.4A CN108416033A (en) | 2018-03-12 | 2018-03-12 | A kind of data analysing method, device and terminal for automobile research and development |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810200963.4A CN108416033A (en) | 2018-03-12 | 2018-03-12 | A kind of data analysing method, device and terminal for automobile research and development |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108416033A true CN108416033A (en) | 2018-08-17 |
Family
ID=63130947
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810200963.4A Pending CN108416033A (en) | 2018-03-12 | 2018-03-12 | A kind of data analysing method, device and terminal for automobile research and development |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108416033A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112328591A (en) * | 2019-08-05 | 2021-02-05 | 安徽智数汽车科技有限公司 | Big data application system operation method based on automobile research and development and storage medium |
| CN112712501A (en) * | 2020-12-28 | 2021-04-27 | 江苏合泰飞梵科技有限公司 | Rearview mirror assembly production method based on artificial intelligence |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2010022378A1 (en) * | 2008-08-21 | 2010-02-25 | Satya Reddy | Interrelated item search |
| CN103902652A (en) * | 2014-02-27 | 2014-07-02 | 深圳市智搜信息技术有限公司 | Automatic question-answering system |
| CN105404644A (en) * | 2015-10-27 | 2016-03-16 | 北京红马传媒文化发展有限公司 | Public opinion information processing method and system |
| CN107577724A (en) * | 2017-08-22 | 2018-01-12 | 佛山市高研信息技术有限公司 | A kind of big data processing method |
| CN108320255A (en) * | 2017-01-16 | 2018-07-24 | 软通动力信息技术（集团）有限公司 | A kind of information processing method and device |
-
2018
- 2018-03-12 CN CN201810200963.4A patent/CN108416033A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2010022378A1 (en) * | 2008-08-21 | 2010-02-25 | Satya Reddy | Interrelated item search |
| CN103902652A (en) * | 2014-02-27 | 2014-07-02 | 深圳市智搜信息技术有限公司 | Automatic question-answering system |
| CN105404644A (en) * | 2015-10-27 | 2016-03-16 | 北京红马传媒文化发展有限公司 | Public opinion information processing method and system |
| CN108320255A (en) * | 2017-01-16 | 2018-07-24 | 软通动力信息技术（集团）有限公司 | A kind of information processing method and device |
| CN107577724A (en) * | 2017-08-22 | 2018-01-12 | 佛山市高研信息技术有限公司 | A kind of big data processing method |
Non-Patent Citations (2)
| Title |
|---|
| 崔立真 等: "《大数据驱动创新方法工作平台》", 31 October 2017 * |
| 郭永菊: "《电子器件领域专利检索策略及应用》", 30 June 2015 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112328591A (en) * | 2019-08-05 | 2021-02-05 | 安徽智数汽车科技有限公司 | Big data application system operation method based on automobile research and development and storage medium |
| CN112712501A (en) * | 2020-12-28 | 2021-04-27 | 江苏合泰飞梵科技有限公司 | Rearview mirror assembly production method based on artificial intelligence |
| CN112712501B (en) * | 2020-12-28 | 2021-10-26 | 江苏合泰飞梵科技有限公司 | Rearview mirror assembly production method based on artificial intelligence |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103176983B (en) | A kind of event method for early warning based on internet information | |
| CN101246499B (en) | Network information search method and system | |
| CN101477554A (en) | User interest based personalized meta search engine and search result processing method | |
| CN101609459A (en) | A kind of extraction system of affective characteristic words | |
| CN103810168A (en) | Search application method, device and terminal | |
| CN111831802A (en) | Urban domain knowledge detection system and method based on LDA topic model | |
| CN103294781A (en) | Method and equipment used for processing page data | |
| CN109101551B (en) | Question-answer knowledge base construction method and device | |
| CN101082936A (en) | Data enquiring system and method | |
| CN110532265B (en) | Method and device for constructing question-answering system based on product instruction manual and computing equipment | |
| CN103116635A (en) | Field-oriented method and system for collecting invisible web resources | |
| CN107463711A (en) | A kind of tag match method and device of data | |
| CN101630315B (en) | Quick retrieval method and system | |
| CN103544307A (en) | Multi-search-engine automatic comparison and evaluation method independent of document library | |
| CN108416033A (en) | A kind of data analysing method, device and terminal for automobile research and development | |
| CN101807183A (en) | Real-time extension method and system of key vocabularies and computer erasable recording medium thereof | |
| CN103020083A (en) | Automatic mining method of requirement identification template, requirement identification method and corresponding device | |
| CN110413307A (en) | Correlating method, device and the electronic equipment of code function | |
| CN103823847A (en) | Keyword extension method and device | |
| CN103729374A (en) | Information search method and search engine | |
| TW201415275A (en) | Forensic system, forensic method, and forensic program | |
| CN103970732B (en) | Mining method and device of new word translation | |
| CN103150307B (en) | The method and apparatus of the title relevant to descriptor is searched from network | |
| Cortez et al. | A flexible approach for extracting metadata from bibliographic citations | |
| CN110209804B (en) | Target corpus determining method and device, storage medium and electronic device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20200508 Address after: 100130 Zhaofeng Town, Shunyi District, Beijing Zhaofeng industrial base Tongxin Road No. 1 Applicant after: BAIC GROUP ORV Co.,Ltd. Address before: 101300, 99, Shuanghe Avenue, Renhe Town, Beijing, Shunyi District Applicant before: BEIJING AUTOMOBILE RESEARCH GENERAL INSTITUTE Co.,Ltd. |
|
| TA01 | Transfer of patent application right | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20180817 |
|
| RJ01 | Rejection of invention patent application after publication |