19 results about "Patent analysis" patented technology

The invention discloses a technology development analysis method and system based on a patent big language model, and relates to the field of big data analysis. The problems that an existing artificial intelligence patent analysis method is difficult to accurately analyze a technical structure in a patent text, cannot describe a technical hierarchical relationship, is difficult to eliminate technical semantic diversity, cannot systematically analyze a technical evolution process and the like are solved. And the network structure characteristics and the technology node importance are analyzed, and the evolution characteristics of the technology system in different stages, the key technology nodes and the change trend of the technology community structure can be identified, so that technical support is provided for artificial intelligence technology development situation research and judgment and technology layout decision. The method is suitable for a technical analysis scene of million-level patent data.

The invention relates to the technical field of patent early warning, and discloses an artificial intelligence-driven patent risk early warning system, and the system comprises a data collection module which is used for collecting patent data from a patent data source, and carrying out the preprocessing and storage of the data; the patent analysis module is used for carrying out information analysis on the patent texts based on natural language processing and machine learning technologies so as to obtain various data of patents and carrying out classification and similarity analysis on the patents; and the risk assessment module is used for assessing risk analysis of a target patent in combination with various data of the patent, analyzing the legal status of the patent, and assessing historical litigation disputes or potential litigation risks of the patent. According to the invention, through cooperative operation of the data acquisition module, the patent analysis module, the risk assessment module, the risk early warning module and the feedback optimization module, advanced natural language processing, machine learning and other technologies are utilized, and the effects of comprehensive and accurate assessment and early warning of patent risks and continuous optimization are achieved.

The invention provides a patent named entity recognition method in the fields of carbon capture, utilization and storage based on an ERNIE-BiLSTM-FNNAtention-CRF model, and relates to the fields of natural language processing and patent information processing. A processed patent corpus CCUSdataset is pre-trained in an ERNIE layer, an input text is vectorized, context features are acquired in combination with BiLSTM, weighted average processing is performed on an operation vector of a BiLSTM layer by adopting FNNAttention, long text semantic information is enhanced, meanwhile, the problem that the same patent entity is inconsistent in annotation in different statements is avoided, and the semantic information of the long text is enhanced. And finally, sequence decoding labeling is carried out through a conditional random field CRF layer, and a prediction label with the highest score is output. According to the method, the problems of more special text content, unclear entity boundary, many professional vocabularies, polysemy and the like of patent texts are solved, word vectors with rich semantics can be obtained, semantic correlation between current information and context information is enhanced, potential semantic features between the texts are mined, a good recognition effect is achieved, and the method is suitable for popularization and application. And support is provided for patent value evaluation, patent analysis and retrieval and the like.

The present invention discloses a method for constructing a patent technology classification system in the field of air traffic management, and belongs to the field of patent analysis and mining technology. The method comprises step 1, mining key technology classification vocabulary in the field of air traffic management; step 2, calculating the measurement value of the technology classification vocabulary; step 3, constructing an initial technology classification system for patents in the field of air traffic management; step 4, constructing an expert set, and the experts in the expert set evaluate the technology classification vocabulary to obtain a first evaluation matrix; step 5, reducing the expert set and calculating a third evaluation matrix; step 6, calculating the importance and consistency of the technology classification vocabulary; step 7, reducing the technology classification vocabulary set to obtain the final patent technology classification system. The method makes full use of the domain corpus and the knowledge accumulation of experts, and reduces the bias of expert decision-making, so that the patent technology classification system finally constructed is more representative.

The application discloses a patent theme graph generation method and system based on deep semantic hierarchical clustering, comprising: obtaining a patent literature set PT to be generated into a patent theme graph; using a patent deep semantic representation model to perform semantic coding on each patent literature in the patent literature set PT, and obtaining a semantic representation vector matrix V={v1,...,v N}; inputting the semantic representation vector matrix V into a hierarchical clustering algorithm to obtain a hierarchical clustering tree structure corresponding to the patent literature set PT; generating a corresponding theme description for each non-leaf node on the hierarchical clustering tree structure; and combining the generated theme description and the hierarchical clustering tree structure into a patent theme graph with an upper and lower hierarchical structure. The patent theme graph generation method and system can help users quickly mine upper and lower hierarchical relationships of patent literatures at a theme level, meet the analysis needs of users for large-scale patent information, and improve the efficiency of patent analysis of users.

The invention discloses a medicine patent information analysis method and device based on a large model, equipment and a medium, and relates to the technical field of artificial intelligence, and the method comprises the steps: inputting a medicine patent uploaded by a current user side into a fine-tuned large model, and employing preset prompt information to analyze key information in the current medicine patent, and obtaining target key information; determining a disease field of the current medical patent according to indications in the target key information, and obtaining the highest research and development state of the current medical patent at home and abroad from a related website according to the disease field and target spots in the target key information; determining the level of a target based on the highest research and development state at home and abroad, and judging whether an application company of a current medical patent belongs to a concerned company or not to obtain a judgment result; and judging whether the target has research and development value or not according to the judgment result and the target level. The efficiency of medicine patent information analysis is greatly improved, the labor cost and time cost of medicine patent analysis are saved, and waste of human resources is avoided.

The application provides a key information analysis system for technical patent data, and relates to the technical field of patent analysis, comprising a collection and storage layer, an analysis layer and an application layer, wherein the collection and storage layer comprises a collection module and a storage module, the analysis layer comprises a text conversion and extraction module, a keyword benchmark library, an extraction module, a specific gravity value analysis module, a summary module and a classification module; the collection module is used for collecting technical patent data in all formats, and the storage module is used for storing the technical patent data; after collecting the technical patent data, the application takes the keyword benchmark library as a benchmark, extracts relevant and similar keywords and their contexts in the patent text data, summarizes the extracted keywords and their contexts into texts representing the fields, advantages and technical means of the patent technology, and induces them into short data reports, so that a person can quickly connect the key information of each patent from the short data reports, save understanding time and facilitate screening.

This application relates to the field of patent analysis, and in particular to a computer-aided patent document clustering method. The method includes: receiving multiple sets of clustering seeds, each set containing a cluster name and at least one corresponding clustering attractor; using a processing unit to determine whether the key feature information of each patent document contains a certain clustering attractor (step A); executing step A whenever additional sets of clustering seeds are received, until the number of patent documents whose key feature information does not contain any clustering attractor is less than a certain threshold; associating patent documents whose key feature information contains a certain clustering attractor with the cluster name corresponding to that attractor, thereby obtaining the cluster name of each patent document. This application improves the accuracy and efficiency of patent clustering, and is a practical, accurate, and efficient patent clustering method that can help users obtain highly accurate clustering results with high efficiency.

The invention belongs to the technical field of patent analysis, and provides a technology life cycle prediction method and system based on patent data, and the method comprises the steps: obtaining the feature data of patents in a patent database; inputting the feature data into a plurality of trained prediction models to obtain a plurality of first prediction results of the technical life cycle; fusing the plurality of first prediction results through a voting mechanism to obtain a second prediction result of the technical life cycle; according to the method, accurate prediction can be provided in each stage of a technology life cycle based on patent data by combining quantitative analysis of characteristic data of patents and a machine learning algorithm, the dependency of a qualitative analysis method on expert experience is overcome, and the limitation of a quantitative analysis method in emerging technology prediction is overcome.

This application discloses a method, device, equipment, and medium for analyzing pharmaceutical patent information based on a large model, which relates to the field of artificial intelligence technology, including: inputting the pharmaceutical patent uploaded by the current user end into the fine-tuned large model to parse the key information in the current pharmaceutical patent using preset prompt information to obtain target key information; determining the disease field of the current pharmaceutical patent based on the indication in the target key information, and obtaining the highest domestic and foreign R&D status of the current pharmaceutical patent from relevant websites based on the disease field and the target in the target key information; determining the level of the target based on the highest domestic and foreign R&D status, and judging whether the applicant company of the current pharmaceutical patent is a company of key concern to obtain a judgment result; judging whether the target has R&D value based on the judgment result and the target level. This application greatly improves the efficiency of pharmaceutical patent information analysis, saves the manpower and time costs of pharmaceutical patent analysis, and avoids waste of human resources.

The invention relates to the technical field of electric digital data processing, in particular to a patent analysis method and retrieval system based on distinguishing technical means traceability. The patent analysis method based on distinguishing technical means traceability comprises the steps that 1, a technical file recording a public technical scheme close to a to-be-analyzed technical scheme is obtained through retrieval, or patent analysis reports of other technical schemes, close to the to-be-analyzed technical scheme, in the field are selected to serve as comparison files; 2, comparing the to-be-analyzed technical scheme with a comparison file, and identifying and distinguishing technical means; 3, performing traceability analysis on the different technical means; and identifying the patent infringement risk of the to-be-analyzed technical scheme. The method has the beneficial effects that the workload is small, the acceptance check is convenient, the accuracy of retrieval is not interfered by an unsubstantially examined or invalid patent protection range, the coverage range is large, and the retrieval can be accepted.

Systems and methods for fine-tuning a machine learning model for use in patent analytics and infringement system are disclosed herein. The method involves providing, in a memory, a litigation dataset comprising a plurality of historical patent litigation records, each patent litigation record comprising at least one patent claim, and a litigation outcome corresponding to each of the at least one patent claim; receiving, at a processor in communication with the memory, a product / service content item associated with a candidate patent litigation record in the plurality of historical patent litigation records; updating, at the processor, the candidate patent litigation record based on the product / service content item; and generating, at the processor, a vector database based on the litigation dataset, the vector database used to fine-tune a machine learning model. Systems and methods for identifying products and services relevant to a patent claim and for ranking results are also described.

The embodiment of the invention relates to an agent analysis system for performing patent infringement analysis on a molecular structure. The system comprises a task scheduling module, a molecular analysis module, a patent analysis agent, a structure matching agent, an infringement analysis module, a fact checking module, a Markush structure library and a substituent database, the task scheduling module sequentially schedules the subtask processing processes of the molecular analysis module, the patent analysis agent and the structure matching agent, performs fact verification on each subtask output by using the fact verification module, and schedules the infringement analysis module to generate an infringement analysis report according to the output of the structure matching agent; and the structure matching agent is also used for carrying out dynamic fine adjustment on the built-in structure matching model according to the Markush structure library and the substituent database. The analysis precision can be improved, and the analysis quality can be improved.

The invention relates to the technical field of patent analysis and drug research and development decision support, in particular to an LLM-based medical patent infringement risk multi-dimensional early warning method, which comprises the following steps of: analyzing a user attention level, configuring a risk dimension weight in combination with a decision scene, obtaining medical patent technical characteristics and a target product, and establishing a medical patent infringement risk model; the method comprises the following steps: analyzing claims by utilizing BERT to generate a multi-dimensional sub-structure map, quantifying technical characteristics by combining atomic stability and an attention matrix, evaluating avoidance feasibility by calculating a candidate site bond energy disturbance value and distribution density, fusing the technical characteristics with multi-source intelligence, constructing a multi-dimensional risk index set, and establishing a multi-dimensional risk index map; according to the multi-dimensional risk early warning method, the BERT is utilized to construct a substructure map, the contribution weight is quantified in combination with the atomic stability, the key energy is calculated to evaluate the avoidance feasibility, the molecular fingerprint is fused with multi-source data mapping, the weighted aggregation is executed according to the scene, the subjective deviation is eliminated, and the microscopic difference is mined. And accurate quantitative early warning of the medical patent infringement risk is realized.

The invention relates to the technical field of patent management, in particular to a patent case management method, system and device and a storage medium, and the method comprises the steps: obtaining the information of patent cases declared by an enterprise, and constructing a patent management library; classifying the patent cases based on the patent case information into finished cases and unfinished cases; for the case completion, setting annual fee payment reminding and recording fee payment information; for an unfinished case, dynamically obtaining an official file, setting a reply prompt and storing a reply record; and carrying out patent analysis and patent competitiveness evaluation regularly based on the patent management library. The patent case management efficiency can be effectively improved.

A system and method for automated establishment of a nucleic acid sequence database, the system comprising: a text exploration module configured to search literatures related to a target species and a retrieval condition from a literature database, the target species and the retrieval condition must appear in the related literatures at the same time; comparing a plurality of specific nucleic acid sequences appearing in the searched related literature with the nucleic acid sequence of the target species to determine that the plurality of specific nucleic acid sequences or complementary sequences thereof exist in the target species; according to the plurality of specific nucleic acid sequences or the complementary sequences thereof, obtaining a plurality of genes where the plurality of specific nucleic acid sequences or the complementary sequences thereof are located; and calculating statistical data according to the plurality of genes. The invention also provides another system and a method for automatically establishing the nucleic acid sequence database. The system comprises a patent analysis module.

The invention provides a technical blank space calibration and layout subject identification method based on suspected missed labeling patents, belongs to the technical field of patents, and solves the problems of technical blank misjudgment and the like caused by term diversity and indexing limitation in an existing patent analysis method. The method comprises the following steps: constructing a patent retrieval expression according to target technology description, performing retrieval, and constructing a large-field patent set; extracting high-purity seed samples from the large-field patent set, and constructing a high-purity seed set; modeling is carried out on the high-purity seed set from different technical perspectives, and a multi-dimensional behavior portrait is constructed; evaluating the to-be-evaluated patent based on the multi-dimensional behavior portrait, and generating a suspected label missing patent set; on the basis of the large-field patent set and the suspected missed labeling patent set, the technical blank area is calibrated, and a true blank and a false blank are distinguished; and identifying an underestimated layout main body and an emerging technical direction based on the large-field patent set and the suspected missed labeling patent set.

The present invention discloses a multi-dimensional analysis method for technical documents based on semantic understanding. The Sentence-BERT model is used to perform text vectorization processing on the text data to generate a dense vector representation of the text; UMAP is used for vector dimensionality reduction to remove redundant features; HDBSCAN is used for unsupervised clustering analysis to generate clustering results; the TF-ICF method is used to extract topic words from the clustering results; and multi-dimensional analysis is performed on the clustering results. Compared with the prior art, the present invention provides a comprehensive and efficient patent analysis tool through an advanced semantic understanding-based patent clustering method, thereby achieving a deeper interpretation and analysis of technical documents while ensuring cost-effectiveness.

The present application relates to a patent analysis method, system, device and storage medium based on artificial intelligence. The method inputs patent text into a patent feature extraction model to obtain technical fields, technical features and technical problems; obtains the number of patent applications corresponding to the technical field based on a first scoring model, builds and determines the life cycle based on a quantity curve, and outputs a first scoring value; obtains the number of related patents of associated binary groups generated by technical features and technical problems based on a second scoring model, and outputs a second scoring value; the second scoring model obtains patent comparative documents based on associated triples generated by the technical field, technical features and technical problems; the third scoring model performs stability analysis on the patent text based on the patent comparative document text, and outputs a third scoring value; performs weighted fusion processing on the obtained scoring values, and outputs the analysis results of the patent to be analyzed; compared with the prior art, the technical solution of the present application can improve the accuracy and efficiency of patent analysis.