自主信息技术“升级”

2008年1月9日，国家知识产权局发布的2007年专利统计数据显示，2007年国家知识产权局共受理专利申请694153件，比2006年同期增长21．1％；授予专利权351782件，比2006年同期增长31．3％。专利申请总量持续快速增长，国内发明专利授权增速高于国外。其中信息产业领域相关专利申请占我国专利总申请量的比例超过1／3，信息技术领域发明专利申请量与实用新型专利申请量比例达到2：1，这一构成比例大大高于全国1：1的平均水平。     

专利文献悄然“触网”

一、专利文献实现网络出版是出版界的一场革命 (1)互联网出现之前专利信息的传播方式 专利文献的信息量浩如烟海,到现在全世界专利文献已有几千万件,日本每年专利申请几十万件。我国专利法实施以来,中国专利申请在1999年底已超过100万件,已公开出版的专利文献达70万件,几百万页。据世界知识产权组织统计,世界范围之发明的90％～95％能在专利文献中查到,并且其中很多只能在专利文献中查到。据美国专利商标局统计,约有70％的发明未在专利文献以外的其他科技期刊中报道。可以说,专利文献几乎记载了人类     

面向SMT智能制造技术专利分析

SMT是新一代电子组装技术,是现代电子产品制造中的关键工艺技术之一.随着中国制造2025的制定,智能制造作为主攻方向,是新一轮工业革命的核心技术,已上升为国家战略.SMT与智能制造理念的融合,建立高效、敏捷、柔性及资源共享的SMT智能制造模式是电子产品制造业未来的发展方向,是提升SMT产品制造能力与水平的重要途径.本文以SooPAT专利数据库为数据来源,从年度专利申请趋势、专利类型分布情况、专利权人、IPC技术领域、专利区域分布等方面对我国SMT智能制造相关技术的专利情况进行深入分析.     

网上专利个性化管理与服务系统

专利文献的管理和分析对于知识产权保护和企业科技创新非常重要.专利个性化管理与服务系统是基于对象代理数据库管理系统的网上专利信息服务系统,它能够提供专利下载工具、检索与统计分析和个性化管理等先进功能.专利下载工具用于集成各国专利局的检索接口,从检索结果中抽取出结构化专利信息;专利检索与统计分析服务通过在本地建立专利数据库和全文索引来实现,能够提供专利各类查询和统计分析服务;个性化服务功能基于对象代理模型创建个性化数据空间来实现,能够自动更新数据空间中的数据,使得用户获得最新的专利信息.     

高等农业院校专利技术创新能力研究

以国家知识产权局专利数据库为基础,通过文献计量分析的原理和方法,从技术创新投入能力、支持能力以及产出能力方 面,对2003~2012 年云南农业大学和四川农业大学的专利进行对比研究。结果表明,从专利角度评价两所农业大学的技术创新能 力,四川农业大学在技术创新投入能力和支持能力方面占优势,云南农业大学在技术创新产出能力方面占优势。     

技术标准视角下全球4G移动通信技术专利信息分析

在简要概括移动通信技术发展历程的基础上，利用“Innography专利信息检索分析平台”，从技术标准的角度，对全球范围内4G移动通信技术专利进行全面检索，形成研究所需要的专利数据库，然后从全球分布、年度趋势、技术领域（IPC）、申请人、发明人、专利强度和专利权人综合竞争力等方面，对全球4G移动通信技术的专利布局进行分析。研究表明，全球4G移动通信技术领域的创新活动和专利保护正处于快速发展阶段，中国和美国是4G移动通信技术领域专利申请量最多的两个国家，中国虽然在该技术领域申请数量全球第一，但核心专利数量却远远落后于美国。     

搅拌摩擦焊接用搅拌头专利申请及技术分析

以DWPI和CNABS专利数据库的检索结果为分析样本,从专利文献的视角对国内外搅拌摩擦焊接用搅拌头专利申请状况和技术发展历程进行了全面的统计分析。     

分布式光纤传感专利技术综述

本文立足于专利文献,从专利的角度对分布式光纤传感技术进行了介绍和分析,梳理了分布式光纤传感技术的发展路线,对国内外涉及分布式光纤传感技术的专利申请进行了统计和分析,为相关领域的审查工作提供技术支持,也为相关的企业和研究机构提供了参考。     

基于专利分析的NB-IoT技术发展研究

专利融合技术信息和产业信息,通过对专利数据分析,可以判断技术和产业发展现状和态势。NB-IoT技术位于物联网技术架构体系的网络层,是物联网的关键技术之一。通过对NB-IoT技术专利申请量趋势、技术产出区域分布、目标市场发布、全球主要申请人排名等进行分析,揭示NB-IoT技术的发展状况与趋势,了解NB-IoT技术发展前景,发现当前存在的问题。     

基于触控技术的GUI交互专利技术分析

为了研究基于触控技术的图形用户界面交互技术的发展趋势,在实际审查经验的基础上,以SIPOABS数据库 为检索入口,采用IPC分类号结合关键词进行检索,对涉及触控技术的GUI交互领域的专利分布进行了分析统计,结果表明近 几年来我国在该领域专利申请量增长较快,但因我国相关技术起步较晚,核心专利主要掌握在国外企业手中。     

专利战略分析系统的设计与实现

分析了目前专利分析工作的不足，介绍了专利分析的理论基础PM，以及专利战略分析系统的系统框架、总体功能设计、数据库设计、流程设计和实现技术。     

Creating patents on the new technology using analogy-based patent mining

Patents on the new technology–a technology not yet commercialized and in an early stage of its life cycle–give firms many benefits. However, existing methods are inadequate because of dependencies on customers and physical prototypes. And there is lack of systems, focused on a problem identification process or an inter-technological comparison. In this research, to remedy existing limitations, analogy-based patent mining system is suggested. The system is developed based on an assumption that similar problems would occur in technologies that have similar properties or functions. So, the system is focused on identification of a Problem Solved Concept (PSC), which describes what problem is solved in the patent. At the first part of the system, the mature technology–a technology relatively matured than the new technology–is described with a property and a function; one of the property or the function should be similar to which of the new technology considered. And the system extract PSCs, construct patent map, and evaluate PSCs utilizing patents on the new and the mature technologies. As a result, the PSCs with high opportunities are revealed and patents related to the PSCs are examined. Then users of this system select some patents as resources for analogy. The system is tested by a case study of wireless charger technology. For the case study, 352 patents on wireless router technology and 227 patents on wireless charger technology are used. At the final, patents related to ‘handoff’, showed a high opportunity score and one of the patents is introduced to show the possibility of patent creation through analogy.     

Searching in Cooperative Patent Classification: Comparison between keyword and concept-based search

International patent corpus is a gigantic source containing today about 80 million of documents. Every patent is manually analyzed by patent officers and then classified by a specific code called Patent Class (PC). Cooperative Patent Classification CPC is the new classification system introduced since January 2013 in order to standardize the classification systems of all major patent offices. Like keywords for papers, PCs point to the core of the invention, describing concisely what they contain inside. Most of patents strategies are based on PC as filter for results therefore the selection of relevant PCs is often a primary and crucial activity. This task is considered particularly challenging and only few tools have been specially developed for this purpose. The most efficient tools are provided by patent offices of EPO and WIPO.This paper analyzes their PCs search strategy (mainly based on keyword-based engines) in order to identify main limitations in terms of missing relevant PCs (recall) and non-relevant results (precision). Patents have been processed by KOM, a semantic patent search tool developed by the authors. Unlike all other PC search tools, KOM uses semantic parser and many knowledge bases for carrying out a conceptual patent search. Its functioning is described step by step through a detailed analysis pointing out the benefits of a concept-based search vis-à-vis a keyword-based search. An exemplary case is proposed dealing with CPCs describing the sterilization of contact lenses. Comparison could be likewise conducted on other PCs such as International (IPC), European (ECLA) or United States (USPC) patent classification codes.     

云计算专利分析与企业专利战略研究*

为了减少企业专利侵权案件的发生和控制整个技术市场,亟需企业与科技情报检索部门精诚合作,协同创新,尝试开展具有企业特色需求和个性化专题的云计算情报检索分析,制定出云计算相关技术专利的发展战略。     

A patent quality analysis and classification system using self-organizing maps with support vector machine

A plethora of patents are approved by the patent officers each year and current patent systems face a solemn quandary of evaluating these patents’ qualities. Traditional researchers and analyzers have fixated on developing sundry patent quality indicators only, but these indicators do not have further prognosticating power on incipient patent applications or publications. Therefore, the data mining (DM) approaches are employed in this article to identify and to classify the new patent's quality in time. An automatic patent quality analysis and classification system, namely SOM-KPCA-SVM, is developed according to patent quality indicators and characteristics, respectively. First, the self-organizing map (SOM) approach is used to cluster patents published before into different quality groups according to the patent quality indicators and defines group quality type instead of via experts. The kernel principal component analysis (KPCA) approach is used to transform nonlinear feature space in order to improve classification performance. Finally, the support vector machine (SVM) is used to build up the patent quality classification model. The proposed SOM-KPCA-SVM is applied to classify patent quality automatically in patent data of the thin film solar cell. Experimental results show that our proposed system can capture the analysis effectively compared with traditional manpower approach.     

A cooperative multi-agent platform for invention based on patent document analysis and ontology

We propose a cooperative multi-agent platform to support the invention process based on the patent document analysis. It helps industrial knowledge managers to retrieve and analyze existing patent documents and extract structure information from patents with the aid of ontology and natural language processing techniques. It allows the invention process to be carried out through the cooperation and coordination among software agents delegated by the various domain experts in the complex industrial R&D environment. Furthermore, it integrates the patent document analysis with the inventive problem solving method known as TRIZ method that can suggest invention directions based on the heuristics or principles to resolve the contradictions among design objectives and engineering parameters. We chose the patent invention for chemical mechanical polishing (CMP) as our case study. However, the platform and techniques could be extended to most cooperative invention domains.     

Development of a GTM-based patent map for identifying patent vacuums

The patent map has long been considered as a useful tool for mining latent technological information. Among others, the detection of patent vacuums, defined as unexplored areas of new technologies, deserves intensive research. However, previous studies for identifying patent vacuums on the patent map have been subjected to some limitations, stemming from the subjective and manual identification of patent vacuums. To address these limitations, this paper proposes a generative topographic mapping (GTM)-based patent map, which aims to automatically identify a patent vacuum. Since GTM is a probabilistic approach of mapping multidimensional data space onto a low-dimensional latent space and vice versa, it contributes to the automatic detection and interpretation of patent vacuums. The proposed approach consists of three stages. Firstly, text mining is executed in order to transform patent documents into keyword vectors as structured data. Secondly, the GTM is employed to develop the patent map, subsequently leading to the discovery of patent vacuums, which are expressed as blank areas in the map. Lastly, the meaning of each patent vacuum is interpreted by the inverse mapping of patent vacuums onto the original keyword vector. The case study is conducted with lithography technology-related patents. We believe the proposed approach not only saves time and effort for identifying patent vacuums, but also increases objectivity and reliability.     

Lessons that Europe can learn from the US patent assertion entity phenomenon

This paper investigates the patent assertion entities (PAEs) problem in Europe. First, it argues that PAEs should be not as active in Europe as it is in the USA simply because European inventors infringe less. They infringe less because there are fewer patents to infringe. PAEs, however, can still thrive in Europe. Using the example of the UK, this paper shows that PAEs visible activities are non-negligible even if they pale compare to the level of activities in the USA. Using the example of France, this paper shows that governments have not waited for PAEs to come their countries; some have taken steps to create their own governmentally sponsored PAE. Finally, this paper argues that the USA is trying to learn from the EU and bring fee-shifting to their system; fee shifting, in and of itself cannot solve the PAE problem. This paper also argues that the EU is taken on some of the problem as the USA and responding in similar ways with regard to injunctions; injunction remains an important part of the PAE arsenal; yet, the highest courts in both jurisdictions have made clear that infringing a patent does not automatically great a patent holder a right to exclude others. The paper concludes by discussing the Unitary Patent Court system and the impact it will have on PAE activities in Europe: some PAEs may benefit but most will still find Europe a hostile environment for their activities.     

Establish a patent risk prediction model for emerging technologies using deep learning and data augmentation

Technology patents are considered the source and bedrock of emerging technologies. Patents create value in any enterprise. However, obtaining patents is time consuming, expensive, and risky; especially if the patent application is rejected. The development of new patents requires extensive costs and resources, but sometimes they may be similar to other patents once the technology is fully developed. They might lack relevant patentable features and as a result, fail to pass the patent examination, resulting in investment losses. Patent infringement is also an especially important topic for reducing the risk of legal damages of patent holders, applicants, and manufacturers. Patent examinations have so far been performed manually. Due to manpower and time limitations, the examination time is exceedingly long and inefficient. Current patent similarity comparison research, and the classification algorithms of text mining are most commonly employed to provide analyses of the possibility of examination approval, but there is insufficient discussion about the possibility of infringement. However, if a new technology or innovation can be accurately determined in advance whether it likely to pass or fail (and why), or is at risk of patent infringement, losses can be mitigated.This research attempts to identify the issues involved in evaluating patent applications and infringement risks from existing patent databases. For each patent application, this research uses Convolutional Neural Networks, CNN + Long Short Term Memory Network, LSTM, prediction model, and the United States Patent and Trademark Office (USPTO) public utility patent application and reviews results based on keyword search. Then, data augmentation is utilized before performing model training; 10% of the approved and rejected applications are randomly selected as test cases, with the remaining 90% of the cases used to train the prediction model of this research in order to determine a model that can predict patent infringement and examination outcomes. Experimental results of the model in this study predicts that the accuracy of each classification is at least 87.7%, and can be used to find the classification of the reason for a rejection of a patent application failure.     

基于领域知识的专利自动分类

根据改进的词语权重计算方法构造给定文本的特征向量,并用之从专利分类的领域知识——国际分类表IPC中直接提取类别的概念向量和待分类专利文本的特征向量,然后采用向量空间模型实现专利的自动分类,该方法不需要大量的训练样本,具有较高的分类正确率和执行速度。