智能驾驶行业高价值专利数据

智能驾驶行业高价值专利数据库中主要包括了全球专利数据库中有智能驾驶行业的发明专利和实用新型专利数据，并根据自有算法对专利数据进行了检索、评价打分，有助于了解智能驾驶行业知识产权申请情况及地域布局；通过对各企业智能驾驶行业专利数据的对比，可了解各企业的技术创新能力；了解智能驾驶行业技术发展趋势及核心技术，有助于企业避免重复研发及侵犯他人的知识产权。数据基于AHP层次法，采用定量与定性相结合，从专利价值度法出发，指标层将专利价值指标体系分为技术、法律、经济3项一级指标，一级指标层向下为二级指标，包括技术价值指标：独立权利要求数量、主权项字数、剩余有效期(年)、同族专利数、引证其它专利数、被其他专利引证数、发明人投入人数、涉及领域数；法律价值指标：专利类型、文献页数、被无效请求次数；经济价值指标：转让次数、许可次数、质押融资次数、专利奖得分、海关备案得分；根据一级、二级指标建立3个维度的矩阵，通过专利接口数据获取专利评价对应的数据指标，采用1-9分标度法（最低为1分，最高为9分），求得相应的指标权重，用权重技术各个指标的分值，所有指标分值的和即为专利得分，根据分值的区间段对专利进行划分，80-100为高价值专利、60-80位重要专利、60分以下为一般专利，为智能驾驶行业企业研发人员提供技术参考及指引，为公司提供研发决策指导。

The High-Value Patent Database for the Autonomous Driving Industry mainly includes invention patents and utility model patents related to the autonomous driving industry from global patent databases. Retrieval and evaluation scoring have been conducted on the patent data using proprietary algorithms, which helps gain insights into the intellectual property (IP) filing status and geographic layout of the autonomous driving industry. By comparing the patent data of enterprises in the autonomous driving industry, one can assess the technological innovation capabilities of each enterprise. Understanding the technological development trends and core technologies of the autonomous driving industry helps enterprises avoid redundant R&D and intellectual property infringement. The dataset is built based on the Analytic Hierarchy Process (AHP), adopting a combination of quantitative and qualitative methods starting from the patent valuation methodology. The patent value index system is divided into three first-level indicators: technological, legal, and economic value. The first-level indicators are further broken down into second-level indicators, including: - Technological value indicators: number of independent claims, word count of the independent claim, remaining valid period (years), number of patent family members, number of cited external patents, number of times cited by other patents, number of contributing inventors, number of involved technical fields; - Legal value indicators: patent type, number of document pages, number of received invalidation requests; - Economic value indicators: number of transfers, number of licenses, number of pledge financing instances, patent award score, customs recordation score. A three-dimensional matrix is established based on the first-level and second-level indicators. Data indicators corresponding to patent evaluation are obtained through patent interface data. The 1-9 point scaling method (minimum 1 point, maximum 9 points) is adopted to calculate the corresponding indicator weights, and the scores of each indicator are multiplied by their respective weights. The sum of all indicator scores constitutes the patent score. Patents are categorized according to their score ranges: 80-100 is high-value patents, 60-80 is important patents, and below 60 is general patents. This database provides technical references and guidance for R&D personnel of enterprises in the autonomous driving industry, and offers R&D decision-making support for companies.

搜集汇总

数据集介绍

特点

该数据集包含529条智能驾驶行业的高价值专利数据，涵盖专利号、名称、类型等19个字段，通过技术、法律、经济三个维度评分划分专利价值等级，适用于了解行业技术趋势和企业创新能力。