CN105590245A - Computer implementation method and data processing method for locating fault cause of electronic transaction - Google Patents
Computer implementation method and data processing method for locating fault cause of electronic transaction Download PDFInfo
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- CN105590245A CN105590245A CN201410845194.5A CN201410845194A CN105590245A CN 105590245 A CN105590245 A CN 105590245A CN 201410845194 A CN201410845194 A CN 201410845194A CN 105590245 A CN105590245 A CN 105590245A
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Abstract
The invention discloses a computer implementation method used for locating the fault cause of electronic transaction. The method comprises the following steps: extracting appropriate transaction data from an electronic transaction database; selecting the data set of a transaction participant with high failure rate and/or failure number comprehensive consideration value as a statistical data set from the transaction data; for each factor in a factor set affecting the quality of electronic transaction, calculating a non-uniformity index reflecting the failure rate and failure contribution degree corresponding to the factor in the statistical data set; determining a factor in the factor set affecting the quality of electronic transaction as a key factor according to the non-uniformity index of the failure rate and failure contribution degree; for each level or a combination of levels of the key factor, calculating the failure rate (EC) and failure contribution degree (ER) corresponding to the level or the combination of levels in the statistical data set; and working out a Pareto optimal set by taking the failure rate (EC) and failure contribution degree (ER) corresponding to the level or the combination of levels as a target, and determining the key level in the key factor. The invention further discloses a data processing method.
Description
Technical field
The present invention relates to computer program, specifically, relate to a kind of computer implemented method and data processing method of fault cause of positioning electronic transaction.
Background technology
Concentrate the electronic transaction quality of rotary-connecting to relate to numerous dimensions, generally include: answer back code, type of transaction, transaction channel, transaction medium, nature of account, account number, transmitting mechanism, receiving mechanism trade company, terminal etc. For instance, various transaction answer back codes can reach over one hundred kind, nearly tens kinds of type of transaction, all kinds of transaction channels. With regard to transaction participant dimension, the thousands of families of the transmitting mechanism of participating in business every day and receiving mechanism. Due to mass data and super various dimensions, if there is no relevant data processing method and good system, be difficult to initiatively find all sidedly problem and the factor location of online general use from magnanimity transaction.
Summary of the invention
In order to address the above problem, according to the application aspect, provide a kind of computer-implemented method, for the fault cause of positioning electronic transaction, described method comprises: from electronic transaction database, extract suitable transaction data, from described transaction data, choose the data set of the transaction participant that mortality and/or failed stroke count comprehensive consideration value are high as statistics set, for each factor in the sets of factors of the described electronic transaction quality of impact, calculate the mortality corresponding with this factor of reflection in described statistics set and the non-uniformity index of failed contribution degree, wherein the larger expression of inhomogeneous index is more even, wherein, the described mortality corresponding with this factor represents the ratio in all failed transactions with the failed transactions of this factor analysis, and the described failed contribution degree corresponding with this factor represents and the failed transactions of this factor analysis ratio in the transaction of all and this factor analysis, according to the non-uniformity index of described mortality and failed contribution degree, determine which factor in the sets of factors of the described electronic transaction quality of described impact is key factor, for each rank of described key factor and the combination of rank, calculate mortality (EC) corresponding with the combination of this rank or rank in described statistics set and failed contribution degree (ER), wherein, the mortality corresponding to the combination of this rank or rank represents the ratio in all failed transactions with the specific rank of described key factor or the relevant failed transactions of level combination, and the failed contribution degree corresponding to the combination of this rank or rank represents and the specific rank of described key factor or the relevant failed transactions of the level combination ratio in the specific rank of all and described key factor or the relevant transaction of level combination, and taking the mortality corresponding with the combination of this rank or rank (EC) and failed contribution degree (ER) as target, ask for the optimum collection of Pareto, thereby determine the crucial rank in described key factor.
In said method, described non-uniformity index is entropy, and the entropy of described mortality is CrameV, and the entropy of described failed contribution degree is standardization entropy.
Said method also can comprise: according to the crucial rank in determined key factor, by asking for cartesian product, thereby generate one or more other key factors and crucial rank.
Said method also can comprise: the optimum collection of Pareto is asked in the set that described key factor and crucial rank are formed.
Said method also can comprise: define multiple rules, in described multiple rules, each rule is corresponding to a key factor and other combination of a critical level.
Said method also can comprise: according to certain condition, described multiple rules merged, thus concentrated fuzzy rules.
Said method also can comprise: according to regular generation relation, be one group by the compatible rule merging with identical trunk node.
Said method also can comprise: according to failed contribution degree, described rule is sorted.
In said method, to ask for the optimum collection of Pareto and comprise and utilize dominance relation that target function value is divided into multiple different grades, the grade of the optimum non-domination solution of concentrating of wherein said Pareto be minimum.
According to another aspect of the application, a kind of data processing method is provided, for the fault cause of positioning electronic transaction, described method comprises: for each factor in the sets of factors of the described electronic transaction quality of impact, in counting statistics data acquisition system, reflect the mortality corresponding with this factor and the non-uniformity index of failed contribution degree, wherein the larger expression of inhomogeneous index is more even, wherein, the described mortality corresponding with this factor represents the ratio in all failed transactions with the failed transactions of this factor analysis, and the described failed contribution degree corresponding with this factor represents and the failed transactions of this factor analysis ratio in the transaction of all and this factor analysis, according to the non-uniformity index of described mortality and failed contribution degree, determine which factor in the sets of factors of the described electronic transaction quality of described impact is key factor, for each rank of described key factor and the combination of rank, calculate mortality (EC) corresponding with the combination of this rank or rank in described statistics set and failed contribution degree (ER), wherein, the mortality corresponding to the combination of this rank or rank represents the ratio in all failed transactions with the specific rank of described key factor or the relevant failed transactions of level combination, and the failed contribution degree corresponding to the combination of this rank or rank represents and the specific rank of described key factor or the relevant failed transactions of the level combination ratio in the specific rank of all and described key factor or the relevant transaction of level combination, and taking the mortality corresponding with the combination of this rank or rank (EC) and failed contribution degree (ER) as target, ask for the optimum collection of Pareto, thereby determine the crucial rank in described key factor.
Feature and rule that the application's technical scheme exists by analyzing failed transactions, orient crucial rank and the factor (as the failure on certain channel of certain type of transaction between Mou Liang mechanism) of impact transaction quality, the row major level of going forward side by side sequence, makes issue in focus.
Brief description of the drawings
After having read the specific embodiment of the present invention with reference to accompanying drawing, those skilled in the art will become apparent various aspects of the present invention. Those skilled in the art should be understood that: these accompanying drawings are only for coordinating detailed description of the invention that technical scheme of the present invention is described, and are not intended to protection scope of the present invention to be construed as limiting.
Fig. 1 is according to the schematic diagram of the data handling system of the fault cause of the application embodiment, positioning electronic transaction;
Fig. 2 is according to the flow chart of data processing schematic diagram of the fault cause of the application embodiment, positioning electronic transaction.
Detailed description of the invention
What introduce below is some in multiple possibility embodiment of the present invention, aims to provide basic understanding of the present invention, is not intended to confirm key of the present invention or conclusive key element or limits claimed scope. Easily understand, according to technical scheme of the present invention, do not changing under connotation of the present invention other implementation that one of ordinary skill in the art can propose mutually to replace. Therefore, below detailed description of the invention and accompanying drawing be only the exemplary illustration to technical scheme of the present invention, and should not be considered as of the present invention all or be considered as restriction or the restriction to technical solution of the present invention.
In magnanimity transaction data, finding the origin cause of formation of failed transactions, when reason is that single factor causes and has obvious characteristic (as all failures of certain type of transaction), is not part difficult matter. But when reason is multifactor causing, the property value of various dimensions and one-dimensional degree reaches 1,000,000, necessarily even more than one hundred million grades time, carry out again various combination between dimension, data, by explosive growth, are now found the origin cause of formation of failed transactions as looked for a needle in a haystack, and will be the very thing of difficulty of part.
Feature and rule that the application's technical scheme exists by analyzing failed transactions, orient crucial rank and the factor (as the failure on certain channel of certain type of transaction between Mou Liang mechanism) of impact transaction quality, the row major level of going forward side by side sequence, makes issue in focus. In addition, the application's rule of also giving chapter and verse, from knowledge base, derive possible reason and scheme (as certain territory in transaction), as the reference of dealing with problems, form analysis report, and give relevant transaction participant by analysis result active push, to dealing with problems fast and effectively, promote success rate, the bank acceptance rate of transaction.
With reference to figure 1, Fig. 1 is according to the schematic diagram of the data handling system of the fault cause of the application embodiment, positioning electronic transaction. This data handling system comprises data processing equipment. As shown in Figure 1, data processing equipment is from transaction system extraction, cleaning, load transaction data. Through the processing of data processing equipment, analyze feature and rule that failed transactions exists, thereby crucial rank and the factor (as the failure on certain channel of certain type of transaction between Mou Liang mechanism) of orienting impact transaction quality, the row major level of going forward side by side sequence, makes issue in focus. In addition, data processing equipment is also according to rule, from knowledge base, derive possible reason and scheme (as certain territory in transaction), as the reference of dealing with problems, form analysis report, and giving relevant transaction participant by analysis result active push, analysis report reader can be according to the actual solution situation feedback of problem, the storehouse of refreshing one's knowledge.
Fig. 2 is according to the schematic flow sheet of the data processing equipment of the fault cause of the application embodiment, positioning electronic transaction.
As shown in Figure 2, in step 1, electronic transaction data are carried out to essential information statistics, thereby can obtain each factor basic statistics values at different levels. In step 2 and step 3, calculate respectively contribution degree (for example, ER and EC) and freedom (for example, CrameV and standard entropy). In step 4, carry out Bi-objective projection, to obtain key factor. In step 5, analyze in conjunction with the key factor drawing in contribution degree and step 4, and carry out Pareto analysis in step 6, thereby draw individual event rule, be i.e. the crucial rank of key factor. In step 7 and step 8, carry out respectively Association Rule Analysis and compatible rule merging, grouping, sequence, thereby draw multinomial rules results collection.
According to the application embodiment, first, data processing equipment extracts suitable transaction data from electronic transaction database. Then the data set that, data processing equipment is chosen mortality and/or the high transaction participant of failed stroke count comprehensive consideration value from described transaction data is as statistics set (as single factor statistics). Then,, for each factor in the sets of factors of the described electronic transaction quality of impact, calculate the mortality corresponding with this factor of reflection in described statistics set and the non-uniformity index of failed contribution degree. Subsequently, according to the non-uniformity index of described mortality and failed contribution degree, determine which factor in the sets of factors of the described electronic transaction quality of described impact is key factor. Follow again, for each rank of described key factor and the combination of rank, calculate mortality (EC) corresponding with the combination of this rank or rank in described statistics set and failed contribution degree (ER). Finally, taking the mortality corresponding with the combination of this rank or rank (EC) and failed contribution degree (ER) as target, ask for the optimum collection of Pareto, thereby determine the crucial rank in described key factor.
In this flow chart of data processing, ER represents mortality, embodies and measurement problem from ratio. EC represents failed contribution degree, and it embodies and measurement problem from actual amount. In one embodiment, CrameV is the inhomogeneous statistical indicator of reflection ER, and standardization entropy is the inhomogeneous statistical indicator of reflection EC.
In one embodiment, factor and the rank thereof of impact transaction quality are carried out to Bi-objective projection, be mapped as two index: ER, EC of transaction quality. Projection pattern can be taked two kinds of spot projection and dimension projections. So-called spot projection is that the impact transaction factor rank of quality or the combination of factor rank are regarded as to a point in plane, and each point can calculate ER, EC by transaction situation. So-called dimension projection is that the factor of impact transaction quality is regarded as to a point in plane, and each point calculates the inhomogeneous statistical indicator of reflection ER: CrameV, and the inhomogeneous statistical indicator of reflection EC: standardization entropy.
In one embodiment, using mortality and failed contribution degree as two targets, utilize dominance relation that target function value is divided into some different grades, i.e. rank (rank). In optimizing process, the rank of non-domination solution (optimal solution) is 1, until the rank minimum of this solution, to reach optimality. This process is also referred to as Pareto multi-objective optimization.
By by key factor create-rule and multinomial rule, generate relevant information, strengthen readable. In one embodiment, according to CrameV, standardization entropy carries out the projection of Bi-objective dimension, asks for key factor. For key factor, adopt Pareto optimizing and two kinds of methods of correspondence analysis to ask for the crucial rank of key factor, generate individual event rule.
In the application's a embodiment, realize in the following way the generation of multinomial rule:
First during, to the result of K item rule, do cartesian product (thinking of correlation rule) and derive from K+1 factor rule (step a). Then, K+1 item rule is verified, and carried out regular leaching (step b) by Bi-objective. Finally, K+1 item rule is asked for to the optimum collection of Pareto (step c). If can also derive from more high-level rules, turn to step a.
In the application's a embodiment, by by qualified compatible rule merging, concentrated fuzzy rules carrys out the merging of implementation rule. In another embodiment, according to regular generation relation, be one group of grouping that carrys out implementation rule by the regular merger with identical trunk node. In yet another embodiment, rule compositor is realized in the following way: in group, according to generation relation, between group, according to EC, strictly all rules is sorted.
To sum up, the application's technical scheme is for magnanimity transaction data, the feature and the rule that exist by analyzing failed transactions, orient crucial rank and the factor (as the failure on certain channel of certain type of transaction between Mou Liang mechanism) of impact transaction quality, the row major level of going forward side by side sequence, make issue in focus, solved the problem of looking for a needle in a haystack.
Above, describe the specific embodiment of the present invention with reference to the accompanying drawings. But those skilled in the art can understand, without departing from the spirit and scope of the present invention in the situation that, can also do various changes and replacement to the specific embodiment of the present invention. These changes and replacement all drop in the claims in the present invention book limited range.
Claims (10)
1. a computer-implemented method, for the fault cause of positioning electronic transaction, is characterized in that, described method comprises:
From electronic transaction database, extract suitable transaction data;
From described transaction data, choose the data set of the transaction participant that mortality and/or failed stroke count comprehensive consideration value are high as statistics set;
For each factor in the sets of factors of the described electronic transaction quality of impact, calculate the mortality corresponding with this factor of reflection in described statistics set and the non-uniformity index of failed contribution degree, wherein the larger expression of inhomogeneous index is more even, wherein, the described mortality corresponding with this factor represents the ratio in all failed transactions with the failed transactions of this factor analysis, and the described failed contribution degree corresponding with this factor represents and the failed transactions of this factor analysis ratio in the transaction of all and this factor analysis;
According to the non-uniformity index of described mortality and failed contribution degree, determine which factor in the sets of factors of the described electronic transaction quality of described impact is key factor;
For each rank of described key factor and the combination of rank, calculate mortality (EC) corresponding with the combination of this rank or rank in described statistics set and failed contribution degree (ER), wherein, the mortality corresponding to the combination of this rank or rank represents the ratio in all failed transactions with the specific rank of described key factor or the relevant failed transactions of level combination, and the failed contribution degree corresponding to the combination of this rank or rank represents and the specific rank of described key factor or the relevant failed transactions of the level combination ratio in the specific rank of all and described key factor or the relevant transaction of level combination, and
Taking the mortality corresponding with the combination of this rank or rank (EC) and failed contribution degree (ER) as target, ask for the optimum collection of Pareto, thereby determine the crucial rank in described key factor.
2. the method for claim 1, wherein described non-uniformity index is entropy, and the entropy of described mortality is CrameV, and the entropy of described failed contribution degree is standardization entropy.
3. the method for claim 1, also comprises: according to the crucial rank in determined key factor, by asking for cartesian product, thereby generate one or more other key factors and crucial rank.
4. method as claimed in claim 3, also comprises: the optimum collection of Pareto is asked in the set that described key factor and crucial rank are formed.
5. method as claimed in claim 3, also comprises: define multiple rules, in described multiple rules, each rule is corresponding to a key factor and other combination of a critical level.
6. method as claimed in claim 5, also comprises: according to certain condition, described multiple rules merged, thus concentrated fuzzy rules.
7. method as claimed in claim 5, also comprises: according to regular generation relation, be one group by the compatible rule merging with identical trunk node.
8. method as claimed in claim 5, also comprises: according to failed contribution degree, described rule is sorted.
9. the method for claim 1, wherein ask for the optimum collection of Pareto and comprise and utilize dominance relation that target function value is divided into multiple different grades, the grade of the optimum non-domination solution of concentrating of wherein said Pareto be minimum.
10. a data processing method, for the fault cause of positioning electronic transaction, is characterized in that, described method comprises:
For each factor in the sets of factors of the described electronic transaction quality of impact, in counting statistics data acquisition system, reflect the mortality corresponding with this factor and the non-uniformity index of failed contribution degree, wherein the larger expression of inhomogeneous index is more even, wherein, the described mortality corresponding with this factor represents the ratio in all failed transactions with the failed transactions of this factor analysis, and the described failed contribution degree corresponding with this factor represents and the failed transactions of this factor analysis ratio in the transaction of all and this factor analysis;
According to the non-uniformity index of described mortality and failed contribution degree, determine which factor in the sets of factors of the described electronic transaction quality of described impact is key factor;
For each rank of described key factor and the combination of rank, calculate mortality (EC) corresponding with the combination of this rank or rank in described statistics set and failed contribution degree (ER), wherein, the mortality corresponding to the combination of this rank or rank represents the ratio in all failed transactions with the specific rank of described key factor or the relevant failed transactions of level combination, and the failed contribution degree corresponding to the combination of this rank or rank represents and the specific rank of described key factor or the relevant failed transactions of the level combination ratio in the specific rank of all and described key factor or the relevant transaction of level combination, and
Taking the mortality corresponding with the combination of this rank or rank (EC) and failed contribution degree (ER) as target, ask for the optimum collection of Pareto, thereby determine the crucial rank in described key factor.
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Application publication date: 20160518 |