门把手专利价值数据

根据自定规则对门把手专利数据进行检索分析，了解门把手专利情况，有助于门把手成果转化，也有利于了解门把手技术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。1.数据来源：全球专利数据库中门把手相关发明专利、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，二类加分项目：权利要求条数和文献页数数量，检索出有关于门把手的专利，指标层向下分准则层，包括：技术价值：被引用专利数量、授权日期；经济价值：剩余年数（实用新型的日期为授权日期往后增加10年，发明的日期为授权日期往后增加20年）；法律价值：权利要求数、文献页数；战略价值：简单同族专利申请数量；市场价值：技术领域。3.数据分析：本数据基于AHP层次法，采用定量与定性相结合，将技术关联性综合平均系数（P）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。技术关联性综合平均系数（P）=( 市场价值、技术价值、法律价值、战略价值、经济价值)/5+（文献页数/3）+（权利要求数/2）+(被引用专利数量*10)，一个被引用专利数量为10分，采用比较集合法：P≤20的为C,20＜P≤40为B,P＞40为A，最后四舍五入取整。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

Retrieving and analyzing doorknob patent data per custom rules to gain insights into the doorknob patent landscape facilitates the commercialization of doorknob-related research achievements, helps grasp the technological development trends and core technologies of doorknobs, and enables enterprises to avoid redundant R&D and intellectual property infringement.
1. Data Source: Relevant invention patents and utility model patents related to doorknobs from the global patent database.
2. Data Collection: The target layer of this dataset is patent technology relevance. The indicator layer divides the patent technology relevance index system into five value dimensions: market, technology, law, strategy and economy, plus two secondary bonus items: the number of claims and the number of document pages. Patents related to doorknobs were retrieved. The indicator layer is further divided into the criterion layer, including:
- Technological value: number of cited patents, authorization date;
- Economic value: remaining valid years (for utility model patents, the remaining years are 10 years after the authorization date; for invention patents, the remaining years are 20 years after the authorization date);
- Legal value: number of claims, number of document pages;
- Strategic value: number of simple patent family applications;
- Market value: technical field.
3. Data Analysis: This dataset adopts the Analytic Hierarchy Process (AHP), combining quantitative and qualitative research methods. The comprehensive average coefficient of technical relevance (P) is categorized into three levels (A, B, C) in descending order, where A represents high relevance, B represents general relevance, and C represents low relevance.
The calculation formula of the comprehensive average coefficient of technical relevance (P) is:
P = (Market Value + Technological Value + Legal Value + Strategic Value + Economic Value)/5 + (Number of Document Pages / 3) + (Number of Claims / 2) + (Number of Cited Patents * 10), where each cited patent counts as 10 points.
Using the comparative set classification method: patents with P ≤ 20 are categorized as C, 20 < P ≤ 40 as B, and P > 40 as A, with the final result rounded to an integer.
4. Data Application: This dataset provides priority references for R&D decision-making and technology avoidance for technical professionals in this field.