CN108804655A - A kind of intangible asset method and system based on big data - Google Patents
A kind of intangible asset method and system based on big data Download PDFInfo
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Abstract
The intangible asset method and system based on big data that the invention discloses a kind of, include assets assessment process optimization, the assets assessment modelling based on big data and the intangible asset system based on the big data design supervised based on big data, the assets assessment process optimization based on big data supervision include single assessment side visual angle under assets assessment process flow under assets assessment process optimization, more assessment side's assets assessment process optimizations based on the form of bid and big data；Assets assessment modelling based on big data include under big data under the analysis of asset assessment system, big data under assets assessment indexes weight design and big data assets assessment model foundation.The present invention improves the assessment result reliability of intangible asset, reduce assessment difference risk, intangible asset accuracy is promoted, the module and data structure of exploitation can provide more reference values, further specification intangible asset market for the assessment of intangible asset.
Description
Technical field
The present invention relates to computer software technical field, more particularly to a kind of intangible asset side based on big data
Method and system.
Background technology
The research origin of big data is proposed " 3V " feature of big data by Laney (2001) earliest in foreign countries：Capacity is big
(Volume), diversified (Variety), speed are fast (Velocity).Foreign countries are more early for assets assessment related field research,
It is proposed that the overall value of company information has included information assets in Glazer (1993), Neil Crosby etc. (2003) are pointed out
Intangible asset is larger since time lag causes rating result deviation occur.The research that big data is combined with assets assessment also originates from
It is more outstanding to have Lucio Cassia and Silvio Vismara (2009) by using 2003-2005 in foreign countries
Between 784 parts of European Company seller analysts equity report, the related infinite horizon laid particular emphasis in research company's valuation field is pre-
Survey the problem of assuming；Syed Umar Farooq (2010) etc. mainly study cash flow with big data and discount Valuation Modelling and stock
Profit is discounted model；Moffitt (2013) extends map analysis by business data ecology and assesses data, from traditional structuring decimal
According to the big data being coupled till now including structuring, unstructured data.With big data thinking, intangible asset is played
Both sides influences and correlative study background has：
(1) the big data skill upgrading fairness of assets assessment, science：Under big data background how maintenance data
The fairness, science and assets price that digging technology improves assets assessment predict (especially intangible asset) reasonability to assets
Assessment risk management, supervision mechanism are crucial.Big data technology is in Study on Price field and traditional economy theory simultaneously
Combination be Asset Pricing field new trend, domestic and foreign scholars have also made this many researchs.Such as：Hutehisont is first
First neural network algorithm is introduced into European option pricing model for the Pricing Research to option assets；Some scholars apply
AMIRA tools are pre- with data to the prediction management in terms of data deployment analysis (ARIMA (P, d, q) model) progress financial asset
It is very universal to survey following way；Domestic scholars also studied many about big data technology to law assets, enterprise assets
Measurement, also include the assessment based on big data to project, personal asset, intangible asset.
(2) big data embodies the value of itself during assets assessment, and the measurement that big data itself is worth belongs to nothing
The assessment scope of shape assets.Early in 1980, the futurist Alvin Toffler in the U.S. proposed big data concept,
McKinsey & Co.'s publication in 2011《Big data：Next innovation, competition and productivity forward position》Report after big data each
Each industry of row all becomes a research hotspot, and feature develops to high speed from various (Variety), a large amount of (Volume) originally
(Velocity) (Grobelink, Dumbill, 2012) and variable (Variability) (Hopkins&Evelson, 2012).
The value for starting discovery big data recent years, although the big data 99% in early-stage study on internet is to 99% user
Useless, but with cloud computing, the development of big data industry, the famous Information technology providers in 2016 to the 2018 years whole world
International Data Corporation (IDC) increase by the estimation of big data market scale on a year-on-year basis with 40% every year.
Kweiyang big data exchange sets up within 2015, just signs annual 10000000 yuan of data with one, Shenzhen logistics trading enterprise for the year
Framework agreement is purchased, by October, 2017, the accumulation of transaction on exchange volume breaks through 1.2 hundred million yuan, nearly 300,000,000 yuan of framework agreement of transaction etc.
These all indicate big data China value dimension.Domestic and foreign scholars in the value research of big data to proposing big data
Proprietary problem and digital asset are said, are put into practice according to big data trade market both domestic and external, and the property attributes of big data are also gradual
It is clear.
In terms of policy, U.S. IASB exists within 1989《Formulate and submit the frame of financial statement》Clear stipulaties assets assessment with
The metering of accounting element, and China to 2006《Accounting standards for enterprises》Just compared with the measurement criteria of system, revise within 2014《Enterprise
Industry accounting standard --- basic norm》Just compare the metering of clear stipulaties intangible asset.The corresponding laws and regulations U.S. is 1989
Year has just passed through special legislation, and unified assets assessment management system is established in the whole nation；Britain is dedicated to unified assess and goes
Industry tissue and evaluation criteria construction, and these standards is made great efforts to be expanded to other countries；It is influenced by Britain's assets assessment standard,
European fourth edition in 2000《European assessment level》Just increase for the first time《Guide eight --- intangible asset》.
In conclusion it is fewer to the research of assets assessment related system with the expansion of big data thinking, it is commented in intangible asset
Estimate aspect and be essentially blank, the capacity gauge that big data technology has can be that intangible asset is obtained than more comprehensive data
Data, the function of machine learning may be that intangible asset provides the metering method of the science that compares and therefore studies and set
Intangible asset system of the meter based on big data contributes to the health, science, sustainable development of assets assessment industry.
Invention content
Invention is designed to provide a kind of intangible asset method and system based on big data, improves invisible money
The assessment result reliability of production, while quality of evaluation is improved, assessment difference risk is reduced, it is accurate to promote intangible asset
Property, the science of intangible asset is improved, the module and data structure of exploitation can provide more for the assessment of intangible asset
More reference values, further specification intangible asset market, to solve the problems mentioned in the above background technology.
To achieve the above object, the present invention provides the following technical solutions：
A kind of intangible asset method and system based on big data include the assets assessment stream supervised based on big data
Cheng Youhua, the assets assessment modelling based on big data and the design of the intangible asset system based on big data, wherein
Assets assessment process optimization based on big data supervision include single assessment side visual angle under assets assessment process optimization,
Assets assessment process flow under more assessment side's assets assessment process optimizations and big data based on bid form；
Assets assessment modelling based on big data includes being provided under the analysis of asset assessment system, big data under big data
Produce the foundation of assets assessment model under evaluation index weight design and big data；
Intangible asset system design based on big data includes functional analysis, Interface design, algorithm design and system
Implementation process designs.
Preferably, functional analysis includes following three subsystem：
(1) acquisition system, platform acquire structuring, semi-structured, more comprehensive in conjunction with crawler technology, scanning monitoring technology
Acquisition assessment business data collecting work and relevant industries data information, the basic data of acquisition system is assets assessment
Whole foundation, assessing it fairness and authenticity has considerable influence；
(2) analysis system participates in the process analysis procedure analysis of assets assessment by way of assessing resource cloud, expert's cloud, determines and closes
The assets assessment scheme of reason, analysis system are the core of assets assessment, and assessment is fixed a price and is summarised in analysis system and completes；
(3) learning system, assets assessment result are shown in a manner of value interval, in the risk analysis for determining assessment
After prediction income, assessment report is formed.
Preferably, the data grabber process of Interface design includes：
(1) information of specified page is obtained：The content of the page is obtained on the specified addresses URL；
(2) reptile of appointed website is obtained；
(3) reptile of designated key on the internet.
Preferably, algorithm, which designs, includes：
(1) the information scratching algorithm design on the page；
(2) big data learning algorithm designs.
Preferably, for more assessment side's assets assessment process optimizations based on bid form, propose that assessment needs with consigner
Starting point is sought, it is specified that two to five assessment sides not waited, are isolated consigner with assessment side by the bidding form of reserve fund.
Compared with prior art, the beneficial effects of the invention are as follows：
(1) transformation traditional value assesses idea, surrounds interests person, evaluator, the regulator triadic relation of assets assessment, fortune
Assets assessment model of the intangible asset Establishing based on big data under big data is analyzed with AHP, and is calculated using decision tree
Method analyze and improve legacy asset assessment, in conjunction with big data technology provide assets assessment earnings forecast thinking improve it is invisible
The assessment result reliability of assets, while quality of evaluation is improved, reduce assessment difference risk.
(2) forecast function of assets assessment compartmental results and assessment result and tracking learning functionality can solve existing skill
In art the problem of the accurate measurement value of intangible asset, intangible asset accuracy is promoted.
(3) be directed to legacy asset assessment there are the problem of, optimize assets assessment with big data technology and Scientific control means
Flow, include single assessment side visual angle under assets assessment and more assessment side's assets assessments based on the form of bid, improve nothing
The science of shape assets assessment.
(4) " internet+" intangible asset system is researched and developed, the module and data structure of exploitation can be intangible asset
Assessment provides more reference values, further specification intangible asset market.
Description of the drawings
Fig. 1 is the structural framing figure of the present invention；
Fig. 2 is assets assessment flow chart under the visual angle of single assessment side of the present invention；
Fig. 3 is more assessment side's assets assessment flow charts based on bid form of the present invention；
Fig. 4 is assets assessment process flow under the big data of the present invention；
Fig. 5 is assets assessment model under the big data of the present invention；
Fig. 6 is assets assessment decision tree under the big data of the present invention；
Fig. 7 is assets assessment earnings forecast decision tree under the big data of the present invention；
Fig. 8 is assets assessment system framework under the big data of the present invention
Fig. 9 tests (study) platform framework for assets assessment under the big data of the present invention；
Figure 10 is the assets assessment platform interface schematic diagram of the present invention；
Figure 11 is the framework of the intangible asset 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 only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
Referring to Fig. 1, a kind of intangible asset method and system based on big data, specific embodiment and method
It is as follows：
(1) the assets assessment process optimization based on big data supervision
(1) assets assessment process optimization under the visual angle of single assessment side
Referring to Fig. 2, the optimization of assets assessment flow is to propose evaluation requirement starting point with consigner, and in evaluation process
In and assessment result be not involved in, with ensure assessment side independence；The process of assets assessment will be intervened by focusing on monitoring party, from
Assess many-sided supervision such as qualification, assessment result.Assets assessment supervision department is clear in relevant laws and regulations, prison
Guan Fang should also advocate intervention evaluation process supervision when formulating assessment level, be allowed to feasibility, operability of criterion etc. and constantly change
Into.After assessment side signs assessment contract with consigner, monitoring party is supervised by big data technology intervention procedure, pre- to assessment result
Sentence carry out analysis on its rationality, finally consigner, assessment side, monitoring party tripartite game after propose assessment report.Monitoring party is thrown
Entering certain manpower and materials, transformation both sides' game is tripartite Game, and can not only promote assets assessment fairness can have greatly improvement,
Also can it is a series of to the recombination, merger, bankruptcy of industry etc. may caused by the question of market be subject to control, and monitoring party is in order to carry
Fairness, the science for rising supervisory efficiency and supervision can also make great efforts the utilization for exploring the scientific methods such as big data.
(2) more assessment side's assets assessment process optimizations based on bid form
Referring to Fig. 3, in assets assessment industry, because the distrust of interests person both sides, assessment result occur and are expected partially
Situations such as difference is more, the case for duplicating assessment is also very much, this not only wastes assessment duration, energy, money etc..With commission
Side proposes evaluation requirement starting point, it is specified that two to five not equal assessment sides, by the bidding form of reserve fund consigner
It is isolated with assessment side, the independence of assessment side can be effectively ensured in this way, the entrusted does not influence assessment result, is commented to be promoted
Estimate the prestige of industry.Meanwhile each assessment Fang Junhui makes an effort to promote the accuracy of assets assessment, including the use of computer
Technology realizes corresponding statistical model, batch assessment, assessment data prediction etc., is just introduced from another side for assets assessment industry big
Data provide basic condition.Assessment side can obtain certain reserve fund in evaluation process, be used for the expense of evaluation work, and
Obtain assessment remaining fund after assessment result is approved, and can in industry prestige bonus point, and it is unreasonable for assessment result
Carry out deduction, these supervision results be used as the qualification of assets assessment screen foundation, promotion assets assessment industry it is winning bad
It eliminates.Increase reserve fund expense in more assessment side's assets assessment flows performance based on bid form, but for repeat assessment and
Can all there be larger change in terms of assessment result distrust, and monitoring party can reduce input manpower and materials, promote big data and obtain
And analysis ability, allow assets assessment industry development to go on prestige track as early as possible.
(3) assets assessment process flow under big data
Referring to Fig. 4, application of the big data in assets assessment field be not very extensively, and assets assessment with compared with
Strong industrial nature, related data and algorithm comparison are few in the big data platform of mainstream, this just needs expert to conclude assets
Evaluation requirement, theme, basic service etc. acquire the web page library of related subject by WEB crawler technologies on the internet, receipts
The data material collected is through certain pretreatment basis of formation data bank, so that big data technology is analyzed.Then it is dug by data
Module is dug, analysis foundation data bank forms assets assessment effective information library, and data-mining module needs to continue to optimize effective letter
Library is ceased, effective information library could be allowed more modest, in order to promote efficiency and the enhancing user search experience of later stage platform application
Deng, and the implementation of auxiliary machinery study and prediction algorithm, and can assets assessment number be formed for assets assessment effective information library
According to visualization and related data safety problem, be also improved place required for data mining, in addition, carrying out on the internet
Deployment WEB reptiles can be because the privacy of partial data leads to IP limitation access etc., in order to acquire more fully assets assessment industry
Data, collecting work may will produce certain expense.
(2) the assets assessment modelling based on big data (containing design procedure and implementation method)
(1) under big data asset assessment system analysis
Assets assessment is directed not only to appraisal agency (appraiser, evaluator), (stakeholder contains assets to assessment object
Assignor and assignee etc. be known as interests person), and be related to the supervision of department (supervision unit, regulator), wherein interests phase
Pass person has a certain difference assets value identification, and values difference is caused to be not necessarily the identification skill of assets value itself
The multi-party prediction of art (appraisal procedure) problem, synergistic effect after assigning there are the potential value of assets or assets etc. differs
It causes.Therefore, related participant wants to obtain tendentiousness, the reliability of assessment result in assets assessment activity, is ground under big data
Study carefully assets assessment triadic relation and finds that evaluator, interests person, regulator respectively to the evaluation index in assets assessment activity, are commenting
As far as possible than more comprehensively reflecting respective advantage factors and condition in the setting of valence index system, for big data assets assessment
The destination layer of system, which summarizes, can reflect big data technology and assets assessment industry requirement factor, be built from big data ability is obtained
It stands with first class index such as big data analysis, standardization, forecasting mechanisms, index is then further refined, shown in table specific as follows：
Under the rule that regulator formulates, the mutual game between interests person and evaluator surrounds interests and is unfolded, comments always
The person of estimating, interests person, regulator are with the assessment indicator system of interests priority principle design assets assessment triadic relation's structure.It ties simultaneously
Big data is closed, each appraisement system is refined, analytic hierarchy process (AHP) is then based on, in conjunction with the jdgement matrix and index of expert
Weight design, guarantee carry out assets assessment result objective and accurate evaluation, to promote the science and public affairs of assets assessment report
Positivity.
(2) assets assessment indexes weight design under big data
In general sense, to avoid the missing and deviation of information, more two are set in the appraisement system of assets assessment
Grade index, and the weight design of index is the numerical value of a relative percentage, weight number it is directly proportional to the importance of index,
And index is not suitable for the foundation and analysis of model too much in linear regression, and therefore, this research application analytic hierarchy process (AHP) (AHP)
Determine that each first class index and two level refine the relative weighting of index, it is unbalance to avoid index weights, finally determine each index pair
In the synthetic weight of big data asset assessment system general objective.Comparator matrix A is initially set up, to the importance of index at all levels
Compare two-by-two, compares shown in the following formula of publicity 1：
There is n evaluation index in hypothesis evaluation system A, then obtains a n rank judgment matrixs A=after expert judging
(aij)n×n, the comparator matrix A of each level index is as shown in formula 2.
Then, sequence indexes of the Judgement Matricies B for each index in calculating matrix A, first passes through Mode of Level Simple Sequence
The process for exactly asking priority weight sequence of all factors of a certain layer to a certain factor in upper layer, shown in following formula 3
Further according to ranking results (rmax=max { ri) and judgment matrix B solution feature vector weights, the specific steps are：The
The product M of all elements in k rowsk, and seek MkN times root bePlace is normalized after seeking feature vector weight
Reason, obtains characteristic vector W, shown in following formula 4.
In formula, wiThe relative weighting of as each index finally carries out total sequence according to the relative weighting of each index and calculates
Absolute weight, it is assumed that (A layers) of last layer time includes A1, A2..., AmTotal m element, their total hierarchial sorting weight are respectively
a1, a2..., am, and it includes n element B to set (B layers) of its next layer1, B2..., Bn, they are about AjThe single weight order difference of layer
For b1j, b2j..., bnj(work as BiWith AjWhen onrelevant, bij=0), then weight b of each element relative to general objective layer in B layers1,
b2..., bnIt can be calculated in the way of formula 5, big data assets assessment index weights and importance ranking result of calculation are as follows
Shown in table：
2 big data assets assessment index weights of table and importance ranking
(3) under big data assets assessment model foundation
Fig. 5-7 is please referred to, on the basis of big data assets assessment index weights based on importance ranking, is establishing big number
According to lower assets assessment model to assess professional, assessment is scientific, assets assessment business information data is excavated, assessment fairness,
Assets assessment standardized data library etc. carries out node analysis.Meanwhile this research surrounds the triadic relation of assets assessment, from profit
The purpose of appraisals of beneficial person, evaluation requirement set out, under the constraintss such as the assessment laws and regulations of regulator, assessment level, assessment
Person fully uses big data technical limit spacing industry data, establishes suitable assessment foundation etc. as big data assets assessment model
Basis.Under big data assets assessment model (D) fully demonstrated on the basis of assets assessment index Design assets assessment authenticity,
Fairness, stability, science, comprehensive etc..It is assumed that appraisal agency (evaluator) receives each specific assessment case (e),
Usually indicated by feature vector (feature vector), as shown in formula 6, wherein e(n)Indicate n-th of assessment case
Feature.
E=(e(1), e(2), e(3)..., e(n))T(formula 6)
Evaluator obtains corresponding industry big data, as assessment foundation, is made of feature vector and output, big data
Set representations are as shown in formula 7, wherein input is also known as sample data with output.
E={ (e1, y1), (e2, y2) ..., (en, yn) (formula 7)
The assessment case that evaluator receives has certain industry wide under normal circumstances, you can it is considered as continuous variable, but
Since assessment timeliness, appraisal procedure and assessment industry may change, variable has the characteristics that centainly discrete again, and right
In output result often not at continuous variable feature, therefore commented using decision tree in classification problem to solve assets under big data
Estimate model problem to be relatively suitble to, decision function is represented by Y=f (e).Assets assessment model, first honor are established under big data
Whether the assessment result of assets assessment industry rule and the constraint of relevant law laws and regulations again, big data study has reference price
Value is the very important evaluation index of assets assessment model, it plays very crucial influence factor to the prediction of big data.?
Under the influence of the respective interests of interests person both sides, the respective anticipated price model of the assignor and assignee of assets in assets assessment activity
It encloses with assessment result there is also certain relevance, knock-down price is also influenced by negotiation between both parties skill, this research exists regarding knock-down price
Assessment section is that assessment result has reference value, and in this, as the foundation of prediction model, is commented because knock-down price is not happened at
Estimating its later stage income of section may be changed by corresponding acquisition cost, and similarly forecasting system is for given input data
enCorresponding output y is provided by modeln, statistical learning aim at from assume space in choose optimal models, pass through decision tree
It indicates shown in following formula.
Under big data assets assessment prediction model whether can realize meet estimation range be it is crucial consider one of standard, by
The assets transfer occurred after assets assessment may occur due to other great interference incidents and influence its prediction deviation, also may be used
Can be not comprehensive enough to the superposition performance analysis after asset portfolio in prediction model, while there is also prediction results in assessment report
With the gap actually to strike a bargain, and prediction model is estimated with assessing section, is that its unpredictable cost becomes for knock-down price
Change can also have a certain impact to prediction model.
Empirical risk minimization strategy is then considered as prediction model, provisional profit should be assets assessment in assets transfer
The adaptive expectations of acquisition are needed most in the process, however prediction is considered as various risks assessment, therefore with the calculating of risk minimization
It is movable safe to be conducive to this, ensures to predict shown in the following formula of safety with Bayesian Estimation probability event.
And there is certain influence relationship in many prediction models, between test error and the complexity of model, and it is expected
And it is very big that deviation probability occurs in reality, therefore optimizes risk minimization strategy by regularization, this is for optimal prediction model
A role of correcting is played, shown in following formula, γ (f) is used as regularization term, for adjusting forecasting risk.
(3) the intangible asset system design based on big data
(1) functional analysis
Fig. 8-9 is please referred to, assets assessment system generally comprises the establishment of three zones assets assessment project relevant documentation, assets
Assessment material summarizes, analyzes, the related description of assessment report and assessment, and the assets assessment Platform Designing based on big data also needs to
Extension assessment business data acquisition and corresponding the sector information collection, pass through data-mining module in assets assessment material summarizes
Corresponding effective information library is established, realizes that assessment assets later stage benefit is pre- by big data machine learning techniques in assessment report
It surveys, the assets assessment platform framework for being specifically based on big data is as shown below.Data mining, big data technology are in assets assessment system
Each stage in assets assessment work is covered in system, platform is divided to acquire, analyze, learn three big subsystems, work(
It can be briefly described as follows：
1) acquisition system：Because unstructured data acquisition, cleaning and analysis difficulty are larger, and it is frequently necessary to human intervention,
Therefore this platform mainly acquires structuring (application systems and the related data such as assessment industry, appraisal agency, professional big data information
Library), semi-structured (assets assessment related web page, report and related resource library), in conjunction with crawler technology, scanning monitoring technology compare
The comprehensive data information for obtaining assessment business data collecting work and relevant industries, the basic data of acquisition system is that assets are commented
The whole foundation estimated, assessing it fairness and authenticity has considerable influence.
2) analysis system：The process analysis procedure analysis of assets assessment is participated in by way of assessing resource cloud, expert's cloud, it is reasonable to determine
Assets assessment scheme, analysis system not only needs the support of data mining technology, also to there is the result of big data analysis.Analysis
System is the core of assets assessment, and assessment fixes a price and summarizes and will be completed in analysis system, the direct learning system of analysis result
Assessment result and predictive ability.
3) learning system：Assets assessment result is shown in a manner of value interval, in the risk analysis for determining assessment
After prediction income, assessment report is formed.Because assessment prediction income whether be actually consistent, it is also necessary to carry out assessment tracking clothes
Business, to the variance analysis reason of assessment, and improves relevant algorithm to promote the forecast function of learning system, reduces subsequent money
Assessment prediction gap is produced, the science of assets assessment is promoted.
Big data, " internet+", cloud computing technology means are studied, design intangible asset system can expand to money
Production assessment experiment porch, the systematicness and science of assets assessment profession is promoted with modular training method, while with assets
Appraisal agency, enterprise case be template refine Simulation Evaluation project, can greatly promote and put into practice technical ability.
(2) Interface design
Referring to Fig. 10, being reduction collecting work amount in the assets assessment platform based on big data, acquisition quality is promoted, from
External system accesses data-interface, such as the assessment resources bank of the relevant financial management system of enterprise, financial robot system, industry
And related web site etc., it is ideal selection.Wherein the management system of specification and database are fairly simple in Interface design,
The demand model matching of general elder generation's Interworking Data, then by SQL statement it is achieved that by for semi-structured data
(WEB) there are certain dynamic factors for Interface design, it is therefore desirable to the analyses such as website, structure, node is carried out to website, from net
Page, document type start with, to its nodal community, element sort out, could be than more comprehensively docking semi structured data.With half structure
For changing data (WEB) Interface design, data will also carry out content analysis in advance in crawl, be grabbed according to certain topic
It takes, on the one hand can mitigate the load for being crawled website, on the other hand can also promote the efficiency of data preparation.Semi-structured data
(WEB) there is html tag feature, as long as being to establish webpage to correspond to one to the website structure analysis common practice that needs capture
Dom tree (website node and content) is extracted and is handled with the relevant element of theme in the page, be by the traversal to dom tree
Than more comprehensively research, capture program is divided into following three kinds of realizations：
1) information (simple, general) of specified page is obtained：The content of the page is obtained on the specified addresses URL, it is main
If the URL set and the corresponding DOM of these webpages of data source required for assets assessment are established, safeguarded according to artificial judgment
It sets (structure of web page of different web sites is generally all different), can periodically or non-periodically obtain the data of these webpages, disadvantage exists
In safeguarding that set of URL closes the workload of corresponding dom tree, while certain computer expertise cooperation is needed, uses python
The inquiry that reptile frame Scrapy is crawled.
2) reptile (depth) of appointed website is obtained：It is relatively more suitable for department and issues relevant assessment mark on corresponding website
The guidance of the public welfare website orientation industry such as accurate, detailed rules and regulations and assets assessment employer's organization, assessment case etc., as long as passing through assets assessment
Mechanism investigation can be collected into than more comprehensive reference site, and the dom tree with website is generally all regular, established and tieed up
Dom tree is protected relatively to be easy.
3) reptile (range) of designated key on the internet：The information of numerous assets assessments is contained on the internet,
And these information are not often concentrated, in order to more fully obtain the data of assets assessment, it is necessary to pass through theme on the internet
Capture the data of all kinds of correlations, difficult point is to need to dispose cloud computing platform, uses crawler technology and search engine technique
In conjunction with, and will appear IP and access limitation, distribution subject captures the problems such as failing.
(3) algorithm designs
1) the information scratching algorithm design on the page
It captures file title, content and downloads attachment (assets assessment basic norm), which can be due to different URL
Variation, algorithm and realization process are almost the same.Set of URL closes content of the corresponding dom tree between obtaining two labels, and usual
This label is all to occur in pairs, it is easy to construct tree, construction thinking shows greatly WEB page interior joint information and HTML
Label carrys out piecemeal processing, constructs a matrix H (HTML) first for html tag rule in the pairs of memory page of in order of numbers
Then gather (such as："<title>" and "</title>","<Meta " and "/>"), shown in following formula：
Html tag is matched in acquiring the page and corresponding content information depends on assets assessment platform to the page info
Acquisition demand, substantially demand is divided into two classes in the practice of platform：
The first kind completely acquires page info, and acquisition is being cleaned；This is needed HTML labels in the page one by one
Match, and content is obtained, if to find each label
Li={ i=1,2,3..., n }, the corresponding traverse path set of the corresponding dom tree of the page
Dj=d=1,2,3..., 2m-1, ωijFor LiAnd DjMatching relationship on side, the DOM trees T=(L, D) of acquisition should
Shown in the following formula of operand on all sides of dom tree that the page obtains：
Second class carries out designated key acquisition to page info, this needs reversely obtains theme correspondence from specific subject
Html tag Li={ i=1,2,3..., n }, acquisition content of pages block be contentj, reversed acquisition is complete in the label
Content, the theme topical of the kth of acquisitionkShown in the following formula of local correlation degree：
It can be compared by regular expression in python crawler technologies and be fast implemented, with python reptile frames
The inquiry code that Scrapy is realized is as follows：
(2) big data learning algorithm designs
Big data integrated study is generally built upon on the basis of the multiple graders of study, common in machine learning algorithm
Grader has Bagging, Boosting, Stacking etc., is AdaBoost algorithms, big data study than more typical algorithm
There is the survival of the fittest using this sorting algorithm, to the effectiveness ranking of grader, the promotion weight such as to classifying quality difference is similarly divided
The good grader weight of class effect will reduce, and sort device, may finally mention classification with high accuracy in each iteration
Device, being applied particularly to assets assessment platform is：Sample data (e1, y1) (referring to formula 7), if weak classifier set is C=
(c1, c2..., cn), respective weights Wi, the formula after strong classifier is integrated is as follows.
Every time after the completion of study, the weight for readjusting sample, weight normalized is needed to be
To correct in upper subseries by the weight of the sample of mistake point, become next iteration, shown in the following formula of iteration, each iteration mistake
A new Weak Classifier is all added in journey, until classification error reach system setting numerical value, to for assessment report (containing prediction
Function) continuous self-perfection provide thinking.
It is assumed that input data record (Array) is the attribute value (value) of a rule, searching from top to bottom meets classification and determines
The attribute value of plan attribute conditions, if deriving that the correlation rule of attribute value is effective, even if classifying successfully, output category result
(data), Implementation of pseudocode is as follows：
(4) system implementation process designs
1 is please referred to Fig.1, intangible asset research process is related to the guiding of assets assessment industry, interagency coordination and evaluator
Just culture etc..
With the fast development of the information technologies such as " internet+", big data, cloud computing, data mining, information technology and biography
The combination of system industry will be the development trend of New Economy, and industry is led to interpenetrate, mutually promote, in assets assessment industry,
Just effective benefit, the fusion of big data method and theory of asset appraisal are feasible and effective for big data.Design based on big data
There is intangible asset model certain versatility, system design also to have certain autgmentability, can serve assets and comment
Estimate industry.The research of assets assessment platform based on big data is started with from the relationship of analysis big data and assets assessment, is used
Analytic hierarchy process (AHP) is from first class index such as acquisition big data ability, big data analysis, standardization, forecasting mechanisms, then arrives two-level index
Refinement, intangible asset model under big data is established by index weights assignment, and use the modelling assets assessment
System, assets assessment model and correspondence system solve the problems, such as follows：
(1) assets assessment triadic relation is surrounded, fully demonstrates its authenticity, fairness, stability, science in a model
Property, it is comprehensive, devise asset evaluation method under big data with decision tree, improve the science of assets assessment, and then specification provides
Production assessment market.
(2) analytic hierarchy process (AHP) is used, asset assessment system is scientifically built, designs the whole frame of intangible asset platform
The function having needed for the module of frame and each subsystem of determining platform, to provide theories integration for assets assessment industry development.
(3) each during maintenance data excavates in assets assessment platform, big data technology to intangible asset works
Stage, and partition functionality analysis and corresponding Interface design are carried out to acquisition system, analysis system, learning system.
(4) in assets assessment at present, the construction of intangible asset related platform and research based on big data are fewer, need
The work such as assets assessment policy, case, teaching platform are collected, specification, standard database are formed, to support follow-up intangible asset
Evaluation Platform construction.
In conclusion the intangible asset method and system proposed by the present invention based on big data, for intangible asset
Value measurement basis, scientific, institutionalization relatively lack, the computerized informations such as " internet+", big data, cloud computing
Technology is dissolved into assets assessment industry, researches and develops " internet+" intangible asset system, the module and data structure of exploitation can
More reference values are provided with the assessment for intangible asset, further specification intangible asset market changes traditional value
Idea is assessed, interests person, evaluator, the regulator triadic relation of assets assessment are surrounded, invisible money under big data is analyzed with AHP
It produces evaluation system and establishes the assets assessment model based on big data, and use Analysis on Decision Tree Algorithm and improve legacy asset and comment
Estimate, the earnings forecast thinking that assets assessment is provided in conjunction with big data technology improves the assessment result reliability of intangible asset, together
When improve quality of evaluation, reduce assessment difference risk.For legacy asset assessment there are the problem of, with big data technology and section
School superintendent's barrel means optimize assets assessment flow, assets assessment and are commented based on form that call for bid under the visual angle for including single assessment side more
The side's of estimating assets assessment improves the science of intangible asset, on the basis of assets assessment model, designs based on big data
Intangible asset system, from data acquisition, data mining to machine learning, detailed analysis system function, and to system
Interface and core algorithm are designed, and are formed the intangible asset method based on big data, are also adopted including assets assessment data
Set method, analysis method and big data learn prediction technique, the value of intangible asset especially in current many new high-tech enterprises
Physical assets are alreadyd exceed, assets assessment, metering etc. have ten to economic behaviours such as the merging, recombination and bankruptcy of new high-tech enterprise
Divide urgent demand, this can also be further driven to the development of assets assessment industry, assets assessment compartmental results and assessment result
Forecast function and tracking learning functionality can solve the problems, such as intangible asset in the prior art accurate measurement value, promoted nothing
Shape assets assessment accuracy.
The foregoing is only a preferred embodiment of the present invention, but scope of protection of the present invention is not limited thereto,
Any one skilled in the art in the technical scope disclosed by the present invention, according to the technique and scheme of the present invention and its
Inventive concept is subject to equivalent substitution or change, should be covered by the protection scope of the present invention.
Claims (5)
1. a kind of intangible asset method and system based on big data, it is characterised in that：Include being supervised based on big data
Assets assessment process optimization, the assets assessment modelling based on big data and the intangible asset system based on big data
Design, wherein
Assets assessment process optimization based on big data supervision include single assessment side visual angle under assets assessment process optimization, be based on
Assets assessment process flow under more assessment side's assets assessment process optimizations of bid form and big data；
Assets assessment modelling based on big data includes that assets are commented under the analysis of asset assessment system, big data under big data
Estimate the foundation of assets assessment model under indexes weight design and big data；
Intangible asset system design based on big data includes that functional analysis, Interface design, algorithm design and system are implemented
Process Design.
2. a kind of intangible asset method and system based on big data according to claim 1, it is characterised in that：Work(
It includes following three subsystem that can analyze：
(1) acquisition system, platform acquire structuring, semi-structured, than are more comprehensively obtained in conjunction with crawler technology, scanning monitoring technology
The data information of assessment business data collecting work and relevant industries is taken, the basic data of acquisition system is the entirety of assets assessment
Foundation, assessing it fairness and authenticity has considerable influence；
(2) analysis system participates in the process analysis procedure analysis of assets assessment by way of assessing resource cloud, expert's cloud, determines rational
Assets assessment scheme, analysis system are the core of assets assessment, and assessment is fixed a price and is summarised in analysis system and completes；
(3) learning system, assets assessment result are shown in a manner of value interval, in the risk analysis for determining assessment and in advance
After surveying income, assessment report is formed.
3. a kind of intangible asset method and system based on big data according to claim 1, it is characterised in that：It connects
Mouthful design data grabber process include：
(1) information of specified page is obtained：The content of the page is obtained on the specified addresses URL；
(2) reptile of appointed website is obtained；
(3) reptile of designated key on the internet.
4. a kind of intangible asset method and system based on big data according to claim 1, it is characterised in that：It calculates
Method designs：
(1) the information scratching algorithm design on the page；
(2) big data learning algorithm designs.
5. a kind of intangible asset method and system based on big data according to claim 1, it is characterised in that：It is right
In based on bid form more assessment side's assets assessment process optimizations, with consigner propose evaluation requirement starting point, it is specified that two to
Five assessment sides not waited, are isolated consigner with assessment side by the bidding form of reserve fund.
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