数据融合系统专利数据

通过收集数据融合系统领域专利申请人、法律状态、技术主题分类、简单同族成员数量等数据，形成了主要包括全球专利数据库中与数据融合系统相关的发明专利和实用新型专利数据，在结果中筛选关键词数据融合系统，找出数据融合系统方向专利数据，并根据自有算法对专利数据进行了评价和分类，可用于了解数据融合系统专利数据变化情况，有助于了解数据融合系统知识产权工作成果；通过对各企业/个人数据融合系统专利数据的对比，可了解各企业/个人的技术创新能力、创新水平差异；了解数据融合系统的技术发展趋势，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。1数据来源：全球专利数据库中数据融合系统相关发明专利、实用新型专利数据。2数据采集：本数据目标层为专利技术相关性，指标层将专利技术相关性指标体系分为市场、技术、法律、战略、经济五大价值维度，检索出有关于数据融合系统的专利，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、质押次数；法律价值：权利要求数、文献页数；战略价值：发明人数量、简单同族成员数量；市场价值：技术主题分类数、专利类型、是否战略新兴产业。3数据分析：本数据基于AHP层次法，采用定量与定性相结合，将技术关联性按从高到低分为（A、B、C），A为高关联性、B为一般关联性、C为较低关联性。采用综合分值法：战略价值≥50分及以上、经济价值≥20分及以上、市场价值≥50分及以上、法律价值≥60分及以上、技术价值≥30分及以上为A，战略价值40-50分（不含50分）、经济价值≥20分及以上、市场价值≥30分及以上、法律价值≥70分及以上、技术价值≥30分及以上为B，其余为C。4数据应用：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。

This dataset is constructed by collecting data including patent applicants, legal statuses, technical subject classifications, and the number of simple patent family members in the field of data fusion systems. It mainly covers invention patents and utility model patents related to data fusion systems from the global patent database. First, the keyword "data fusion system" is used to screen out patent data in the data fusion system domain. Then, self-developed algorithms are applied to evaluate and classify these patent data. This dataset can be used to track the changes of patent data related to data fusion systems, and help understand the achievements of intellectual property (IP) work in this field. By comparing the patent data of different enterprises or individuals, one can analyze the differences in their technological innovation capabilities and innovation levels. Additionally, it can help grasp the technological development trends of data fusion systems, enabling enterprises to avoid redundant R&D and intellectual property infringement caused by their developed technologies.
1. Data Source: Invention patents and utility model patents related to data fusion systems from the global patent database.
2. Data Collection: Taking the patent technology relevance as the target layer, the indicator system for patent technology relevance is divided into five value dimensions: market, technology, law, strategy, and economy at the indicator layer. Patents related to data fusion systems are retrieved. The indicator layer is further decomposed into the criterion layer, with specific indicators as follows:
- Technological value: Number of IPC classifications, number of cited patents, authorized years
- Economic value: Remaining valid years, number of pledge times
- Legal value: Number of claims, number of document pages
- Strategic value: Number of inventors, number of simple patent family members
- Market value: Number of technical subject classifications, patent type, whether it belongs to strategic emerging industries
3. Data Analysis: This dataset uses the Analytic Hierarchy Process (AHP), combining quantitative and qualitative methods. The technological relevance is divided into three levels from high to low: (A, B, C), where A represents high relevance, B represents general relevance, and C represents relatively low relevance. The comprehensive scoring method is adopted:
- Level A: Strategic value ≥ 50 points, Economic value ≥ 20 points, Market value ≥ 50 points, Legal value ≥ 60 points, Technological value ≥ 30 points
- Level B: Strategic value ranges from 40 to 50 points (excluding 50), Economic value ≥ 20 points, Market value ≥ 30 points, Legal value ≥ 70 points, Technological value ≥ 30 points
- Level C: All other cases
4. Data Application: Provide R&D decision-making references and priority guidance for technology avoidance for technical personnel in this field.

搜集汇总

数据集介绍

特点

该数据集包含264条全球数据融合系统相关专利数据，涵盖多维评价指标，适用于技术创新分析和知识产权管理。