CN116307765A - Artificial intelligence government affair data review method and system - Google Patents
Artificial intelligence government affair data review method and system Download PDFInfo
- Publication number
- CN116307765A CN116307765A CN202310271494.6A CN202310271494A CN116307765A CN 116307765 A CN116307765 A CN 116307765A CN 202310271494 A CN202310271494 A CN 202310271494A CN 116307765 A CN116307765 A CN 116307765A
- Authority
- CN
- China
- Prior art keywords
- data
- government
- government affair
- affair data
- review
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000012552 review Methods 0.000 title claims abstract description 106
- 238000000034 method Methods 0.000 title claims abstract description 34
- 238000013473 artificial intelligence Methods 0.000 title claims abstract description 31
- 238000012544 monitoring process Methods 0.000 claims abstract description 46
- 238000007781 pre-processing Methods 0.000 claims abstract description 20
- 238000012545 processing Methods 0.000 claims abstract description 11
- 238000005065 mining Methods 0.000 claims abstract description 6
- 238000004422 calculation algorithm Methods 0.000 claims description 24
- 238000003745 diagnosis Methods 0.000 claims description 21
- 238000004458 analytical method Methods 0.000 claims description 19
- 230000002159 abnormal effect Effects 0.000 claims description 18
- 238000011157 data evaluation Methods 0.000 claims description 13
- 230000006399 behavior Effects 0.000 claims description 11
- 238000010801 machine learning Methods 0.000 claims description 11
- 238000011156 evaluation Methods 0.000 claims description 10
- 238000003066 decision tree Methods 0.000 claims description 9
- 238000013136 deep learning model Methods 0.000 claims description 9
- 238000011161 development Methods 0.000 claims description 9
- 238000007418 data mining Methods 0.000 claims description 8
- 230000009471 action Effects 0.000 claims description 7
- 238000013528 artificial neural network Methods 0.000 claims description 7
- 230000008859 change Effects 0.000 claims description 7
- 238000001514 detection method Methods 0.000 claims description 7
- 206010000117 Abnormal behaviour Diseases 0.000 claims description 6
- 230000004927 fusion Effects 0.000 claims description 6
- 238000012300 Sequence Analysis Methods 0.000 claims description 5
- 238000000605 extraction Methods 0.000 claims description 5
- 238000000342 Monte Carlo simulation Methods 0.000 claims description 3
- 238000005457 optimization Methods 0.000 claims description 3
- 230000018109 developmental process Effects 0.000 description 6
- 230000008569 process Effects 0.000 description 5
- 238000004891 communication Methods 0.000 description 4
- 238000007726 management method Methods 0.000 description 4
- 238000013499 data model Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000007621 cluster analysis Methods 0.000 description 2
- 238000007405 data analysis Methods 0.000 description 2
- 238000013135 deep learning Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000007170 pathology Effects 0.000 description 2
- 238000009411 base construction Methods 0.000 description 1
- 238000013145 classification model Methods 0.000 description 1
- 238000013079 data visualisation Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000003062 neural network model Methods 0.000 description 1
- 238000003909 pattern recognition Methods 0.000 description 1
- 238000011176 pooling Methods 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- 238000012731 temporal analysis Methods 0.000 description 1
- 238000000700 time series analysis Methods 0.000 description 1
- 238000012800 visualization Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Educational Administration (AREA)
- Economics (AREA)
- Tourism & Hospitality (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Marketing (AREA)
- Theoretical Computer Science (AREA)
- Development Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Physics & Mathematics (AREA)
- Quality & Reliability (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention discloses an artificial intelligence government affair data review method and system, which are used for collecting multi-source government affair data, preprocessing the obtained multi-source government affair data, extracting features of the government affair data obtained by preprocessing, mining data, fusing and analyzing the data, and obtaining a first government affair data result; based on a plurality of pre-constructed government data review models, performing government data review model matching, inputting the first government data result into the government data review model obtained by matching, outputting the first government data review result, and generating a government decision report; and continuously acquiring government affair data, monitoring and diagnosing according to the implementation of government affair decisions, acquiring a second government affair data result, optimizing a corresponding government affair data review model according to the second government affair data result, and adjusting the implemented government affair decisions. The artificial intelligent government affair data review system has the advantages of higher data processing speed, higher accuracy, lower cost and the like.
Description
Technical Field
The invention relates to the technical field of artificial intelligence evaluation, in particular to an artificial intelligence government affair data evaluation method and system.
Background
In government purchasing bidding, a large amount of time may be spent for collecting and auditing quotations by a traditional artificial government affair data review system, and related quotations can be quickly and accurately collected and audited by a novel artificial intelligence government affair data review system, so that the efficiency of government purchasing bidding can be greatly improved. The invention provides an artificial intelligence government affair data review system which can be applied to the implementation process of government decision and administrative service, the management in government institutions and the like. Compared with the traditional artificial government affair data review system, the novel artificial intelligence government affair data review system has the advantages of higher data processing speed, higher accuracy, lower cost and the like.
Disclosure of Invention
Therefore, the invention provides an artificial intelligence government affair data review method and system, which are used for solving the problems that the existing artificial government affair review needs to take a lot of time to collect and review quotations, has low government purchasing bid-inviting efficiency and the like.
In order to achieve the above object, the present invention provides the following technical solutions:
according to a first aspect of an embodiment of the present invention, an artificial intelligence government affair data review method is provided, and the method includes:
collecting multi-source government affair data, preprocessing the obtained multi-source government affair data, extracting features, mining data, fusing and analyzing the government affair data obtained by preprocessing, and obtaining a first government affair data result;
based on a plurality of pre-constructed government data review models, carrying out government data review model matching in combination with a specific business scene and review requirements, inputting the first government data result into the government data review model obtained by matching, outputting a first government data review result, and generating a government decision report based on the first government review result;
and continuously acquiring government affair data according to the implementation of government affair decision, monitoring and diagnosing, analyzing and acquiring a second government affair data result by using the monitoring and diagnosing result of the government affair data, early warning abnormal conditions, optimizing a corresponding government affair data review model according to the second government affair data result, and adjusting the implemented government affair decision.
Further, collecting multisource government affair data specifically includes:
the government affair data is acquired through a crawler or through a website API or interface;
the source of the government data comprises a government department database or a database of a third party;
the content of the government affair data comprises government affair data, policy files, policy reading and government statistical data.
Further, feature extraction, data mining and data fusion and analysis are carried out on government affair data obtained through preprocessing, and the method specifically comprises the following steps:
the extracted characteristic data comprise social trends, geographic locations, economic development predictions, government behaviors and climate changes;
acquiring social trend information by using time sequence analysis on government affair data;
acquiring government action detection results by using text analysis on government service data;
analyzing and obtaining economic development condition prediction results by using a decision tree algorithm to government affair data;
grouping people or things in different geographic positions by using clustering algorithm analysis on government affair data;
and obtaining a climate change prediction result by using a neural network algorithm on government affair data.
Further, the plurality of government affair data review models specifically include:
a SWOT analysis model for identifying and evaluating advantages, disadvantages, opportunities, and threats of policy items;
the decision tree model is used for helping a decision maker to determine an optimal path according to different conditions;
a Monte Carlo simulation model for selecting the best results for the policy in order to maximize its utility;
a fuzzy logic model for identifying and evaluating uncertainties between policy variables; a predictive model for predicting the impact and possible outcome of the policy;
microscopic and macroscopic models for estimating the economic impact of policies;
and the machine learning or deep learning model is used for outputting government affair data classification results.
Further, continuously collecting government affair data and monitoring and diagnosing according to the implementation of government affair decision, which comprises the following steps:
based on data monitoring and diagnosis of user behaviors, acquiring abnormal behavior data of the user;
acquiring abnormal log data based on log data monitoring and diagnosis;
based on the data monitoring and diagnosis of the database, the access condition of the database is analyzed, and the abnormal condition is obtained.
According to a second aspect of an embodiment of the present invention, there is provided an artificial intelligence government affair data review system, the system including:
the data processing module is used for acquiring multi-source government affair data, preprocessing the acquired multi-source government affair data, extracting features of the government affair data obtained through preprocessing, mining data, fusing and analyzing the data, and acquiring a first government affair data result;
the evaluation module is used for carrying out the matching of the government affair data evaluation models based on a plurality of government affair data evaluation models which are built in advance and combining a specific business scene and evaluation requirements, inputting the first government affair data result into the government affair data evaluation model obtained by matching, outputting a first government affair data evaluation result, and generating a government affair decision report based on the first government affair evaluation result;
and the optimization module is used for continuously acquiring government affair data, monitoring and diagnosing according to the implementation of government affair decisions, analyzing and acquiring a second government affair data result by using the monitoring and diagnosing results of the government affair data, early warning abnormal conditions, optimizing a corresponding government affair data review model according to the second government affair data result and adjusting the implemented government affair decisions.
Further, the data processing module is specifically configured to:
acquiring social trend information by using time sequence analysis on government affair data;
acquiring government action detection results by using text analysis on government service data;
analyzing and obtaining economic development condition prediction results by using a decision tree algorithm to government affair data;
grouping people or things in different geographic positions by using clustering algorithm analysis on government affair data;
and obtaining a climate change prediction result by using a neural network algorithm on government affair data.
Further, the optimizing module is specifically configured to:
based on data monitoring and diagnosis of user behaviors, acquiring abnormal behavior data of the user;
acquiring abnormal log data based on log data monitoring and diagnosis;
based on the data monitoring and diagnosis of the database, the access condition of the database is analyzed, and the abnormal condition is obtained.
According to a third aspect of an embodiment of the present invention, there is provided an electronic device including:
one or more processors;
a memory;
one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs configured to perform the method of any of the above.
According to a fourth aspect of embodiments of the present invention, there is provided a computer storage medium having one or more program instructions embodied therein for performing the method of any of the above by an artificial intelligence government affairs data review system.
The invention has the following advantages:
according to the artificial intelligence government affair data review method and system, multi-source government affair data are collected, preprocessing is carried out on the obtained multi-source government affair data, feature extraction, data mining and data fusion and analysis are carried out on the government affair data obtained through preprocessing, and a first government affair data result is obtained; based on a plurality of pre-constructed government data review models, carrying out government data review model matching in combination with a specific business scene and review requirements, inputting the first government data result into the government data review model obtained by matching, outputting a first government data review result, and generating a government decision report based on the first government review result; and continuously acquiring government affair data according to the implementation of government affair decision, monitoring and diagnosing, analyzing and acquiring a second government affair data result by using the monitoring and diagnosing result of the government affair data, early warning abnormal conditions, optimizing a corresponding government affair data review model according to the second government affair data result, and adjusting the implemented government affair decision. The method and the system can be applied to the implementation process of government decision and administrative service, the management in government institutions and the like, and compared with the traditional artificial government affair data review system, the novel artificial intelligence government affair data review system has the advantages of higher data processing speed, higher accuracy, lower cost and the like.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It will be apparent to those of ordinary skill in the art that the drawings in the following description are exemplary only and that other implementations can be obtained from the extensions of the drawings provided without inventive effort.
FIG. 1 is a flowchart of an artificial intelligence government affair data review method provided in embodiment 1 of the present invention;
fig. 2 is a functional architecture diagram of an artificial intelligence government affair data review system provided in embodiment 2 of the present invention;
fig. 3 is a schematic structural diagram of an electronic device according to embodiment 3 of the present invention.
Detailed Description
Other advantages and advantages of the present invention will become apparent to those skilled in the art from the following detailed description, which, by way of illustration, is to be read in connection with certain specific embodiments, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1
As shown in fig. 1, this embodiment proposes an artificial intelligence government affair data review method, which includes:
s100, acquiring multi-source government affair data, preprocessing the acquired multi-source government affair data, and performing feature extraction, data mining, data fusion and analysis on the government affair data obtained by preprocessing to acquire a first government affair data result.
In this embodiment, the data is acquired through a crawler, or acquired through an API or an interface, or the like; the source of the data includes government databases or databases of third parties; the content of the data includes government affair data, policy files, policy interpretation, government statistics, and the like.
The method is characterized in that effective information is extracted from multi-source data and integrated into a single system to realize data analysis, algorithms adopted include cluster analysis, statistical analysis and pattern recognition, means adopted include machine learning, data mining and the like, and finally, the processed results are visually displayed to generate a policy report implemented by government departments.
For example, the government affair data review system can integrate economic indexes and public opinion issued by government departments, extract effective information from the economic indexes and the public opinion, and perform data fusion by utilizing algorithms such as data mining, cluster analysis and the like so as to evaluate economic policies. Finally, the system will visually present the results of the processing and generate a decision report for the government to implement the policy.
In this embodiment, the feature data that may be extracted includes: social trends, geographical locations, economic developments, government actions, climate change, and the like. For example, social trends can be explored using time series analysis, government actions can be detected using text analysis, economic development can be predicted using decision tree algorithms, people in different geographic locations can be grouped using clustering algorithms, climate change can be predicted using neural network algorithms, and so forth.
And S200, based on a plurality of pre-constructed government data review models, carrying out government data review model matching in combination with a specific business scene and a review requirement, inputting the first government data result into the government data review model obtained by matching, outputting a first government data review result, and generating a government decision report based on the first government data review result.
The government affair data review model specifically comprises a rule model, a machine learning model and a deep learning model.
A rule model is a model that is reviewed based on certain rules, which may review government data according to a set of rules, and give results. In addition, the rule model can be constructed from existing empirical knowledge and can be reviewed more quickly.
The machine learning model is a model for performing review based on a machine learning algorithm, and is characterized in that the machine learning model can learn from a large amount of historical data, thereby improving the review result and performing the review according to new government affair data.
The deep learning model is a model for performing review based on a deep neural network model, and is characterized in that the deep learning model can learn from a large amount of historical data so as to improve the review result and can perform review according to new government data.
In this embodiment, the constructed government affair data review model specifically includes:
a SWOT analysis model for identifying and evaluating advantages, disadvantages, opportunities, and threats of policy items;
the decision tree model is used for helping a decision maker to determine an optimal path according to different conditions;
a Monte Carlo simulation model for selecting the best results for the policy in order to maximize its utility;
a fuzzy logic model for identifying and evaluating uncertainties between policy variables; a predictive model for predicting the impact and possible outcome of the policy;
microscopic and macroscopic models for estimating the economic impact of policies;
and the machine learning or deep learning model is used for outputting government affair data classification results.
The process of constructing the machine learning or deep learning model is to collect a large amount of government affair data, analyze the government affair data by using a data mining algorithm to extract useful characteristics, train the model by using the machine learning algorithm or the deep learning algorithm, and finally obtain the model capable of evaluating the government affair data.
For example, an automatic text classification model based on deep learning is adopted, the model performs word embedding and pooling on the extracted features, converts the text into a multidimensional vector, and classifies the multidimensional vector through a neural network. The result of the model output is a review result, such as whether funds are available for funding, whether review is available, etc.
Matching of the business scenario and the review model needs to be considered according to the actual business scenario, for example:
1. public safety: for example, the monitoring system may employ a deep learning model to analyze video images of the camera to detect potential security threats.
2. Education: for example, a clustering model may be used to evaluate student performance, thereby providing more targeted teaching support.
3. Medical treatment: for example, machine learning models may be used to diagnose pathology of a patient, and comparisons may be made between different pathologies in order to more accurately assess the condition of the patient.
4. And (3) energy management: for example, deep learning models may be used to analyze energy usage in order to more accurately determine efficient utilization of energy.
And S300, continuously collecting government affair data and carrying out monitoring and diagnosis according to the implementation of government affair decisions, analyzing and obtaining a second government affair data result by using the monitoring and diagnosis results of the government affair data, carrying out early warning on abnormal conditions, optimizing a corresponding government affair data review model according to the second government affair data result, and adjusting the implemented government affair decisions.
The multi-source data monitoring and diagnosis specifically comprises:
1. data monitoring and diagnostics based on user behavior: by monitoring the user behavior, abnormal behavior can be quickly found, so that the aim of safety monitoring is fulfilled.
2. Log-based data monitoring and diagnostics: the log is important information generated in the running process of the system, and can record the behavior of a user, so that safety monitoring is realized.
3. Database-based data monitoring and diagnostics: the data stored in the database may provide useful information and the access to the database may be analyzed to discover anomalies.
In the embodiment, reliable data guidance can be provided for government affair review through monitoring and diagnosis of government affair data. For example, data monitoring and diagnostics based on user behavior may help governments better understand the service experience of the masses and thereby optimize public services more accurately. The log-based data monitoring and diagnosis can help governments predict and prevent problems that may occur in advance, thereby improving the accuracy of government reviews. In addition, the data monitoring and diagnosis based on the database can help the government to better analyze the running condition of the government, improve the government review flow better and further improve the government review efficiency.
The government affair data review method in the embodiment has the following characteristics:
1. the identification, calibration and integrity detection of the data resources are realized: the integrity and the authenticity of the data resources can be ensured through the identification, the calibration and the integrity detection of the data set, so that the integrity and the accuracy of government affair data are ensured.
2. And (3) constructing a data model: by constructing the data model, a proper data model can be designed according to the characteristics of government affair data, so that the effective review of the government affair data is realized.
3. The visualization of government affair data is realized: through data visualization, government affair data can be more intuitively checked, so that data analysis and review are more convenient.
According to the artificial intelligence government affair data review method and system, multi-source government affair data are collected, preprocessing is carried out on the obtained multi-source government affair data, feature extraction, data mining and data fusion and analysis are carried out on the government affair data obtained through preprocessing, and a first government affair data result is obtained; based on a plurality of pre-constructed government data review models, carrying out government data review model matching in combination with a specific business scene and review requirements, inputting the first government data result into the government data review model obtained by matching, outputting a first government data review result, and generating a government decision report based on the first government review result; and continuously acquiring government affair data according to the implementation of government affair decision, monitoring and diagnosing, analyzing and acquiring a second government affair data result by using the monitoring and diagnosing result of the government affair data, early warning abnormal conditions, optimizing a corresponding government affair data review model according to the second government affair data result, and adjusting the implemented government affair decision. The method and the system can be applied to the implementation process of government decision and administrative service, the management in government institutions and the like, and compared with the traditional artificial government affair data review system, the novel artificial intelligence government affair data review system has the advantages of higher data processing speed, higher accuracy, lower cost and the like.
Example 2
Corresponding to the above embodiment 1, this embodiment proposes an artificial intelligence government affair data review system, which includes:
the data processing module is used for acquiring multi-source government affair data, preprocessing the acquired multi-source government affair data, extracting features of the government affair data obtained through preprocessing, mining data, fusing and analyzing the data, and acquiring a first government affair data result;
the evaluation module is used for carrying out the matching of the government affair data evaluation models based on a plurality of government affair data evaluation models which are built in advance and combining a specific business scene and evaluation requirements, inputting the first government affair data result into the government affair data evaluation model obtained by matching, outputting a first government affair data evaluation result, and generating a government affair decision report based on the first government affair evaluation result;
and the optimization module is used for continuously acquiring government affair data, monitoring and diagnosing according to the implementation of government affair decisions, analyzing and acquiring a second government affair data result by using the monitoring and diagnosing results of the government affair data, early warning abnormal conditions, optimizing a corresponding government affair data review model according to the second government affair data result and adjusting the implemented government affair decisions.
Further, the data processing module is specifically configured to:
acquiring social trend information by using time sequence analysis on government affair data;
acquiring government action detection results by using text analysis on government service data;
analyzing and obtaining economic development condition prediction results by using a decision tree algorithm to government affair data;
grouping people or things in different geographic positions by using clustering algorithm analysis on government affair data;
and obtaining a climate change prediction result by using a neural network algorithm on government affair data.
Further, the optimizing module is specifically configured to:
based on data monitoring and diagnosis of user behaviors, acquiring abnormal behavior data of the user;
acquiring abnormal log data based on log data monitoring and diagnosis;
based on the data monitoring and diagnosis of the database, the access condition of the database is analyzed, and the abnormal condition is obtained.
The architecture of the artificial intelligent government affair data review system provided by the embodiment of the invention is shown in figure 2, and can support the manual review of various materials and the quality inspection review of the review result besides configuring the intelligent review service.
The functions executed by each component in the artificial intelligence government affair data review system provided in the embodiment of the invention are described in detail in the above embodiment 1, so that redundant description is omitted here.
Example 3
An embodiment of the present invention proposes an electronic device, and fig. 3 is a schematic entity structure diagram of the electronic device provided by the present invention, where the electronic device may include: processor 1010, memory 1020, input/output interface 1030, communication interface 1040, and communication bus 1050, wherein processor 1010, memory 1020, input/output interface 1030, and communication interface 1040 communicate with each other via communication bus 1050. One or more programs are stored in the memory 1020 and configured to be executed by the one or more processors 1010, the one or more programs configured to perform the NLP recognition and knowledge base construction method described in the above embodiments.
Example 4
In correspondence with the above-described embodiments, this embodiment proposes a computer storage medium containing one or more program instructions for executing the method as in embodiment 1 by an artificial intelligence government affair data review system.
While the invention has been described in detail in the foregoing general description and specific examples, it will be apparent to those skilled in the art that modifications and improvements can be made thereto. Accordingly, such modifications or improvements may be made without departing from the spirit of the invention and are intended to be within the scope of the invention as claimed.
Claims (10)
1. An artificial intelligence government affair data review method, which is characterized by comprising the following steps:
collecting multi-source government affair data, preprocessing the obtained multi-source government affair data, extracting features, mining data, fusing and analyzing the government affair data obtained by preprocessing, and obtaining a first government affair data result;
based on a plurality of pre-constructed government data review models, carrying out government data review model matching in combination with a specific business scene and review requirements, inputting the first government data result into the government data review model obtained by matching, outputting a first government data review result, and generating a government decision report based on the first government review result;
and continuously acquiring government affair data according to the implementation of government affair decision, monitoring and diagnosing, analyzing and acquiring a second government affair data result by using the monitoring and diagnosing result of the government affair data, early warning abnormal conditions, optimizing a corresponding government affair data review model according to the second government affair data result, and adjusting the implemented government affair decision.
2. The artificial intelligence government affair data review method according to claim 1, wherein the collecting of the multi-source government affair data comprises the following steps:
the government affair data is acquired through a crawler or through a website API or interface;
the source of the government data comprises a government department database or a database of a third party;
the content of the government affair data comprises government affair data, policy files, policy reading and government statistical data.
3. The artificial intelligence government affair data review method according to claim 1, wherein the feature extraction, data mining and data fusion and analysis are performed on the government affair data obtained through preprocessing, and the method specifically comprises the following steps:
the extracted characteristic data comprise social trends, geographic locations, economic development predictions, government behaviors and climate changes;
acquiring social trend information by using time sequence analysis on government affair data;
acquiring government action detection results by using text analysis on government service data;
analyzing and obtaining economic development condition prediction results by using a decision tree algorithm to government affair data;
grouping people or things in different geographic positions by using clustering algorithm analysis on government affair data;
and obtaining a climate change prediction result by using a neural network algorithm on government affair data.
4. The artificial intelligence government affair data review method according to claim 1, wherein the plurality of government affair data review models specifically include:
a SWOT analysis model for identifying and evaluating advantages, disadvantages, opportunities, and threats of policy items;
the decision tree model is used for helping a decision maker to determine an optimal path according to different conditions;
a Monte Carlo simulation model for selecting the best results for the policy in order to maximize its utility;
a fuzzy logic model for identifying and evaluating uncertainties between policy variables; a predictive model for predicting the impact and possible outcome of the policy;
microscopic and macroscopic models for estimating the economic impact of policies;
and the machine learning or deep learning model is used for outputting government affair data classification results.
5. The artificial intelligence government affair data review method according to claim 1, wherein the method is characterized by continuously collecting government affair data and monitoring and diagnosing according to the implementation of government affair decision, and specifically comprises the following steps:
based on data monitoring and diagnosis of user behaviors, acquiring abnormal behavior data of the user;
acquiring abnormal log data based on log data monitoring and diagnosis;
based on the data monitoring and diagnosis of the database, the access condition of the database is analyzed, and the abnormal condition is obtained.
6. An artificial intelligence government affair data review system, the system comprising:
the data processing module is used for acquiring multi-source government affair data, preprocessing the acquired multi-source government affair data, extracting features of the government affair data obtained through preprocessing, mining data, fusing and analyzing the data, and acquiring a first government affair data result;
the evaluation module is used for carrying out the matching of the government affair data evaluation models based on a plurality of government affair data evaluation models which are built in advance and combining a specific business scene and evaluation requirements, inputting the first government affair data result into the government affair data evaluation model obtained by matching, outputting a first government affair data evaluation result, and generating a government affair decision report based on the first government affair evaluation result;
and the optimization module is used for continuously acquiring government affair data, monitoring and diagnosing according to the implementation of government affair decisions, analyzing and acquiring a second government affair data result by using the monitoring and diagnosing results of the government affair data, early warning abnormal conditions, optimizing a corresponding government affair data review model according to the second government affair data result and adjusting the implemented government affair decisions.
7. The artificial intelligence government affairs data review system according to claim 6, wherein the data processing module is specifically configured to:
acquiring social trend information by using time sequence analysis on government affair data;
acquiring government action detection results by using text analysis on government service data;
analyzing and obtaining economic development condition prediction results by using a decision tree algorithm to government affair data;
grouping people or things in different geographic positions by using clustering algorithm analysis on government affair data;
and obtaining a climate change prediction result by using a neural network algorithm on government affair data.
8. The artificial intelligence government affairs data review system according to claim 6, wherein the optimizing module is specifically configured to:
based on data monitoring and diagnosis of user behaviors, acquiring abnormal behavior data of the user;
acquiring abnormal log data based on log data monitoring and diagnosis;
based on the data monitoring and diagnosis of the database, the access condition of the database is analyzed, and the abnormal condition is obtained.
9. An electronic device, the electronic device comprising:
one or more processors;
a memory;
one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs configured to perform the method of any of claims 1-6.
10. A computer storage medium having one or more program instructions embodied therein for performing the method of any of claims 1-6 by an artificial intelligence government data review system.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310271494.6A CN116307765A (en) | 2023-03-17 | 2023-03-17 | Artificial intelligence government affair data review method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310271494.6A CN116307765A (en) | 2023-03-17 | 2023-03-17 | Artificial intelligence government affair data review method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116307765A true CN116307765A (en) | 2023-06-23 |
Family
ID=86788357
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310271494.6A Pending CN116307765A (en) | 2023-03-17 | 2023-03-17 | Artificial intelligence government affair data review method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116307765A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117436729A (en) * | 2023-12-21 | 2024-01-23 | 山东中翰软件有限公司 | Government system based data management and data analysis method |
-
2023
- 2023-03-17 CN CN202310271494.6A patent/CN116307765A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117436729A (en) * | 2023-12-21 | 2024-01-23 | 山东中翰软件有限公司 | Government system based data management and data analysis method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Mehdiyev et al. | Explainable artificial intelligence for process mining: A general overview and application of a novel local explanation approach for predictive process monitoring | |
| García et al. | An insight into the experimental design for credit risk and corporate bankruptcy prediction systems | |
| EP3522078A1 (en) | Explainable artificial intelligence | |
| CN114048436A (en) | Construction method and construction device for forecasting enterprise financial data model | |
| Li et al. | Explain graph neural networks to understand weighted graph features in node classification | |
| CN116307765A (en) | Artificial intelligence government affair data review method and system | |
| Kaiser et al. | Attack hypotheses generation based on threat intelligence knowledge graph | |
| Al-Rawahnaa et al. | Data mining for Education Sector, a proposed concept | |
| Stracuzzi et al. | Quantifying Uncertainty to Improve Decision Making in Machine Learning. | |
| Mostofi et al. | Construction safety predictions with multi-head attention graph and sparse accident networks | |
| Saranya et al. | ENHANCED PREDICTION OF STUDENT DROPOUTS USING FUZZY INFERENCE SYSTEM AND LOGISTIC REGRESSION. | |
| Chinu et al. | Explainable AI: to reveal the logic of black-box models | |
| Bhattacharjee et al. | PRIVEE: A visual analytic workflow for proactive privacy risk inspection of open data | |
| CN114612239A (en) | Stock public opinion monitoring and wind control system based on algorithm, big data and artificial intelligence | |
| Gupta et al. | Android smells detection using ML algorithms with static code metrics | |
| Muramudalige | Automating investigative pattern detection using machine learning & graph pattern matching techniques | |
| Manengadan et al. | Crime Data Analysis, Visualization and Prediction Using LSTM | |
| Sabharwal et al. | Empirical analysis of metrics for object oriented multidimensional model of data warehouse using unsupervised machine learning techniques | |
| Hammarström | Towards explainable decision-making strategies of deep convolutional neural networks: An exploration into explainable ai and potential applications within cancer detection | |
| Sharanya et al. | Predicting Abnormal User Behaviour Patterns in Social Media Platforms based on Process Mining | |
| Sivapriya et al. | FMDB Transactions on Sustainable Computer Letters | |
| Lopez Torres | SafeCity: Predictive Crime Analysis Integrating Social Media Big Data and Official Reports | |
| Rajan et al. | Leveraging Machine Learning for More Efficient Real-Time Data Analysis | |
| Du Toit et al. | Shapley values as an interpretability technique in credit scoring | |
| CN117436729A (en) | Government system based data management and data analysis method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |