Novel data structure and visualization tool for studying technology evolution based on patent information: The DTFootprint and the TechSpectrogram

We introduce a new, bespoke data structure to analyze and visualize the evolution of a technology. The technology under analysis is defined by a set of patents corresponding to a technical field, owned by a company or invented by a team of research. Our data structure, the Dynamic Technology Footprint –DTFootprint–, facilitates the analysis and visualization of trends and dynamics of a given technology, and therefore the evolution of a technical field, a company, or a team of people. A graphical tool based on our data structure is defined, it is named Technology Spectrogram –TechSpectrogram–, because it is inspired by the acoustic frequency spectrograms: as the acoustic frequency spectrograms visualize the dynamics of an acoustic wave showing the evolution of its frequency components our tool shows the dynamics of a technology showing the evolution of its technological components, which are represented by the whole set of IPC-codes. Our graphical tool, the TechSpectrogram is shown for some study cases, and its application to the history of technology and technology management are disclosed.     

Construction and validation of an ontology-based technology function matrix: Technology mining of cyber physical system patent portfolios

This research develops a computer-supported ontology-based Technology Function Matrix (TFM) construction method, called eTFM, as an approach to reduce technology mining man-power and enhance the accuracy and consistency of patent analysis results. The paper addresses a rarely discussed issue of the TFM validation. The proposed validation approach compares the TFMs construction based on both on the domain ontology and the International Patent Classification (IPC) classes. The research demonstrates the methodology's practical applications using the patent analysis case of cyber physical system (CPS), an essential core technology enabling advanced manufacturing and Industry 4.0.     

Visualizing patent statistics by means of social network analysis tools

The present paper reviews the literature on social network analysis with applications to bibliometric data, and in particular, patent information. Several approaches of network analysis are conducted in the field of optoelectronics to exemplify the power of network analysis tools. Cooperation networks between inventors and applicants are illustrated, emphasizing bibliometric measures such as activity, citation frequency, etc. as well as network theoretical measures, e.g. centrality or betweenness. In this context it is found that inventors who serve as interfaces or links between different inventor groups apply for technologically broader patents, hence, benefiting from their access to different knowledge through their position. Furthermore, citation networks of patent documents as well as patent applicants were drawn. Here, patent thickets could be identified. The position of applicants within citation networks seems to be useful in explaining behaviour of the applicants in the marketplace, such as cooperation or patent infringement trials.     

Text mining applied to patent mapping: a practical business case

Professional patent searchers are traditionally rather suspicious of the alleged “black box” effect inherently attached to intelligent software engines relying upon linguistic technologies for patent analysis and mapping. In this article, the authors propose that such prejudices can be overcome by setting a realistic business objective while experimenting with these new linguistic tools, as well as by applying serious methodology for validating the results of the analysis. The strengths and weaknesses of a particular text mining tool are assessed with reference to a practical business case in the field of packaging technology, and a comparison of the outcome of such an analysis with a traditional one, carried out using conventional patent classifications, is also described.     

Tech mining to validate and refine a technology roadmap

This study uses 'tech mining' (extracting intelligence from R&D data) to validate and refine the content of a particular section of a landmark roadmap of nanotechnology for aeronautics. We utilize topical content from publications and patents to analyze the developmental status of nanocomposite coating technologies. This enables us to validate predictions made by specialists, as presented in the target technology roadmap section. Moreover, we augment that roadmap section by providing additional information on nanocomposite-related emerging technologies. This study supports use of tech mining as a means to inform technology roadmapping, both when creating a new roadmap and to check progress.     

A survey on deep learning for patent analysis

Patent document collections are an immense source of knowledge for research and innovation communities worldwide. The rapid growth of the number of patent documents poses an enormous challenge for retrieving and analyzing information from this source in an effective manner. Based on deep learning methods for natural language processing, novel approaches have been developed in the field of patent analysis. The goal of these approaches is to reduce costs by automating tasks that previously only domain experts could solve. In this article, we provide a comprehensive survey of the application of deep learning for patent analysis. We summarize the state-of-the-art techniques and describe how they are applied to various tasks in the patent domain. In a detailed discussion, we categorize 40 papers based on the dataset, the representation, and the deep learning architecture that were used, as well as the patent analysis task that was targeted. With our survey, we aim to foster future research at the intersection of patent analysis and deep learning and we conclude by listing promising paths for future work.     

Twenty years of US nanopatenting: Maintenance renewal scoring as an indicator of patent value

This paper introduces a new measure of patent value – Maintenance Renewal Score (MRSc) – reflecting assignee valuing the patent by paying successive renewal fees. We generate MRSc's for nanotechnology patents issued by the US Patent Office from 1999 through 2009, with US assignees and US inventors. Patenting increases over this period, coincident with increased US funding of nanotechnology R&D. We compare maintenance rates over the period, and against a comparison set of all 1999 USPTO grants to US inventors/assignees. We find differences in propensity to maintain the nanopatents by institution type, technological sector, and patent complexity.     

Patent attorney as technology intermediary: A patent attorney-facilitated model of technology transfer in developing countries

Technology transfer (TT) is gaining popularity in the developing countries, but there exist barriers impeding the transfer. Technology intermediaries are believed to be able to mitigate such barriers in the literature, which however seldom considers patent attorneys. We contribute to the extant literature by highlighting that patent attorneys could facilitate TT, particularly in the developing countries (e.g., China). We propose a model to specify how patent attorneys can leverage their expertise and resource to motivate technology players to engage in TT, to identify the potential supply and demand of TT as well as to establish comprehensive IPR protection for TT.     

Analysis of the patent cooperation network in global artificial intelligence technologies based on the assignees

Studying the distribution of the patent cooperation networks from the perspective of assignees provides a very important reference to improve the analysis of the market situation, master the layout of industrial technology and seek partners or mergers and acquisitions. This study uses the Derwent patent database and the patent metric approach to investigate the cooperative network structure of the assignees. The overall patent output in the artificial intelligence field on a global scale exhibited a rapid growth, and the proportion of cooperative patents significantly increased; the cooperation structure between the assignees was loose, and the innovation efficiency was low.     

An analysis of the effects of artificial intelligence on electric vehicle technology innovation using patent data

This study empirically analyzes the effects of artificial intelligence (AI) on electric vehicle technology innovation by employing a machine learning-based text mining model and the international patent classification (IPC) co-occurrence network analysis, using patent data filed from 1980 to 2017. Based on artificial intelligence algorithms classified, the study demonstrates the dynamic changing pattern of the convergence of artificial intelligence and electric vehicle technology and reveals how artificial intelligence has affected electric vehicle technology innovation over time. This study reveals that artificial intelligence accelerates the automation of electric vehicle driving, and that artificial intelligence algorithms that are widely used in electric vehicles have changed over time, and that technology areas of electric vehicles that AI affects also have been changed.     

A guide to efficient keyword, sequence and classification search strategies for biopharmaceutical drug-centric patent landscape searches - A human recombinant insulin patent landscape case study

Searching biopharmaceutical drug-related patent information is generally considered to be challenging. In particular, setting up efficient search strategies for comprehensive retrieval of high amounts of patent documents related to processes and methods of use, that achieve a reasonable level of precision, but still remain within a particular search scope. While it is generally accepted that patent information cannot be searched using standardized approaches, it is desirable to have a basic rule set for successful biopharmaceutical drug-related patent information retrieval, particularly facing a steady flow of patent expirations for prominent biologic drugs. The present human recombinant insulin case study shows an assessment of keyword, sequence and classification search strategies for establishing biopharmaceutical drug-centric patent landscapes. The search results of both crude and sophisticated keyword search strategies, as well as of a sequence search strategy, were compared in terms of the key information retrieval quality indicators; the recall and the precision. Through analyses of the relevant retrieved documents, a quality assessment of keyword choice is provided, as well as determining focused IPC and Derwent Manual classification codes and terminology from original patent and Derwent documentation abstract titles. All of which can be used for setting up more efficient search strategies and facilitated document categorization.     

Electric vehicle technology in China: An exploratory patent analysis

Currently, the electric vehicle (EV) technology is of great interest in China and around the world. This paper first conducts a comprehensive review of China's EV policies and the development of China's EV technology, and then analyzes the domestic performances of China's EV technology and its international competitiveness by adopting the recently developed concept of transnational patents. The results show an outstanding performance for China's EV technology in the domestic market, but a relatively poor performance in the international markets. Finally, several main factors causing the inconsistent performance of China's EV technology are proposed and discussed.     

Exploring and visualizing spatial-temporal evolution of patent collaboration networks: A case of China's intelligent manufacturing equipment industry

With the integration of intelligent manufacturing (IM) technology and the manufacturing industry, the intelligent manufacturing equipment industry (IMEI) has become the focus of a new round of industrial revolution. This integration has led to a new revolution in the manufacturing industry and is key to transforming China into a manufacturing country with international competitiveness. However, China's IMEI is in the development stage, thus presenting a major challenge to it becoming a competitive core industry. Therefore, there is an urgent need to explore the IMEI patent collaboration network and analyze its evolutionary characteristics, which can improve not only the innovation ability of network organizations but also the overall competitiveness of the IMEI. This study employs social network analysis (SNA) to study the evolution of the patent collaboration network of China's IMEI. The results show that the number of co-patents for the IMEI field in China has obvious stage characteristics, the collaborative innovation patterns adopted by different provinces vary, and the State Grid has a strong influence on the network. The scale of the patent collaboration network is gradually expanding, exhibiting a “small-world” structure. Jiangsu mainly innovates through intra-provincial collaboration. Provinces such as Beijing, Guangdong and Shandong are more inclined to inter-provincial collaboration.     

The patent activities of Korea and Taiwan: a comparative case study of patent statistics

This paper examines the patent grant rate of Korea and Taiwan by using the country-level patent statistics of Korea, Taiwan and USA during the period of 1988–1998. The patent grant rate means the rate of US patent grants to the applications filed in USA during the investigated years. To measure the grant rate, a model was developed for the methodological procedure. In the framework of the model, the process of patent dynamics in these countries shows different patterns. The financial crisis of Korea in 1998–1999 influenced the number of domestic patent applications by Koreans, resulting in the rapid decrease. The US patent application rate by Koreans, however, was not affected, keeping the average rate of applications at 7.5% of the Korean applications during the investigated period. The rate of US patent grants by Koreans in the early 1990s dropped, which can be explained by the change of patent strategy of Samsung Elec. Co. Ltd.Taiwan, on the other hand, had filed 160% more US patent applications than its own domestic applications. The authors suggest that this is attributable to some US patent applications corresponding to Taiwanese domestic applications for utility models, and that this may be a factor in the lower rate of Taiwanese US patent grants (average 53.4%) than that of Koreans (average 66.3%). The rate of US patent grants by Taiwanese has constantly increased, while that for Koreans has fluctuated; the authors conjecture that this implies that Taiwanese patent management for the US patents has improved.     

The idiosyncrasy and dynamism of technological innovation across industries: patent citation analysis

In general, the structural and behavioral patterns of technological innovation are idiosyncratic across industrial sectors and dynamic over time. Yet, despite voluminous amounts of previous research, patterns of innovation are hard to standardize or theorize. The objectives of this article are two-fold. One is to investigate distinctive and changing patterns of technological innovation across industries and observe dynamic trends over time. The other is to identify patterns of relationships among industries and examine the roles of respective industries. To this end, the U.S. Patent and Trademark Office (PTO) patent database was used and patent citation analysis applied. The idiosyncratic differences among industrial sectors are highlighted, especially between conventional manufacturing sectors and science-based sectors. We also found changing trends in technological knowledge flows across industries.     

Applying an anchor based patent mapping approach: Basic conception and the case of carbon fiber reinforcements

Patent mapping is an important method for analyzing technological patterns both for scientific research and strategic tasks in companies. In this paper we focus on a specific type of technological pattern, namely the analysis of patents' positions in relation to predefined positions of application fields. For this purpose we use an anchoring approach. We apply semantic patent measurement and discuss RadViz as a powerful method to visualize the measurement's results and to provide insightful motion patterns for monitoring technology change. Moreover, we present an algorithm to define so called anchor points as high dimensional reference points by using textual elements of patents. By the example of carbon fiber reinforcements we demonstrate the usefulness of our approach. Thus, our approach enables academics to analyze important types of technological patterns like convergence or divergence by means of a new instrument and gives practitioners like the R&D management of companies the opportunity to build a reliable strategic business decision support.     

Using automated patent landscaping and legal geography analysis to spot biopiracy activities in the island of Hispaniola

This paper reports on an automated patent landscaping and legal geography analysis to scrutinize the biopiracy of endemic plants in the island of Hispaniola (Haiti and the Dominican Republic). My analysis relies on shrubs and flowers that may be reaped without a fair and equitable distribution of benefits. My findings highlight that Western pharmaceutical and biotechnology companies' innovations may overlap sovereign states’ intellectual property rights, implying that regulatory gaps must be filled to empower local communities to benefit from biodiversity and ecosystem services. Therefore, I suggest that the island adopt effective and consistent access and benefit-sharing policies, including mechanisms that encourage environmental protection and require prior informed consent and mutually agreed terms for utilizing genetic resources. I also suggest the introduction of disclosure of origin and/or source of genetic resources in their respective patents regime to ensure that Convention on Biological Diversity regulations and other related international frameworks can be followed.     

Patenting trends in biometric technology of the Big Five patent offices

We examined the overall trends in biometric technology based on patent documents. Using PATSTAT database, we extracted 37,462 patent documents applied at the Big Five patent offices between 1990 and 2016. Latent Dirichlet allocation was applied to their abstracts to observe annual trends by topic. Our results are as follows: Fingerprint-enabled car anti-theft systems have been undergoing rapid technological development since 2014. In response, biometric signal transmitting models are becoming popular owing to concerns about theft of biometric templates. While fingerprint, face, and iris authentication technologies continue to advance, finger vein, voice, and signature authentication technologies are lagging. Use of biometric technologies in financial transactions, server networks, and digital media content security are decreasing as well. A citation analysis discovered key topics and patent applicants: Surprisingly, the quantitative growth rate of topics and the effect on the knowledge network showed an inverse relationship. US firms had the most citations, but fewer backward citations of own work, unlike Japanese companies. We provide practical insights to stakeholders of biometric technology.     

Blurring the line between bioinformatics and patent analysis

Biological patent analysts are often faced with querying multiple databases of sequence and text. After retrieving the query results, the results must be analyzed by reviewing patents and applications in a form of manual data reduction. Once families are identified for final analysis, the analyst must expand back out, looking at the members of those patent families. Again, sequence and text is reviewed manually, not algorithmically. One way for patent analysts to reduce the number of repetitive tasks performed is through the creation of macros. Such macros can be used for time-consuming tasks like global formatting, searching and replacing within a document, formatting extracted sequences into FASTA, or even converting three-letter amino acid code into single-letter code. Another way for a patent analyst to reduce repetitive tasks in biosequence patent analysis is through an alliance between biological patent analysts and bioinformaticians. Such an alliance could result in the development of tools that focus on these types of repetitive tasks. A bioinformatician is skilled in looking for solutions to various repetitive tasks. Such a solution could even be packaged and deployed to those colleagues who would benefit from access to such a time-saving program. Finding a way to automate repetitive tasks will free the patent analyst to spend more time on intellectual analysis of the results.