互联网食品销售系统高价值专利数据

互联网食品销售系统高价值专利数据库中主要包括了全球专利数据库中有互联网食品销售系统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，有助于了解互联网食品销售系统知识产权申请情况及地域布局；通过对各企业互联网食品销售系统专利数据的对比，可了解各企业的技术创新能力；了解互联网食品销售系统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。本数据基于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、专利剩余年限、同族专利数、引证其它专利数、被其他专利引证数、申请人类型得分、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，根据专利名称和专利号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，为互联网食品销售系统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。以上算法中提到的数据结果均在数据结构中体现。

High-Value Patent Database for Internet Food Sales Systems comprises primarily invention patents and utility model patents related to internet food sales systems sourced from global patent databases. Proprietary algorithms are employed to retrieve, evaluate and score these patent data, which enables insight into the intellectual property (IP) filing status and geographical layout of internet food sales systems. By comparing the patent data of enterprises in this sector, the technological innovation capabilities of individual enterprises can be assessed. Additionally, understanding the development trends and core technologies of internet food sales systems helps enterprises avoid redundant R&D and infringement of third-party IP rights.

This dataset is built upon the Analytic Hierarchy Process (AHP), combining quantitative and qualitative methodologies rooted in the patent value assessment framework. The indicator layer categorizes the patent value indicator system into three first-level dimensions: technological, legal, and economic value. Each first-level dimension is further decomposed into second-level indicators:
1. Technological value indicators: number of independent claims, word count of the independent claim, remaining patent term, number of patent family members, number of cited patents, number of citations by other patents, applicant type score, number of contributing inventors, and number of involved technical fields;
2. Legal value indicators: patent type, number of document pages, and number of received invalidation requests;
3. Economic value indicators: number of transfers, number of licenses, number of pledge financing transactions, patent award score, and customs recordation score.

A three-dimensional matrix is constructed based on the first and second-level indicators. Corresponding data indicators for patent evaluation are acquired via patent interface data using patent titles and patent numbers as identifiers. The 1-9 point scaling method (with 1 as the minimum score and 9 as the maximum) is utilized to calculate the weight of each indicator. The score of each indicator is multiplied by its respective weight, and the sum of all weighted indicator scores constitutes the total patent score. Patents are classified into three categories based on their total score ranges: 80-100 are high-value patents, 60-80 are important patents, and below 60 are general patents. This database provides technical references and guidance for R&D personnel of enterprises engaged in internet food sales systems, and supports R&D decision-making for relevant companies. All data results derived from the aforementioned algorithms are fully reflected in the dataset's data structure.

搜集汇总

数据集介绍

特点

该数据集包含96条互联网食品销售系统的高价值专利数据，涵盖了专利的详细信息及其价值评估。数据通过AHP层次法进行评分，分为技术、法律、经济三个维度，适用于企业研发决策和技术创新分析。