CN114693280B - Digital collaborative office platform based on electronic signature technology - Google Patents
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Abstract
The invention is suitable for the field of computers, and provides a digital collaborative office platform based on an electronic signature technology, which comprises the following steps: the distribution and detection module is used for distributing the target task data to the corresponding examination and approval addresses according to the examination and approval process, and detecting the stay time of the target task data in the examination and approval nodes of the security-related subtask data after the target task data is examined and approved by the examination and approval nodes of the general subtask data, wherein the target task data comprises the general subtask data which are examined and approved in advance and the security-related subtask data which are examined and approved later; the obtaining module is used for obtaining the in-doubt data marked by the first approver passing the electronic signature authentication at the approval node of the security associated subtask data if and only if the stay time exceeds the first set time length, and the obtaining module has the advantages that: whether can reliably provide quick examination and approval reference for suspicious data does benefit to first approver and improves the efficiency of examining and approving, can improve the security and the privacy of examining and approving simultaneously.
Description
Technical Field
The invention belongs to the field of computers, and particularly relates to a digital collaborative office platform based on an electronic signature technology.
Background
The birth of the internet enables society to have a rapid revolution, the living mode and the working mode are also changed greatly, the coming of the internet era and the popularization of the artificial intelligence technology enable the enterprise to be transformed into a new wave in a digital way, but the data is displayed according to certain authoritative survey organization: more than half of domestic enterprises are in the stage of digital entry, the application of the new technology is in the experimental stage, and the customer experience is poor; 30% of the enterprises are in the digital explorer stage; and only less than 1% of enterprises go to the last stage of enterprise digital transformation to become digital subverters.
At present, the digital collaborative office in the market mainly has two major types of platform type and tool type, and the platform type mobile office software means: the four platforms basically have the functions of personnel management, schedule, online documents, online conferences, cloud disks and the like, and have vertical solutions of different industries, and the tool type mobile office software comprises: online meeting tools, online documentation tools, online memorandum tools, online flow chart tools, online project management tools, and the like.
The applicant has found that the above technical solution has at least the following disadvantages: 1. for some important examination and approval office links, due to the heavy work or the inconvenience of places where the examiners are located, some contents may lack certain understanding or judging capability, so that the examination and approval progress is delayed, but a channel capable of carrying out safe consultation cannot be found at one time; 2. the protection of some relatively important data in the cooperative office is not enough, which easily causes the leakage of the data.
Disclosure of Invention
The embodiment of the invention aims to provide a digital collaborative office platform based on an electronic signature technology, and aims to solve the problems in the background technology.
The embodiment of the invention is realized in such a way that a digital collaborative office platform based on an electronic signature technology comprises the following steps:
the distribution and detection module is used for distributing the target task data to the corresponding examination and approval addresses according to the examination and approval process, and detecting the stay time of the target task data in the examination and approval nodes of the security-related subtask data after the target task data is examined and approved by the examination and approval nodes of the general subtask data, wherein the target task data comprises the general subtask data which are examined and approved in advance and the security-related subtask data which are examined and approved later;
the obtaining module is used for obtaining the in-doubt data marked by a first approver authenticated by the electronic signature at the approval node of the confidential associated subtask data and identifying the type entry of the in-doubt data if and only if the stay time exceeds a first set time length;
the scaling transformation module is used for acquiring execution data which meets the requirement of matching with the in-doubt data and is input by a preset number of target task executors, and performing corresponding scaling transformation on the execution data to obtain scaling range execution data, wherein the scaling transformation proportion is acquired from historical successful target task data which is similar to the in-doubt data;
and the judging and prompting module is used for judging whether the in-doubt data are all in the range of the zoom range execution data, if so, sending an information available reference prompt at the approval node of the secret related subtask data, otherwise, sending an information to-be-further-confirmed prompt at the approval node of the secret related subtask data, and the information reliable prompt and the information unreliable prompt are respectively used for indicating that the secret related subtask data are available for reference and are to-be-further-confirmed.
As a further aspect of the present invention, the platform further includes a hierarchy identification module, the hierarchy identification module including:
the identification unit is used for acquiring target task data and identifying the security level of the target task data;
the dividing unit is used for dividing the sensitive data related to the target task data when the security level of the target task data exceeds the security threshold level, and calculating the density-preserving score of the divided sensitive data according to the scores of the preset classification items and the single classification items;
and the marking unit is used for marking the sensitive data exceeding the density-preserving score threshold value as the confidential subtask data, and marking other data as the general subtask data.
As a still further aspect of the present invention, the platform further includes a timing module, and the timing module includes:
the timing unit is used for starting to calculate the stay time of the confidential associated subtask data after the general subtask data completes the approval of an approval node before the approval node corresponding to the first approver;
and the judging unit is used for judging the stay time length of the calculated privacy association subtask data and the size of the first set time length.
As a further aspect of the present invention, the specific steps of obtaining the scaling of the scaling transformation from the historical successful target task data having similar association with the in-doubt data include:
acquiring historical successful target task data through the historical successful approval record;
identifying historical successful subtask data similar to the in-doubt data in the historical successful target task data, and marking all historical successful subtask data with similarity greater than a first preset threshold value with the in-doubt data;
calculating the mean value of the numerical words corresponding to all the historical successful subtask data and obtaining the maximum value and the minimum value of the numerical words corresponding to the subdata data;
and respectively calculating the ratio of the maximum value to the average value and the ratio of the minimum value to the average value to obtain the magnification ratio and the reduction ratio.
As a further aspect of the present invention, the specific step of identifying historical successful subtask data similar to the in-doubt data in the historical successful target task data includes:
decomposing the in-doubt data according to parts of speech to obtain a first keyword combination, wherein the first keyword combination comprises a combination of nouns and volume words;
respectively decomposing the contents in the historical successful target task data according to a part-of-speech decomposition mode in the in-doubt data to obtain a second keyword combination, wherein the part-of-speech combinations of the second keyword combination and the first keyword combination are the same;
and identifying the similarity between the second keyword combination and the first keyword combination, defining the second keyword combination with the similarity larger than a second preset threshold as all the historical successful subtask data, and defining the number words bound by the nouns and the quantifiers as the number words corresponding to the subdata.
As a further aspect of the present invention, the platform further includes an execution data reporting module, where the execution data reporting module includes:
the issuing unit is used for issuing the type item and the first keyword combination to a terminal where a target task executor corresponding to the target task data is located, and numbering all the terminals from small to large in sequence;
and the reporting unit is used for establishing an information transmission channel between the numbered terminals, the information transmission channel is used for receiving all the front execution data sent by the terminal with the number being in the previous position, allowing the execution data input by the corresponding target task executor to be received, transmitting the self execution data and all the front execution data to the terminal with the number being in the next position, and then sending a feedback completion instruction to the terminal with the number being in the previous position.
As a further aspect of the present invention, the zoom range execution data is execution data that is of the same type as the words corresponding to the historical successful subtask data and that is subjected to the calculation of the zoom-in ratio and the zoom-out ratio.
As a further aspect of the present invention, the platform further includes a notarization and output module, the notarization and output module including:
the acquisition unit is used for acquiring completely approved target task data when the stay time length does not exceed a first set time length or when and only after the stay time length exceeds the first set time length;
and the notarization unit is used for notarizing the completely approved target task data, the notarization information at least comprises an approval correlation link of a first approver, and if the notarization is passed, the notarization and completely approved target task data are output.
According to the digital collaborative office platform based on the electronic signature technology, the target task data comprise general subtask data and confidential associated subtask data through the arrangement of the distribution and detection module and the like, and an approver of the general subtask cannot see the content of the confidential associated subtask data, so that the privacy and the safety of the target task data are ensured; directly clicking the location of a main approval pain point before time lag by acquiring the susceptance data marked by a first approver authenticated by an electronic signature at an approval node of the security-associated subtask data; and obtaining a scaling range execution data by correspondingly scaling and transforming the execution data, judging whether the in-doubt data are all in the range of the scaling range execution data, namely obtaining the scaling range execution data by the successfully-approved historical successful target task data and the execution data associated with the target task data, and judging whether the in-doubt data are all in the range of the scaling range execution data, so that a quick approval reference is reliably provided for whether the in-doubt data are reliable under the condition that the in-doubt data are not leaked, the efficiency of approval is improved by a first approver, the in-doubt data can be marked by the first approver after the first approver passes electronic signature authentication, and the safety of approval is further ensured.
Drawings
Fig. 1 is a first main structure diagram of a digital collaborative office platform based on electronic signature technology.
Fig. 2 is a second main structure diagram of a digital collaborative office platform based on electronic signature technology, which comprises a hierarchy identification module.
Fig. 3 is a third main structure diagram of a digital collaborative office platform based on electronic signature technology, which includes a timing module.
FIG. 4 is a detailed flow diagram of scaling a transform through historical successful target task data having similar associations with in-doubt data.
FIG. 5 is a detailed flow diagram of identifying historical success subtask data in the historical success subtask data that is similar to the in-doubt data.
Fig. 6 is a fourth main structure diagram of a digital collaborative office platform based on electronic signature technology, which includes a data reporting module.
Fig. 7 is an implementation environment diagram for data reporting in a digital collaborative office platform based on an electronic signature technology.
Fig. 8 is a fifth main structure diagram of a digital collaborative office platform based on electronic signature technology, which includes a notarization and output module.
Fig. 9 is a schematic flow chart of approval in a digital collaborative office platform based on an electronic signature technology.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the invention.
Specific implementations of the present invention are described in detail below with reference to specific embodiments.
The invention provides a digital collaborative office platform based on an electronic signature technology, which solves the technical problem in the background technology.
As shown in fig. 1 and fig. 9, a main structure diagram and a schematic flow diagram of approval (described in conjunction with specific projects) of a digital collaborative office platform based on an electronic signature technology according to an embodiment of the present invention are provided, where the digital collaborative office platform based on the electronic signature technology includes:
the distribution and detection module 10 is used for distributing the target task data to corresponding examination and approval addresses according to an examination and approval process, each examination and approval address is provided with at least one examination and approval node, and the stay time of the examination and approval nodes of the security-related subtask data is detected after the target task data is examined and approved by the examination and approval nodes of the general subtask data, wherein the target task data comprises the general subtask data which are examined and approved in advance and the security-related subtask data which are examined and approved later; specifically, the form of the target task data includes, but is not limited to, a multimedia form such as an electronic file, a picture or a video;
an obtaining module 20, configured to obtain the in-doubt data marked by the first approver in the approval node of the confidential subtask data through electronic signature authentication, and identify a type entry of the in-doubt data, if and only if the dwell time exceeds a first set time length, where the in-doubt data may be expressed as a xx element (kilogram, centimeter, etc.) when the in-doubt data relates to a price (weight, size, etc.) of an article a, for example;
specifically, in fig. 9, the initial approver initiates target task data of the XX wind turbine project budget, which is in the form of an electronic file, and after a plurality of second approvers approve general subtask data, the target task data stream is transferred to the first approver, where the general subtask data: and (4) the procurement period: y month XX day in X year; security association subtask data: the quantity of yaw motor accessories purchased is XX, the unit price is XY units/unit, and the in-doubt data marked by the first approver is the yaw motor accessories: the unit price is XY unit/station; the second approver cannot see the confidential associated subtask data;
it can be understood that the first approver can mark the in-doubt data and other operations only after passing the electronic signature authentication, thereby further ensuring the safety of the approval;
a scaling transformation module 30, configured to obtain execution data matched with the in-doubt data, and perform corresponding scaling transformation on the execution data to obtain scaling range execution data, where a scale of the scaling transformation is obtained from historical successful target task data having similar association with the in-doubt data, where the similar association may be understood as data in an approved history file of the same type or the same type, and the execution data is mainly used to optimize the execution data by the corresponding scaling transformation, so as to further reduce an error of the execution data, where the execution data may be understood as data directly related to execution and implementation of the target task data, and since a change may occur due to a change in time during implementation, by the scaling transformation, it is substantially ensured that even if reliability of an execution data source is low, the actual approximate change range of the execution data can be determined according to the change range of the similar associated data in the approved history file, and the change is not changed when being searched, so that the method has a better reference effect when the confidential associated subtask data is not clear enough due to the missing or insufficient knowledge of the first approver or forgetting;
and the judging and prompting module 40 is used for judging whether the in-doubt data is in the range of the execution data in the zooming range, if so, sending an information available reference prompt at the examination and approval node of the secret related subtask data, otherwise, sending an information to-be-further-confirmed prompt at the examination and approval node of the secret related subtask data, wherein the information reliable prompt and the information unreliable prompt are respectively used for indicating that the secret related subtask data is available for reference and is to be further confirmed.
In the embodiment of the invention, when the method is applied, in consideration of the important degree of criticality of the first approver, the workload of work or the distance between the first approver and the approval initiator, the reliability of some confidential associated subtask data may lack certain understanding or judgment capability, so that the approval progress is delayed; directly clicking the location of a main approval pain point before time lag by acquiring the susceptance data marked by a first approver authenticated by an electronic signature at an approval node of the security-associated subtask data; and performing corresponding scaling transformation on the execution data to obtain scaling range execution data, judging whether the doubtful data are all in the range of the scaling range execution data, namely obtaining the scaling range execution data through the successfully approved historical successful target task data and the execution data associated with the target task data, and judging whether the doubtful data are all in the range of the scaling range execution data, so that a quick approval reference is reliably provided for whether the doubtful data are reliable under the condition that the doubtful data are not leaked, the efficiency of approval is improved by a first approver, the doubtful data can be marked by the first approver only through electronic signature authentication, and the safety of approval is further ensured.
As shown in fig. 2 and 3, as a preferred embodiment of the present invention, the platform further includes a hierarchy identification module 00, and the hierarchy identification module 00 includes:
the identification unit 001 is used for acquiring target task data and identifying the security level of the target task data;
the dividing unit 002 is configured to divide the sensitive data related to the target task data when the security level of the target task data exceeds the security threshold level, and perform the density-preserving score calculation on the divided sensitive data according to the scores of the preset classification items and the single classification items;
and the marking unit 003 is used for marking the sensitive data exceeding the density-preserving score threshold as confidential subtask data, and marking other data as general subtask data.
It can be understood that only data with a security level exceeding a security threshold level is defined as the security subtask data, and whether the security threshold level is exceeded or not is judged by the size between the security score and the security score threshold corresponding to the security threshold level, the sensitive data exceeding the security score threshold is the security subtask data, and the sensitive data not exceeding the security score threshold is the general subtask data;
furthermore, the security level of the target task data can be derived from the security level selected by the initial approval initiator, the definition of the sensitive data is derived from the setting in the system in advance, for example, the bidding related to a certain article in the winning bid document should belong to the more sensitive data before bidding, and the sensitive data should also have the data requiring higher sensitivity coefficient, for this, the density-preserving score calculation is performed by adopting the preset classification items and the single classification item scores, for example, the preset classification items are respectively the amount of money and the number of related customers; the scores of the individual classification items are respectively the score of a specific amount and the score of the number of related customers, the sum of the two scores is the density-keeping score, the scores corresponding to the amounts of different differences are also different, and the scores corresponding to the number of customers between different differences are also different, for example, the specific amount is 50 ten thousand, the number of related customers is 10, and assuming that the score criteria are 10 ten thousand/minute and 2 digits/minute, the density-keeping score can be calculated as follows: (50/10) + (10/2) =10 points, which should be compared to a warranty score threshold, and if the warranty score threshold is 8 points, then the sensitive data is confidential subtask data.
As shown in fig. 3, as a preferred embodiment of the present invention, the platform further includes a timing module 11, and the timing module 11 includes:
the timing unit 111 is configured to start to calculate a stay duration of the security-associated subtask data after the general subtask data completes the approval of an approval node before an approval node corresponding to the first approver;
a judging unit 112, configured to judge the calculated stay time and the first set time of the security-related subtask data; the setting of the first set time period may be determined according to practical experience, for example, 5h, and the first set time period may be different between different levels of approval documents.
The so-called first set duration is generally determined by an initial approval initiator according to actual conditions and experience, and the actual conditions according to which the first set duration is determined can be determined according to the complexity and the urgency of approval of different target task data, that is, the total approval durations of different target task data can be different, so that the first set duration can also be different; the initial approval initiator should be set according to actual conditions and experience (of previous approvals), and it should be understood that the first set time length is the longest allowed stay time of the secretly associated subtask data at the approval node, and the proportion of the stay time of the secretly associated subtask data in the approval node is not less than 50%, that is, the used time length is not less than the approval time length of the general subtask data.
As shown in fig. 4, as a preferred embodiment of the present invention, the specific steps of obtaining the scaling of the scaling transformation through the historical successful target task data with similar association with the in-doubt data include:
step S100: historical successful target task data are obtained through the historical successful approval record, and the historical successful target task data are preferably within a preset time period from the current time node, such as within the last year, and the reference value of relevant data is larger;
step S101: identifying historical successful subtask data similar to the in-doubt data in the historical successful target task data, and marking all historical successful subtask data with similarity greater than a first preset threshold value with the in-doubt data; similarly, the first preset threshold, as the first set duration, should be set according to practical situations and experience, for example, the first preset threshold is 80%, which means that only if the similarity between the history successful subtask data and the in-doubt data is greater than 80%, the marking is performed;
step S102: calculating the mean value of the numerical words corresponding to all the historical successful subtask data and obtaining the maximum value and the minimum value of the numerical words corresponding to the subdata data, wherein the numerical words represent the numerical words, the source of the numerical words corresponding to the subdata data is summarized at the upper level, and the explanation is expanded in the next embodiment;
step S103: and respectively calculating the ratio of the maximum value to the average value and the ratio of the minimum value to the average value to obtain the magnification ratio and the reduction ratio.
It can be understood that the history successful approval record has a greater reference value, and of course, it should be data that can be obtained by the system, and identify history successful subtask data similar to the in-doubt data in the history successful target task data, where the identification should be performed by first identifying topics of both, for example, by topic keywords, and the identification may be performed by using a principle similar to a similar identification principle of keyword combination, or by using a Convolutional Neural Network (CNN), and specifically, the identification related principle is described in the following embodiment;
the essence of the method is extraction of text keywords, which is an effective means for highly refining text information, accurately summarizes the text topics by 3-5 words to help readers quickly understand the text information, and at present, four main methods for extracting the text keywords in the prior art are provided: extracting keywords based on TF-IDF, extracting keywords based on TextRank, extracting keywords based on Word2Vec Word cluster, and extracting keywords with various algorithms fused;
specifically, for example, the numbers corresponding to the historical successful subtask data are 60, 70, 82, and 65, it should be understood that the numbers corresponding to the same type of keywords such as 60, 70, 82, and 65 are numbers, so that the numerical operation can be performed, the average value is 69.25, the maximum value is 82, the minimum value is 60, so that the enlargement ratio is 1.18, the reduction ratio is 0.87, and the corresponding dimensions can be elements (kilograms and centimeters), where the enlargement ratio and the reduction ratio are obtained mainly to effectively optimize the execution data and reduce the error.
As shown in fig. 5, the present embodiment is a further extension of the previous embodiment, and the specific step of identifying the historical successful subtask data similar to the in-doubt data in the historical successful target task data includes:
step S1011: decomposing the in-doubt data according to parts of speech to obtain a first keyword combination, wherein the first keyword combination comprises a combination of nouns and volume words;
step S1012: respectively decomposing the contents in the historical successful target task data according to a part-of-speech decomposition mode in the in-doubt data to obtain a second keyword combination, wherein the part-of-speech combinations of the second keyword combination and the first keyword combination are the same;
step S1013: and identifying the similarity between the second keyword combination and the first keyword combination, defining the second keyword combination with the similarity larger than a second preset threshold as all the historical successful subtask data, defining the number words bound by the nouns and the quantifier as the number words corresponding to the subdata, and generally defining the number words bound by the nouns and the quantifier as the numerical values between the nouns and the quantifier combinations.
Specifically, for example, when the combination of nouns and words is related to the price (weight, size, etc.) of an article a, it may be expressed as xx elements (kilograms, centimeters, etc.) corresponding to the blind areas of cognition that cannot be confirmed by the first approver, the nouns related to the second keyword combination may be B substituted by a, or C matched with a, whose dimension is the same as a or is the same dimension of the dimension of a in a conversion relationship, the identification of the similarity may be performed by a trained neural network model, the identification is based on the features of the pre-trained keyword combination, such as the part-of-speech expression of the keyword combination, the part-of-speech expression is converted into a vector form as the input of the neural network model, the initialization of the network weight is performed by using the rands function of matlab, the hidden layer and output layer output are calculated according to the formula, and errors, updating the network weight, after training the neural network, predicting the network by using the extracted second keyword combination, inputting the characteristic vector, and calculating the output of the hidden layer and the output layer to obtain the similarity between the second keyword combination and the first keyword combination;
specifically, in practical application, the method for identifying the similarity between the second keyword combination and the first keyword combination is not limited herein, and at present, in order to calculate the similarity between texts, the similarity calculation can be realized by a keyword matching technology, and the related principle includes a jaccard similarity coefficient, a cosine distance, a euclidean distance, a TFIDF and the like, which method is selected for identification, and is not limited herein, and the identification method itself is the prior art, and the main improvement point of the embodiment is that the second keyword combination before identification is obtained, and the number word corresponding to the identified subdata is extracted;
in addition, the similarity and the preset threshold may be determined by adding scores of single similarity, for example, only if the similarity score reaches 90% of the full score, the second keyword combination is determined to be defined as all the historical successful subtask data, where the main purpose of identifying the historical successful subtask data similar to the doubt data in the historical successful target task data is to obtain all the historical successful subtask data, so as to provide more accurate data support for calculating the enlargement ratio and the reduction ratio, effectively optimize the execution data, and reduce the error.
As shown in fig. 6 and fig. 7, as a preferred embodiment of the present invention, the platform further includes a data reporting module 31, where the data reporting module 31 includes:
the issuing unit 311 is configured to issue (by the server) the type entry and the first keyword combination to a terminal where a target task performer corresponding to the plurality of target task data is located, and number all the terminals from small to large in sequence;
a reporting unit 312, configured to establish an information transmission channel between numbered terminals, where the information transmission channel is configured to allow receiving of execution data input by a corresponding target task executor after receiving all the previous execution data sent by a terminal with a previous number, and transmit the own execution data and all the previous execution data to a terminal with a subsequent number, and then send a feedback completion instruction to the terminal with the previous number, and when the terminal with the previous number does not receive the feedback completion instruction within a second set time period after transmitting the execution data, feed back the own execution data and all the previous execution data to the terminal with the subsequent number and request to obtain the feedback completion instruction, and so on until the terminal with the number meeting the preset number reports all the execution data (to the server).
The number of the in-doubt data can be one or more, correspondingly, each in-doubt data at least corresponds to one execution data, and when the execution data corresponding to each in-doubt data is multiple, the maximum value and the minimum value of the execution data are removed, and then average value calculation is carried out, so that the error of the single execution data is eliminated;
it can be understood that all the execution data are obtained through the information transmission channels among the plurality of terminals, on one hand, the timeliness of the execution data reporting is ensured, when the terminal with the number in the previous position does not receive the feedback completion instruction within the second set time length after the execution data is transmitted by the terminal with the number in the previous position, the execution data and all the execution data in the previous position are fed back to the terminal with the number in the next position and the feedback completion instruction is required to be obtained, the terminals which do not meet the conditions are skipped in time, the reporting efficiency is ensured, and therefore the efficiency of the approval is ensured, on the other hand, the preset amount of execution data can be reported at one time, omission is avoided, and single one-by-one collection is not needed.
As a preferred embodiment of the present invention, the scaling range execution data is execution data that is of the same type as the numerics corresponding to the historical successful subtask data and that is subjected to the scaling-up and scaling-down calculations.
Here, the zoom range execution data is further explained and explained, that is, when the history success subtask data corresponding to the numeral is defined, the zoom range execution data is also the corresponding numeral and is subjected to calculation of the enlargement ratio and the reduction ratio; in another embodiment, the target task performer is automatically calculated based on the performance data input by the target task performer according to the existing market rules, and the scaling up and scaling down calculations are equivalent to optimizing the difference of the performance data, but may be other forms of performance data, such as performance data related to performance or implementation of the target task data (e.g., on a market or a network-wide platform), which is different from the historical successful target task data.
As shown in fig. 8, as a preferred embodiment of the present invention, the platform further includes a notarization and export module 50, and the notarization and export module 50 includes:
the acquiring unit 501 is configured to acquire completely approved target task data when the staying time does not exceed a first set time or when and only after the staying time exceeds the first set time; if and only if the stay time exceeds the first set time, the approval is possible to be successful, namely, the information is sent out at the approval node of the security-associated subtask data for reference prompt, and the first approver determines that the approval can be passed by combining the judgment of the first approver and the reliable prompt of the information;
a notarization unit 502, configured to notarize the completely approved target task data, where information of the notarization at least includes an approval correlation link of the first approver, and if the notarization passes, output the notarized and completely approved target task data; if the output complete approved target task data is an approved file, a CA (certificate Authority) authenticated mark should be attached to the approved target task data, so that the authority and the credibility of the approval are improved.
It should be noted that, the notarization of the link associated with the approval of the first approver herein mainly aims to further improve the security of the approval, because the target task data may be at the approval node where the first approver is located, because the other task data are general task sub-data, and it is necessary to notarize the key process or all the operation processes of the first approver, the notarization herein includes but is not limited to CA authentication, and the specific content thereof may include screen recording, shooting, identity verification, and the like of the operation process, which is not described herein, and the CA authentication itself belongs to a mature prior art, and no description is provided herein.
The embodiment of the invention provides a digital collaborative office platform based on an electronic signature technology, and through the arrangement of a distribution and detection module 10 and the like, the target task data comprises general subtask data and secrecy related subtask data, and an approver of the general subtask cannot see the contents of the secrecy related subtask data, so that the privacy and the safety of the target task data are ensured; directly clicking the location of a main approval pain point before time lag by acquiring the susceptance data marked by a first approver authenticated by an electronic signature at an approval node of the security-associated subtask data; obtaining a scaling range execution data through corresponding scaling transformation of the execution data, judging whether the doubtful data are all in the range of the scaling range execution data, namely obtaining the scaling range execution data through the successfully approved historical successful target task data and the execution data associated with the target task data, and judging whether the doubtful data are all in the range of the scaling range execution data, so that a quick approval reference is reliably provided for whether the doubtful data are reliable under the condition that the doubtful data are not leaked, the efficiency of approval is improved by a first approver, the doubtful data can be marked by the first approver through electronic signature authentication, and the safety of approval is further ensured; further, by executing the setting of the data reporting module 31, the reporting efficiency can be ensured, thereby ensuring the efficiency of the approval.
In order to load the above method and system to operate smoothly, the system may include more or less components than those described above, or combine some components, or different components, besides the various modules described above, for example, input/output devices, network access devices, buses, processors, memories, and the like.
The processor may be a Central Processing Unit (CPU), other general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like that is the control center for the system and that connects the various components using various interfaces and lines.
The memory may be used to store computer and system programs and/or modules, and the processor may perform the various functions described above by operating or executing the computer programs and/or modules stored in the memory and invoking data stored in the memory. The memory may mainly include a program storage area and a data storage area, where the program storage area may store an operating system, an application program required by at least one function (such as an information collection template presentation function, a product information distribution function, and the like), and the like. The storage data area may store data created according to the use of the berth-state display system (e.g., product information acquisition templates corresponding to different product types, product information that needs to be issued by different product providers, etc.), and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card (FlashCard), at least one disk storage device, a flash memory device, or other volatile solid state storage device.
It should be understood that, although the steps in the block diagrams of the embodiments of the present invention are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of the steps in various embodiments may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is specific and detailed, but not to be understood as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent should be subject to the appended claims.
The above description is intended to be illustrative of the preferred embodiment of the present invention and should not be taken as limiting the invention, but rather, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.
Claims (6)
1. A digital collaborative office platform based on electronic signature technology is characterized by comprising:
the distribution and detection module is used for distributing the target task data to the corresponding examination and approval addresses according to the examination and approval process, and detecting the stay time of the target task data in the examination and approval nodes of the security-related subtask data after the target task data is examined and approved by the examination and approval nodes of the general subtask data, wherein the target task data comprises the general subtask data which are examined and approved in advance and the security-related subtask data which are examined and approved later;
the obtaining module is used for obtaining the in-doubt data marked by a first approver authenticated by the electronic signature at the approval node of the confidential associated subtask data and identifying the type entry of the in-doubt data if and only if the stay time exceeds a first set time length;
the scaling transformation module is used for acquiring execution data matched with the in-doubt sub-data and carrying out corresponding scaling transformation on the execution data to obtain scaling range execution data, wherein the scaling transformation proportion is acquired from historical successful target task data which are similar to and associated with the in-doubt sub-data;
the specific steps of obtaining the scaling of the scaling transformation through historical successful target task data which is similar to the in-doubt data comprise:
obtaining historical successful target task data through the historical successful approval record;
identifying historical successful subtask data similar to the in-doubt data in the historical successful target task data, and marking all historical successful subtask data with similarity greater than a first preset threshold value with the in-doubt data;
calculating the mean value of the numerical words corresponding to all the historical successful subtask data and obtaining the maximum value and the minimum value of the numerical words corresponding to the subdata data;
respectively calculating the ratio of the maximum value to the average value and the ratio of the minimum value to the average value to obtain an amplification ratio and a reduction ratio;
the specific steps of identifying historical successful subtask data similar to the in-doubt data in the historical successful target task data include:
decomposing the in-doubt data according to parts of speech to obtain a first keyword combination, wherein the first keyword combination comprises a combination of nouns and volume words;
respectively decomposing the contents in the historical successful target task data according to a part-of-speech decomposition mode in the in-doubt data to obtain a second keyword combination, wherein the part-of-speech combinations of the second keyword combination and the first keyword combination are the same;
identifying the similarity between a second keyword combination and the first keyword combination, defining the second keyword combination with the similarity larger than a second preset threshold value as all historical successful subtask data, and defining the number words bound by nouns and quantifiers as the number words corresponding to the subdata;
and the judging and prompting module is used for judging whether the in-doubt data are all in the range of the zoom range execution data, if so, sending an information available reference prompt at the approval node of the secret related subtask data, otherwise, sending an information to-be-further-confirmed prompt at the approval node of the secret related subtask data, and the information reliable prompt and the information unreliable prompt are respectively used for indicating that the secret related subtask data are available for reference and are to-be-further-confirmed.
2. The digital collaborative office platform based on electronic signature technology as claimed in claim 1, wherein the platform further comprises a hierarchy identification module comprising:
the identification unit is used for acquiring target task data and identifying the security level of the target task data;
the dividing unit is used for dividing the sensitive data related to the target task data when the security level of the target task data exceeds the security threshold level, and calculating the density-preserving score of the divided sensitive data according to the scores of the preset classification items and the single classification items;
and the marking unit is used for marking the sensitive data exceeding the density-preserving score threshold value as the confidential subtask data, and marking other data as the general subtask data.
3. The digital collaborative office platform based on electronic signature technology as claimed in claim 1, wherein the platform further comprises a timing module comprising:
the timing unit is used for starting to calculate the stay time of the confidential associated subtask data after the general subtask data completes the approval of an approval node before the approval node corresponding to the first approver;
and the judging unit is used for judging the stay time length of the calculated secret correlation subtask data and the size of the first set time length.
4. The digital collaborative office platform based on the electronic signature technology as claimed in claim 1, wherein the platform further comprises a data reporting module, the data reporting module comprises:
the issuing unit is used for issuing the type item and the first keyword combination to a terminal where a target task executor corresponding to the target task data is located, and numbering all the terminals from small to large in sequence;
and the reporting unit is used for establishing an information transmission channel between the numbered terminals, the information transmission channel is used for receiving all the front execution data sent by the terminal with the number being in the previous position, allowing the execution data input by the corresponding target task executor to be received, transmitting the self execution data and all the front execution data to the terminal with the number being in the next position, and then sending a feedback completion instruction to the terminal with the number being in the previous position.
5. The digital collaborative office platform based on the electronic signature technology as claimed in claim 1 or 4, wherein the scaling range execution data is execution data which is the same type as the corresponding words of the historical successful subtask data and is subjected to scaling up and scaling down calculations.
6. A digital collaborative office platform based on electronic signature technology according to claim 1, 2 or 3, wherein the platform further comprises a notarization and export module comprising:
the acquisition unit is used for acquiring completely approved target task data when the stay time length does not exceed a first set time length or when and only after the stay time length exceeds the first set time length;
and the notarization unit is used for notarizing the completely approved target task data, the notarization information at least comprises an approval correlation link of a first approver, and if the notarization is passed, the notarization and completely approved target task data are output.
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Denomination of invention: A Digital Collaborative Office Platform Based on Electronic Signature Technology Granted publication date: 20220913 Pledgee: Jinan Rural Commercial Bank Co.,Ltd. Pledgor: Shandong GuoDun Information Technology Co.,Ltd. Registration number: Y2024980002239 |