Patent Value Assessment Framework

Patent management system with tools to help analyze, organize, and search patent portfolios. The system allows quick and relevant patent analysis using features like claim mapping, concept organization, similarity indexing, and expanded search results. It provides tools to efficiently manage and analyze patent portfolios by leveraging automated techniques like mining, mapping, and indexing to extract insights from patent claims and texts. The system also enables expanded search results, concept organization, and claim mapping to help with quick and relevant patent analysis.

Source

Computerized system for evaluating patent claim inputs and authorized contributions to a project. The system tracks inputs, outputs, prompts, queries, responses, and collaborations. It analyzes and evaluates metrics like creativity, novelty, utility, reliability, success, value, rights, and IP. The system uses AI to persistently monitor, parse, and analyze inputs/outputs/prompts for determining metrics. It provides data, scores, graphs, and statistics for measurably improving SWOT and ROI.

Source

When frequency-modulated continuous-wave (FMCW) laser radar (Ladar) is employed for three-dimensional imaging, the echo signal susceptible to modulation nonlinearity and platform vibration due short wavelength. These effects cause main-lobe widening, side-lobe elevation, positional shift, which degrades distance detection accuracy. To solve these problems, this paper proposes a compensation method combining multiple synchrosqueezing transform (MSST), equal-phase interval resampling, high-order ambiguity function (HAF). Firstly, variational mode decomposition (VMD) applied optical prism eliminate low-frequency noise harmonic peaks. MSST used extract timefrequency curve of prism. The in transmitted estimated by two-step integration. An internal calibration containing constructed at higher sampling rate resample actual an interval. Then, HAF compensates residual phase error after resampling. Finally, symmetrical triangle wave remove constant-speed vibration. Verifying data, proposed can enhance main lobe suppress side about 1.5 dB strong reflection target signal. Natural-target peaks... Read More

Source

Frequency tuning nonlinearities in semiconductor lasers constitute a critical factor that degrades measurement precision and spectral resolution frequency-modulated continuous-wave (FMCW) LiDAR systems. This study systematically investigates the influence of nonlinear beat signal phase distortions on peak broadening develops phase-fitting-based pre-correction algorithm. To further enhance system performance, an electro-optic phase-locked loop architecture combined with non-uniform discrete Fourier transform processing is implemented, establishing comprehensive solution for nonlinearity suppression. Experimental validation demonstrates sub-18 m standard deviation absolute distance measurements at 19 m target range. integrated approach represents significant advancement coherent frequency-sweep detection methodologies, offering considerable potential high-precision photonic radar applications.

Source

AI-driven asset analysis and personalized value assessment system that overcomes limitations of traditional asset search and valuation tools. The system uses AI techniques like computer vision, natural language processing, and specialized neural networks to analyze multi-modal asset data like images, videos, text, and audio. This provides a deeper understanding of asset features and more accurate value predictions tailored to individual user profiles. The system also incorporates environmental, contextual, and personalization factors to optimize asset discovery, selection, and identification.

Source

An intellectual property landscaping platform that uses machine learning to analyze and visualize patent portfolios. The platform clusters related patents based on technical aspects using user-seeded searches. It generates refined clusters of IP assets using seed searches in varying areas of interest like target fields, products, or competitors. The platform also calculates metrics like coverage, opportunity, and exposure for each cluster. The clusters are visually represented in an interactive map to provide an efficient and accurate way to analyze IP landscapes with large portfolios.

Source

Frequency-modulated continuous-wave (FMCW) laser ranging typically applies an interferometer and linear frequency-modulated (LFM) signals to measure the distance, in which precision resolution are limited by phase noise of bandwidth LFM signals, respectively. This work proposes FMCW method that overcomes limits bandwidth, beat frequency is estimated via time-domain maximum likelihood estimation. Using this method, super-resolved can be achieved within coherence length. It also break noise, enabling beyond An experiment conducted. a 5 GHz 0.8 cm length, enhanced 5.1 times compared traditional LiDARS. Moreover, 10 4.5 times, The performance feasible even though acquisition time reduced 20 s. In addition, three-dimensional imaging static dynamic targets implemented show performance. proposed enables long-range, fast using low-cost laser, helpful enhance interferometry.

Source

Artificial intelligence (AI) system for analyzing patent documents to provide insights into technology development trends, competitive intelligence, and patent analysis. The system uses AI techniques like semantic analysis and relationship analysis to automatically identify the most critical patents and documents in a collection, determine what they reveal, and provide summaries and visualizations. It consolidates metadata like citations, litigation, and expiration dates to provide statistics like citation indices and influence factors. The AI also generates alerts, flags, and indicators based on patent quality, relevance, and expiration. The system aims to automate tasks like competitive analysis, prior art search, patentability assessment, and freedom to operate analysis using AI instead of manual review.

Source

Ranging and velocimetry constitute fundamental operational capabilities in Light Detection (LiDAR) systems. However, the presence of Doppler shift during moving targets imposes severe interference on ranging accuracy continuous-wave (CW) LiDAR In order to overcome these inherent constraints conventional Amplitude-Modulated Continuous-Wave (AMCW) systems, we propose a dual-frequency source amplitude modulation (DFAM) scheme that enables concurrent laser velocimetry. This method employs two components: low-frequency signal for quantification throughout velocity measurement, along with higher-frequency facilitates phase-difference measurements between transmitted reflected signals. Subsequently, obtained from is then employed compensate this phase difference, allowing precise distance calculation compensated phase. The experimental results demonstrate not only achieves highly precision consistently within 5 mm/s but also maintains comparable static under identical conditions. All findings validate feasibility proposed approach. We believe provides new perspective systems realize simulta... Read More

Source

Ranging and velocimetry constitute fundamental operational capabilities in Light Detection (LiDAR) systems. However, the presence of Doppler shift during moving targets imposes severe interference on ranging accuracy continuous-wave (CW) LiDAR In order to overcome these inherent constraints conventional Amplitude-Modulated Continuous-Wave (AMCW) systems, we propose a dual-frequency source amplitude modulation (DFAM) scheme that enables concurrent laser velocimetry. This method employs two components: low-frequency signal for quantification throughout velocity measurement, along with higher-frequency facilitates phase-difference measurements between transmitted reflected signals. Subsequently, obtained from is then employed compensate this phase difference, allowing precise distance calculation compensated phase. The experimental results demonstrate not only achieves highly precision consistently within 5 mm/s but also maintains comparable static under identical conditions. All findings validate feasibility proposed approach. We believe provides new perspective systems realize simulta... Read More

Source

A platform for analyzing intellectual property portfolios of entities by identifying similarities between portfolios and clustering IP assets based on technical aspects. The platform allows users to seed searches based on technical fields, competitor portfolios, etc. to find IP assets similar to their own. It then clusters the assets at varying levels of granularity and generates visual representations of the clusters. This helps users efficiently analyze and compare portfolios, identify gaps and saturation, and assess exposure.

Source

Improving search engine results by using machine learning techniques to generate semantically related search queries from document metadata. The system identifies semantically similar search queries for a document by projecting the document vector and search query vector into a low-dimensional semantic space. If the distance between the vectors is below a threshold, the system generates a semantically similar search query for the document that includes at least one lexical token different from the original document. This query is associated with the document and added to its index to improve semantic matching during future searches.

Source

Automated analysis of patent claims to help evaluate relative breadth, identify corresponding products, and find related patents. The system analyzes claims using techniques like stemming and normalization to extract features like unique word counts. It generates claim profiles based on these features and compares them to determine relative breadth. It also searches for products and related patents based on identified elements in the claims.

Source

Patent management system that provides quick claim scope determination and relevancy assessment for patent portfolios. The system uses automated tools to search, map, analyze, and chart patent claims to help quickly understand and compare patent scope. It enables quick claim relevance assessment by generating expanded sets of search results, mapping claims to concepts, highlighting terms, and displaying charts. This allows rapid and accurate assessment of patent relevance and distinction compared to prior art.

Source

A patent value evaluation method that combines traditional methods and machine learning to provide more accurate and reliable evaluation results for patents. It captures patent information and potential citation relationships through network data retrieval, determines stage-based weights, uses association rule mining, self-learning, and feedback to classify and value patents based on correlation matrices. This provides more comprehensive, dynamic, and real-time patent value evaluation.

Source

Improving the accuracy of determining patent value and generating technical routes using a comprehensive evaluation method. The method involves assessing patent value based on factors beyond just the patent document itself. It considers the patent applicant's ability, inventor info, inherent attributes, and awards. Coefficients are used to weigh these factors. This provides a more accurate patent value compared to just the patent document. The technical route generation uses patent application dates to improve accuracy compared to just searching.

Source

Method for evaluating the value of a patent based on claim analysis. The method involves extracting components from the patent claims, finding documents with matching configurations, calculating frequencies of prior and subsequent documents, and scoring the patent based on weights for these frequencies. The weights can favor subsequent documents over prior ones. The scoring also considers vector distances between components, component frequencies, technical field concentration, applicant type, and trend.

Source

Patent value assessment method, system and device using a quantitative model to determine the economic value of a patent. The method involves collecting patent data, building a database, and establishing a patent value evaluation model using machine learning techniques. The model quantitatively calculates the market value, legal value, and technical value of a patent based on indicators like practicality, versatility, advancement, and awards.

Source

A comprehensive method for evaluating patent value that considers multiple factors like legal, technical, and market dimensions. The method involves a multi-step process to quantitatively evaluate indicators using a Delphi technique. It involves experts making accurate judgments on indicators, converting language levels to fuzzy numbers, averaging the fuzzy numbers to construct indexes, and calculating patent value based on the indexes. This provides a more objective and accurate patent value evaluation compared to subjective methods like AHP.

Source

Objective and rapid patent value evaluation system that can avoid subjective judgments by using a classification number-industry comparison table. The system receives patent files and queries the table using the patent classification number to find the industry category. It then retrieves the output value and total number of valid patents for that industry. By comparing the patent's output value to the industry average, it objectively evaluates the patent's value.

Source