验布机专利数据

通过收集验布机领域专利申请人、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验布机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验布机，找出验布机方向专利数据，并根据自有算法对专利数据进行了评价和分类，可用于了解验布机专利数据变化情况，有助于了解验布机知识产权工作成果；通过对各企业/个人验布机专利数据的对比，可了解各企业/个人的技术创新能力、创新水平差异；了解验布机的技术发展趋势，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：全球专利数据库中验布机相关发明专利、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，检索出有关于验布机的专利，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；经济价值：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、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 developed by collecting multi-dimensional data including patent applicants, legal statuses, technical subject classifications, and the number of simple patent family members in the fabric inspection machine domain. It primarily covers invention patents and utility model patents related to fabric inspection machines sourced from the global patent database. The dataset is filtered using the keyword "fabric inspection machine" to isolate relevant patent records, followed by evaluation and classification via a proprietary algorithm.

This dataset enables researchers and practitioners to track changes in fabric inspection machine-related patent data and assess the outcomes of intellectual property (IP) work in this field. Comparative analysis of patent data across different enterprises or individual inventors facilitates the evaluation of their technological innovation capabilities and disparities in innovation levels. Additionally, it supports the identification of technological development trends for fabric inspection machines, helping enterprises avoid redundant research and development (R&D) activities and prevent infringement of third-party intellectual property rights.

1. Data Source: Invention patents and utility model patents related to fabric inspection machines retrieved from the global patent database.
2. Data Collection: The target layer of this dataset is patent technology relevance. The indicator layer categorizes the patent technology relevance index system into five value dimensions: market, technology, legal, strategic, and economic. Patents related to fabric inspection machines were retrieved, with the indicator layer further decomposed into criterion layer indicators as follows:
- Technological value: Number of IPC classifications, number of cited patents
- Economic value: Number of pledge incidents
- Legal value: Number of claims, document page count
- Strategic value: Number of inventors, number of simple patent family members
- Market value: Number of technical subject categories, whether the patent belongs to strategic emerging industries
3. Data Analysis: This dataset applies the Analytic Hierarchy Process (AHP) method, integrating both quantitative and qualitative analysis approaches. The technical relevance of patents is graded into three tiers from high to low: Grade A (high relevance), Grade B (general relevance), and Grade C (relatively low relevance). The composite scoring criteria for grading are specified as:
- Grade A: Strategic value ≥ 50 points, Economic value ≥ 20 points, Market value ≥ 50 points, Legal value ≥ 60 points, Technological value ≥ 30 points
- Grade B: 40 ≤ Strategic value < 50 points, Economic value ≥ 20 points, Market value ≥ 30 points, Legal value ≥ 70 points, Technological value ≥ 30 points
- Grade C: All remaining cases
4. Data Application: Provide R&D decision-making references and priority guidance for technology avoidance for technical personnel in the fabric inspection machine field.

搜集汇总

数据集介绍

特点

该数据集包含397条验布机相关专利数据，涵盖发明专利和实用新型专利，每年更新一次，用于评估技术创新能力和技术发展趋势。