筑床机专利价值数据

通过收集筑床机领域法律状态、技术主题分类、简单同族专利申请数量、技术主题分类等数据，形成了主要包括全球专利数据库中与筑床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筑床机，找出筑床机方向专利数据，并根据自有算法对专利数据进行了评价和分类，可用于了解筑床机专利数据变化情况，有助于了解筑床机知识产权工作成果；通过对各企业/个人筑床机专利数据的对比，可了解各企业/个人的技术创新能力、创新水平差异；了解筑床机的技术发展趋势，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：全球专利数据库中筑床机相关发明专利、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，检索出有关于筑床机的专利，指标层向下分准则层，包括：技术价值：被引用专利数量；经济价值：授权日；法律价值：权利要求数、文献页数；战略价值：发明人数量、简单同族专利申请数量；市场价值：技术主题分类、专利类型。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 legal status, technical subject classification, number of simple family patent applications, etc. in the bed-forming machine field. It primarily covers invention patents and utility model patents related to bed-forming machines sourced from the global patent database. Specifically, the keyword "bed-forming machine" is adopted to screen out patent data targeting the bed-forming machine domain from initial retrieval results. Then, self-developed algorithms are applied to evaluate and classify the screened patent data.

This dataset supports multiple application scenarios: firstly, it enables tracking of changes in bed-forming machine patent data, helping to understand the outcomes of intellectual property work in this field; secondly, by comparing patent data of bed-forming machines across different enterprises or individuals, differences in technological innovation capabilities and innovation levels among these entities can be identified; thirdly, grasping the technological development trends of bed-forming machines helps enterprises avoid redundant R&D and prevent their developed technologies from infringing others' intellectual property rights.

1. Data Source: Data on invention patents and utility model patents related to bed-forming machines from the global patent database.

2. Data Collection: The target layer of this dataset is patent technical relevance. The indicator layer divides the patent technical relevance index system into five value dimensions: market, technology, law, strategy and economy. When retrieving patents related to bed-forming machines, the indicator layer is further decomposed into the criterion layer, which includes:
- Technical value: Number of cited patents
- Economic value: Grant date
- Legal value: Number of claims, number of document pages
- Strategic value: Number of inventors, number of simple family patent applications
- Market value: Technical subject classification, patent type

3. Data Analysis: This dataset adopts the Analytic Hierarchy Process (AHP) combined with both quantitative and qualitative research methods. The technical relevance is divided into three levels from high to low: Category A (high relevance), Category B (general relevance), and Category C (low relevance). The comprehensive scoring method is used for classification:
- Category A: Strategic value ≥ 50 points, Economic value ≥ 20 points, Market value ≥ 50 points, Legal value ≥ 60 points, Technical value ≥ 30 points
- Category B: Strategic value ranges from 40 to 50 points (excluding 50), Economic value ≥ 20 points, Market value ≥ 30 points, Legal value ≥ 70 points, Technical value ≥ 30 points
- Category C: All other cases

4. Data Application: Provide decision-making basis for R&D and priority reference for technology avoidance for technical personnel in the bed-forming machine field.