17 results about "Contract type" patented technology

A kind of natural language processing-based new clause position confirmation method and system, natural language processing-based new clause position confirmation method includes: obtaining first contract content, identifying contract type, display corresponding risk point and prompt new clause, according to new clause, the text content of first contract and contract type, obtain the contract chapter theme to which new clause belongs, obtain the text content of the contract chapter to which new clause belongs, and obtain updated clause order by clause order model, then according to chapter clause format, increase the clause number of new clause, increase clause number to corresponding position, while adjusting the clause number of context accordingly, output second contract content after new contract clause.This application obtains new clause by analyzing contract content, and after user confirmation, automatically analyzes the chapter and order in chapter to which new clause belongs, and automatically increases new clause to corresponding chapter and label.

The invention relates to a resource scheduling method and device, access network equipment and a storage medium. The method comprises: according to a resource allocation proportion of each contract type service, determining a standardized data transmission amount of each contract type service, the contract type service comprising at least one NGBR bearer type service; according to the standardized data sending amount of a target contract type service and the standardized data sending amount of each contract type service, a target priority corresponding to the target contract type service is determined, and the target contract type service is one of the contract type services; and performing resource scheduling on the target contract type service based on the target priority. According to the method, the priority of the target contract type service can be dynamically determined, and the purpose of differential resources of different user levels is achieved according to the contract type.

The invention discloses a department double-track system performance quantitative evaluation method and system under a dynamic balance perspective, and the method comprises the steps: carrying out the classification management of contract projects, endowing each class of projects with a preference coefficient, and endowing each class of projects with a specific project contribution coefficient; performing equivalent operation on non-contract projects, dividing the non-contract projects into a plurality of categories, setting an equivalent contract amount and correcting the equivalent contract amount; quantizing department investment indexes including the number of employees, operation expenditure, fixed asset depreciation and office area; constructing a multi-input multi-output input-output system, and obtaining a total quantitative evaluation score of contract projects and a total quantitative evaluation score of non-contract projects; performing relative efficiency evaluation on each department by using a BCC model in a DEA method to obtain a technical benefit value and a scale benefit value; and obtaining a comprehensive efficiency value, and dividing the performance evaluation grade of each department. According to the method, the relative efficiency of each department can be objectively measured, the comprehensive performance of the department is reflected, and meanwhile, input-output adjustment suggestions are provided for the department with insufficient relative efficiency.

The invention discloses a contract element extraction method and device, electronic equipment and a storage medium, and relates to the technical field of information processing, and the method comprises the steps: carrying out the preprocessing of an engineering contract, and obtaining a structured contract text; identifying a contract type based on the structured contract text, and generating at least one element extraction task according to the contract type; the element extraction task is executed, multi-stage cascade extraction of contract elements is carried out in the execution process of the element extraction task, and in the multi-stage cascade extraction process, the result of the previous stage is used as the input of the subsequent stage; and integrating the contract elements extracted by the at least one element extraction task to obtain contract element data corresponding to the engineering contract. According to the invention, the accuracy of contract element extraction can be improved.

This invention discloses an intelligent contract review method and system based on artificial intelligence, relating to the fields of computer and artificial intelligence technologies. The method includes: receiving and parsing contract documents to obtain structured text data and contract type; automatically extracting multiple key clauses based on the contract type; performing compliance review and difference comparison on the key clauses to generate intermediate review results containing risk points and modification suggestions; dynamically analyzing the clause content in the intermediate review results, determining the responsible party for review according to preset rules, and automatically generating and assigning independent review sub-tasks to corresponding review terminals; completing the review process based on feedback from the review terminals, and structurally storing the results in a contract knowledge base. The system includes modules for document parsing, intelligent analysis, task assignment, and knowledge base management. This invention achieves automation, intelligence, and collaboration in contract review, significantly improving review efficiency, risk identification accuracy, and process traceability, and promoting the accumulation and reuse of enterprise contract knowledge.

This invention relates to a contract review method and system. The method includes: performing multi-channel retrieval of the contract to be reviewed based on a pre-built contract knowledge base to obtain contract retrieval results, re-ranking them, and generating enhanced context; matching contract prompt word templates according to contract type, and adjusting the contract prompt word templates based on historical feedback information to generate optimized prompt words; inputting the contract to be reviewed, enhanced context, and optimized prompt words into an optimal large language model to generate contract review opinions, performing structured parsing, and outputting structured review results; and adjusting at least one of the strategy parameters used in multi-channel retrieval and re-ranking, as well as the weight and content of the prompt word template library, based on user feedback on the review results, and triggering incremental updates to the contract knowledge base. Using this invention can improve contract retrieval accuracy, ranking effect, and prompt word adaptability, ensuring continuous optimization of review capabilities and improving the accuracy and efficiency of contract review.

The invention relates to a training set optimization method for a contract fulfillment risk analysis model, belongs to the technical field of training set optimization, and solves the problems of low model training efficiency caused by high dimension of existing original features and severely reduced model interpretability caused by dimension reduction of the existing features. The method comprises the steps of obtaining an initial training data set of a contract fulfillment risk analysis model; performing preliminary screening on the initial training data set to obtain a basic training data set; obtaining feature data of contract risk interaction features based on opposite party credit rating features, contract type features and contract amount features in the basic training data set; obtaining a statistical feature set and feature data corresponding to each feature based on the contract fulfillment time sequence data; and adding the contract risk interaction features, the corresponding feature data, the statistical feature set and the feature data corresponding to each feature into a basic training data set to obtain an optimized training data set of the contract fulfillment risk analysis model.

The invention discloses a bulk and general cargo contract performance prediction method and system based on tallying data and a prediction model, and relates to the technical field of bulk and general cargo port management, and the method comprises the steps: collecting the tallying data of bulk and general cargos in the port arriving and unloading process in real time, and forming the accumulation of the cargo number in a contract period; constructing a prediction model based on the historical transportation volume, the tallying data, the shipping fluctuation and the predicted port arrival data, and predicting the final cargo volume in the same period according to the prediction model to obtain a predicted cumulative tallying volume; establishing different contract models according to different protocol contract types and contract modeling rules, wherein the protocol contract types comprise guaranteed contracts and ladder contracts; calculating the settlement amount of the contract based on the predicted cumulative tallying amount and a contract modeling rule; adopting a Monte Carlo method to calculate the standard reaching probability of the contract based on the predicted cumulative tallying quantity and the contract model; according to the invention, dynamic monitoring, quantitative analysis and prediction evaluation of the contract execution condition are realized.

The invention provides an electronic contract generation method and device, electronic equipment and a computer program product, belongs to the field of data storage, and aims at solving the problems that an existing method is low in automation degree, insufficient in accuracy, lack of intelligence and the like. The method comprises the following steps: acquiring text content of an offline business contract; semantic understanding is conducted on the text content through a pre-trained language model, target information in the text content is extracted, and the target information comprises a contract type; matching a corresponding electronic contract template according to the contract type; and generating an electronic contract based on the target information and the electronic contract template.

The embodiment of the application discloses a revenue confirmation method and a computing device, and relates to the technical field of enterprise financial management. The method comprises the following steps: acquiring first information of a target sales contract, the target sales contract being a sales contract for at least one product, and the first information comprising a product type, a transaction type and a contract type of the at least one product. Based on the first information, a target analysis rule matched with the first information is determined from a plurality of analysis rules, the analysis rule being used for defining revenue confirmation content of the sales contract. Based on the target analysis rule, an analysis conclusion of the target sales contract is determined, the analysis conclusion of the target sales contract being used for indicating the revenue confirmation content corresponding to the at least one product in the target sales contract. Based on the analysis conclusion of the target sales contract, revenue confirmation is performed. In this way, the automation processing efficiency and the accuracy of the revenue confirmation are improved, the adaptability of the revenue confirmation process of the enterprise is enhanced, and the work flow and the manpower input demand of the enterprise are simplified.

This invention discloses a method, apparatus, and related equipment for dynamic real-time cost occupancy and reserve calculation. The method includes: responding to the initiation of a target business, automatically calculating the monthly cost occupancy amount of the target business under the corresponding contract type based on the total amount and start and end dates of the target business; automatically triggering a locking or releasing operation on the monthly cost occupancy amount based on the approval status of the target business, and synchronously updating the incurred costs; wherein the incurred costs are actual expenditure costs; and dynamically calculating the monthly planned reserve and annual planned reserve based on the incurred costs and the pending costs distinguished according to the contract type of the target business, wherein the contract type includes at least contractual contracts and non-contractual contracts, and the pending costs are planned expenditure costs.

This application provides a contract content verification method, system, electronic device, and storage medium, relating to the field of data processing, which can improve the accuracy of verification results obtained by current contract content verification technologies. The method is applied to an electronic device, which stores a first knowledge graph corresponding to at least one contract type in at least one domain. The first knowledge graph is used to characterize the relationship between the contract content, source basis, and risk level corresponding to a contract type. The method includes: the electronic device acquiring a target contract; constructing a second knowledge graph corresponding to the target contract based on the target first knowledge graph matching the contract type; the second knowledge graph being used to characterize the relationship between the target contract content, source basis, and risk level; and the electronic device acquiring the verification result of the target contract based on the second knowledge graph, the verification result including at least the content risk item of the target contract.

The invention provides a differentiated technology contract risk hedging clause generation method and system, the system comprises a plurality of user terminals and a generation server, and the generation server comprises a type determination part which determines the contract type of a contract draft received from the user terminals; the feature extraction part is used for extracting risk-related features of the contract draft according to the contract type; the clause forming part is used for generating risk hedging clauses as preliminary hedging clauses according to contract types and risk related characteristics; the quantization correction part is used for carrying out quantization correction on the preliminary hedging clauses to form clauses to be embedded; the clause embedding part is used for embedding to-be-embedded clauses into the contract draft to form a to-be-confirmed contract; and a contract output unit for outputting the contract to be confirmed. The risk hedging clauses are generated based on the specific contract type of the contract draft and the corresponding risk related features, different types of specific risks can be reflected, differentiated hedging clauses are generated, and then the contract quality is improved.

This application relates to an automatic intelligent classification and identification method, system, device, and medium for contract archive resources. The method includes: constructing a contract domain knowledge graph containing legal concepts, business terms, and contract type entities based on historical contract archive texts and publicly available legal provisions; preprocessing the contract archives to be classified to obtain word sequences; encoding the word sequences into contextual semantic vector sequences using a pre-trained language model; linking the sequences with the knowledge graph and aggregating multi-hop neighbor information of relevant entities to generate a knowledge-enhanced text feature vector sequence; simultaneously extracting the document structure features of the contract documents to obtain document structure vectors; finally, aggregating the knowledge-enhanced text features and combining them with the structure vectors, and calculating the probability of the document belonging to each classification label using a multi-label classifier to obtain the classification result. This method deeply integrates domain knowledge and document structure, effectively improving the accuracy and domain adaptability of contract archive classification.

A contract management and control method comprises the steps of converting a paper contract into an electronic contract and performing character recognition, so that contract information can be stored and processed in a digital form, and accessibility and searchability of contract data are improved. And classifying different types of contracts into corresponding data sets through text analysis and keyword set construction. Through the attention mechanism and keyword set labeling, the relationship and dependence between keywords in the contract can be deeply understood, and the contract content can be comprehensively understood and analyzed. Potential topics are extracted from the keyword matrix by using potential semantic analysis to help to identify the generality of different contract types. According to the method, the category vectors and the subject vectors of the contracts are integrated to construct feature vectors of the contracts, then type division is carried out according to the combined feature vectors and based on a clustering algorithm, each cluster represents a specific contract type, and therefore the purpose of fine classification management is achieved.

The invention discloses an oil and gas well measure benefit evaluation method based on contract types and related equipment. According to the contract type of the to-be-evaluated oil and gas well project, determining a static gain evaluation model corresponding to the contract type, and obtaining the benefit measurement and calculation data of the oil and gas well with measures and the benefit measurement and calculation data of the oil and gas well without measures corresponding to the contract type; inputting the benefit measurement and calculation data of the oil and gas well with measures and the benefit measurement and calculation data of the oil and gas well without measures of the oil and gas well project to be evaluated into the static gain evaluation model to obtain static incremental data; and inputting the static incremental data and the measure data of the oil and gas well measures into a pre-constructed dynamic benefit evaluation model to obtain oil and gas well project benefits at specified time nodes in a plurality of time periods in the future. The dynamic benefit evaluation model considers factors changing along with time, and oil and gas well project benefits change along with change parameters and are closer to real oil and gas well project benefits.