碘海醇高价值专利数据

数据包中主要包括了全球专利数据库中有关碘海醇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评价和分类，可用于横向、纵向了解碘海醇专利数据变化情况，有助于了解碘海醇知识产权工作成果；通过对各企业/个人碘海醇专利数据的对比，可了解各企业/个人的技术创新能力、创新水平差异；了解碘海醇的技术发展趋势，有助于企业避免重复研发，避免企业开发的技术侵犯他人的知识产权。本数据基于熵权法的 AHP 模型，目标层为专利价值，指标层将专利价值指标体系分为市场、技术、法律、战略、经济五大价值维度，指标层向下分准则层，包括：技术价值：IPC分类数量、被引用专利数量、授权年限；经济价值：剩余年数、综合第三方估值、质押次数；法律价值：权利要求数、文献页数、非专利引用文献数量；战略价值：发明人数量、简单同族成员数量、5年内被引次数；市场价值：技术主题分类数、专利类型、是否战略新兴产业。根据维度和指标建立五个维度的原始矩阵，利用算法随机爬取专利评价准则的对应数据，求得相应权重。由熵权法求得的权重用于各个价值的计算，五个维度单项价值均等，五类价值之和定义为高价值专利综合价值，利用IFS函数对专利进行价值判定，用于区分超高价值专利、高价值专利、一般价值专利和无价值专利，为本领域技术人员提供研发决策依据和技术规避作优先参考。

The data package mainly includes invention patents and utility model patents related to Iohexol from the global patent database. The proprietary algorithm is used to evaluate and classify the patent data, which enables users to analyze the changes of Iohexol-related patent data both cross-sectionally and longitudinally, and helps to understand the achievements of Iohexol-related intellectual property work. By comparing the Iohexol-related patent data of various enterprises and individuals, users can learn about the differences in technological innovation capabilities and innovation levels among them. Understanding the technological development trends of Iohexol can help enterprises avoid redundant R&D and the risk of infringing others' intellectual property rights with their developed technologies. This dataset is based on the integrated AHP-entropy weight model. The target layer of the model is patent value. The indicator layer divides the patent value index system into five value dimensions: market, technology, law, strategy and economy, with a criterion layer under the indicator layer. The specific indicators are as follows: Technology Value includes number of IPC classifications, number of cited patents and years of patent authorization; Economic Value includes remaining patent term, comprehensive third-party valuation and number of pledges; Legal Value includes number of claims, number of document pages and number of non-patent literature citations; Strategic Value includes number of inventors, number of simple patent family members and number of citations received within 5 years; Market Value includes number of technical topic categories, patent type and whether it belongs to strategic emerging industries. An original five-dimensional matrix is established based on the above dimensions and indicators. The corresponding data of patent evaluation criteria are randomly crawled via algorithms to calculate the corresponding weights. The weights obtained by the entropy weight method are used to calculate the value of each dimension. The five dimensions are equally weighted, and the sum of the five values is defined as the comprehensive value of high-value patents. The IFS function is used to judge the value of patents, so as to distinguish ultra-high-value patents, high-value patents, general-value patents and valueless patents. This dataset provides R&D decision-making basis and priority references for technology avoidance for technical personnel in this field.