Measuring textual patent similarity on the basis of combined concepts: design decisions and their consequences

For certain tasks in patent management it makes sense to apply a quantitative measure of textual similarity between patents and/or parts thereof: be it the analysis of freedom to operate, the analysis of technology convergence, or the mapping of patents for strategic purposes. In this paper we intend to outline the process of measuring textual patent similarity on the basis of elements referred to as ‘combined concepts’. We are going to use this process in various operations leading to design decisions, and shall also provide guidance regarding these decisions. By way of two applications from patent management, namely the prioritization of patents and the analysis of convergence between two technological fields, we mean to demonstrate the crucial importance of design decisions in terms of patent analysis results.     

The prevalence of weak patents in the United States: A new method to identify weak patents and the implications for patent policy

The presence of patents with dubious validity (i.e., weak patents) has been one of the prominent patent policy issues with undesirable consequences in innovation. The present study empirically examines the prevalence of weak patents in the United States and whether or not the current patent system is capable of correcting weak patent issues. To this end, we propose a new method to identify weak patents by using patent citation information in conjunction with the textual similarity between citing and cited patents. Our method, along with a series of internal validation measures, shows that 13% of U.S. patents filed from 2001 to 2010 are weak patents. By applying this new method, we find that patent owners build a patent portfolio around a weak patent by developing subsequent inventions more than they do for a non-weak patent. Our further analysis finds that a weak patent is more or equally likely to be retained by the patent owner than a non-weak patent. Our findings suggest that patent owners have an incentive to invest in maintaining and appropriating weak patents, and thus, the current patent system is incapable of self-correcting weak patent issues.     

A new instrument for technology monitoring: novelty in patents measured by semantic patent analysis

Given that in terms of technology novel inventions are crucial factors for companies; this article contributes to the identification of inventions of high novelty in patent data. As companies are confronted with an information overflow, and having patents reviewed by experts is a time-consuming task, we introduce a new approach to the identification of inventions of high novelty: a specific form of semantic patent analysis. Subsequent to the introduction of the concept of novelty in patents, the classical method of semantic patent analysis will be adapted to support novelty measurement. By means of a case study from the automotive industry, we corroborate that semantic patent analysis is able to outperform available methods for the identification of inventions of high novelty. Accordingly, semantic patent information possesses the potential to enhance technology monitoring while reducing both costs and uncertainty in the identification of inventions of high novelty.     

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.     

Measures for textual patent similarities: a guided way to select appropriate approaches

The measurement of textual patent similarities is crucial for important tasks in patent management, be it prior art analysis, infringement analysis, or patent mapping. In this paper the common theory of similarity measurement is applied to the field of patents, using solitary concepts as basic textual elements of patents. After unfolding the term ‘similarity’ in a content and formal oriented level and presenting a basic model of understanding, a segmented approach to the measurement of underlying variables, similarity coefficients, and the criteria-related profiles of their combinations is lined out. This leads to a guided way to the application of textual patent similarities, interesting both for theory and practice.     

Technology–industry networks in technology commercialization: evidence from Korean university patents

Although there is increasing interest in policy issues on university patents, studies hitherto have focused on certain limited factors or case studies. By using a two-mode network analysis, this study identifies idiosyncratic patterns and differences in technology–industry networks between the two groups of Korean university patents—commercialized and non-commercialized. We collected patent data including bibliographic information from Korean universities that have run a patent management advisor dispatch program since 2005. Then, network analysis and analysis of variance for the two groups were conducted to investigate the group differences. We found that the structure of the technology–industry network was significantly more direct and simpler for commercialized than for non-commercialized patents. Specifically, we found that both direct and indirect linkages between technology and related industry were more complex for the non-commercialized group than for the commercialized one: the direct linkage was stronger for the commercialized than for the non-commercialized group. Our study suggests an important aspect of technology commercialization from the perspective of the inherent characteristics of patents, which is at variance with the evolutionary approaches of previous studies.     

Assessing coreness and intermediarity of technology sectors using patent co-classification analysis: the case of Korean national R&D

Rapid technological advancements and increasing research and development (R&D) costs are making it necessary for national R&D plans to identify the coreness and intermediarity of technologies in selecting projects and allocating budgets. Studies on the coreness or intermediarity of technology sectors have used patent citations, but there are limitations to dealing with patent data. The limitations arise from the most current patents and patents that do not require citations, e.g. Korean patents. Further, few or no studies have simultaneously considered both coreness and intermediarity. Therefore, we propose a patent co-classification based method to measure coreness and intermediarity of technology sectors by incorporating the analytic network process and the social network analysis. Using IPC co-classifications of patents as technological knowledge flows, this method constructs a network of directed knowledge flows among technology sectors and measures the long-term importance and the intermediating potential of each technology sector, despite the limitations of patent-based analyses. Considering both coreness and intermediarity, this method can provide more detailed and essential knowledge for decision making in planning national R&D. We demonstrated this method using Korean national R&D patents from 2008 to 2011. We expect that this method will help in planning national R&D in a rapidly evolving technological environment.     

A Systemic Approach to Exploring an Essential Patent Linking Standard and Patent Maps: Application of Generative Topographic Mapping (GTM)

Abstract:

As the intense competition for the international standardization of technology has increased, many companies are concentrating their capabilities on securing essential patents that claim one or more inventions required to practice a given industry standard; however, despite the importance of developing essential patents, the approaches to exploring promising essential patent: have some limitations in terms of methodology and data. As a remedy, this article proposes a method that derives an essential patent through Generative Topographic Mapping (GTM)-based standard and patent maps. The suggested approach involves a systematic process that identifies vacuums on a standard map in a specific technology field and enables analysts to find candidate for promising essential patents instead of relying on the experts. By applying the proposed methodology, this research discovered the vacuums in an industrial standard document about fuel cell technology as well as the candidates of essential patents in this technology field.     

Identifying rapidly evolving technological trends for R&;D planning using SAO-based semantic patent networks

Patents constitute an up-to-date source of competitive intelligence in technological development; thus, patent analysis has been a vital tool for identifying technological trends. Patent citation analysis is easy to use, but fundamentally has two main limitations: (1) new patents tend to be less cited than old ones and may miss citations to contemporary patents; (2) citation-based analysis cannot be used for patents in databases which do not require citations. Naturally, citation-based analysis tends to underestimate the importance of new patents and may not work in rapidly-evolving industries in which technology life-cycles are shortening and new inventions are increasingly patented world-wide. As a remedy, this paper proposes a patent network based on semantic patent analysis using subject-action-object (SAO) structures. SAO structures represent the explicit relationships among components used in a patent, and are considered to represent key concepts of the patent or the expertise of the inventor. Based on the internal similarities between patents, the patent network provides the up-to-date status of a given technology. Furthermore, this paper suggests new indices to identify the technological importance of patents, the characteristics of patent clusters, and the technological capabilities of competitors. The proposed method is illustrated using patents related to synthesis of carbon nanotubes. We expect that the proposed procedure and analysis will be incorporated into technology planning processes to assist experts such as researchers and R&D policy makers in rapidly-evolving industries.     

Detecting signals of new technological opportunities using semantic patent analysis and outlier detection

In the competitive business environment, early identification of technological opportunities is crucial for technology strategy formulation and research and development planning. There exist previous studies that identify technological directions or areas from a broad view for technological opportunities, while few studies have researched a way to detect distinctive patents that can act as new technological opportunities at the individual patent level. This paper proposes a method of detecting new technological opportunities by using subject–action–object (SAO)-based semantic patent analysis and outlier detection. SAO structures are syntactically ordered sentences that can be automatically extracted by natural language processing of patent text; they explicitly show the structural relationships among technological components in a patent, and thus encode key findings of inventions and the expertise of inventors. Therefore, the proposed method allows quantification of structural dissimilarities among patents. We use outlier detection to identify unusual or distinctive patents in a given technology area; some of these outlier patents may represent new technological opportunities. The proposed method is illustrated using patents related to organic photovoltaic cells. We expect that this method can be incorporated into the research and development process for early identification of technological opportunities.     

Identifying potential users of technology for technology transfer using patent citation analysis: a case analysis of a Korean research institute

The purpose of this study is to examine whether patent citation analysis can be used for making decisions of technology transfer. More precisely, the authors of this paper are interested in the matter of identifying potential users of technology by patent citation analysis. Previous research relied on patents’ keywords, and as a consequence it was difficult to implement in practice where organizations retain huge number of patents to transfer. In this study, we attempt to use IPCs instead of keywords. Our approach is to identify dominant IPC and sub-classes of an organization by applying co-classification analysis, and explore firms that cited the patents in the dominant IPC. Our view is that the organizations explored in this process can be potential users of technology. To verify our view, we examined the patents and technology transfer cases of two divisions in K Research Institute in Korea. The results show that our view was right only for a limited field. We suppose that the reasons may stem from technological characteristics and firm size effect. Therefore, we suggest that there should be further research considering technological characteristics and firm size.     

What makes the first forward citation of a patent occur earlier?

Identifying the economic value of a patent is crucial to technology management. It also facilitates the commercialization and transactions of patents. As a proxy of patent value, forward citation counting is widely used, but it takes a long time for a patent to be sufficiently cited. In this context, we suggest the first citation lag, namely the time taken until the first citation, as a proxy of patent value, as it is positively correlated with the patent value and considers the fact that important patents with a high economic value tend to receive many citations in a short space of time. We explore the influential patent attributes related to the first citation lag to build a model to predict the patent value. By using the Cox proportional hazard model on green inventory patent data, we find that patents with a shorter technology cycle time and a larger number of IPC four-digit classes, claims, patent family, and backward citations are associated with the shorter first citation lag, while a patent’s science linkage has an inverse U-shaped relationship with the first citation lag. Further, patents having an unconventional technological core have a longer first citation lag and among patents having an unconventional technological core, the presence of a novel element makes the first citation earlier. Our study is expected to help patent evaluation in the early stage of technology transfer.     

The technology assessment and forecast program of the United States patent and trademark office

Often overlooked is the wealth of information in patents that makes patents useful to public policy making agencies and corporate management, among others. The source of this information is the bibliographic and classification data associated with each patent. much of which is required by law and hence is extremely accurate. These data serve to fingerprint the increment of technological activity disclosed in a patent. Possible ways of using the data include: — identification of emerging technologies — Monotoring foreign activity — identification of “actors” in the technology — tracking applications and impacts of a technologyThe objective of the technology assessment and forecast program of the United States Patent and Trademark Office is to stimulate the use of the patent file of the Office. The Office of Technology Assessment and Forecast (OTAF), which administers the program has assembled a master data base covering all U.S. patents. It periodically updates this base and adds new data items to it.     

Patent information retrieval: approaching a method and analysing nanotechnology patent collaborations

Many challenges still remain in the processing of explicit technological knowledge documents such as patents. Given the limitations and drawbacks of the existing approaches, this research sets out to develop an improved method for searching patent databases and extracting patent information to increase the efficiency and reliability of nanotechnology patent information retrieval process and to empirically analyse patent collaboration. A tech-mining method was applied and the subsequent analysis was performed using Thomson data analyser software. The findings show that nations such as Korea and Japan are highly collaborative in sharing technological knowledge across academic and corporate organisations within their national boundaries, and China presents, in some cases, a great illustration of effective patent collaboration and co-inventorship. This study also analyses key patent strengths by country, organisation and technology.     

Patents cited in the scientific literature: An exploratory study of 'reverse' citation relations

This paper reports on a new approach to study the linkage between science and technology. Unlike most contributions to this area we do not trace citations of scientific literature in patents but explore citations of patents in scientific literature. Our analysis is based on papers recorded in the 1996-2000 annual volumes of the CD-Edition of Science Citation Index (SCI) of the Institute for Scientific Information (ISI) and patent data provided by the US Patent and Trademark Office. Almost 30,000 US patents were cited by scientific research papers. We analysed the citation links by scientific fields and technological sectors. Chemistry-related subfields tended to cite patents more than other scientific area. Among technological sectors, chemical clearly dominates followed by drugs and medical patents as the most frequently cited categories. Further analyses included a country-ranking based on inventor-addresses of the cited patents, a more detailed inspection of the ten most cited patents, and an analysis of class-field transfers. The paper concludes with the suggestions for future research. One of them is to compare our 'reverse' citation data with 'regular' patent citation data within the same classification system to see whether citations occur, irrespectively of their directionality, in the same fields of science and technology. Another question is as to how one should interpret reverse citation linkages.     

Patents as technological information in Latin America

This study shows the importance of patents as a source of technological information in Latin America. We studied the industrial property offices’ websites and the kind of patent information available such as laws, gazette, statistics, cost, forms, and contacts. We found at the USPTO and PCT websites the quantity of patent applications from applicants in Latin American countries filed in these offices. Brazil and Mexico in particular provide information on their websites to anyone interested in filing patent applications, searching patents and using patents as a source of technological information. This work shows that the quantity of patent applications is only slowly increasing in Latin America. Thus, each one of the 21 countries of Latin America needs to have a policy of dissemination of the importance of the patent system as a source of technological information to increase research and innovation in their countries.     

Methods for identifying emerging General Purpose Technologies: a case study of nanotechnologies

Nanotechnology is an emerging field of science with the potential to generate new and enhance existing products and transform the production process. US patent data is used to track the emergence of nanotechnologies since 1978. The nanotechnologies that have undergone the most development are identified using patent citation data and co-citation patterns of patents are examined to define clusters of related nanotechnologies. The potential for economic impact of the emerging nanotechnologies is assessed using a generality index.     

Transnational citation, technological diversity and small world in global nanotechnology patenting

Despite the extensive studies conducted in the field of nanotechnology based on US patent data, the choice of a single database may impede a wider view of this technology frontier. Based on patent data from the Derwent Innovation Index database that covers the data of 41 major patent offices, we review the development of nanotechnology patenting from the dimensions of patenting authority and technological classification. We find that a small number of countries dominating the technology have similar technological diversity in terms of nanotechnology patents. After the discussion and summary of the citation modes and citation rate curve, we construct the patent citation networks at the patent document level and discuss the distinctive transnational citation patterns. We then use Search Path Count Method to extract the technological trajectory, where we find very high selectiveness. In the final section of this paper, we discover the small world phenomenon in the citation networks, which is widely investigated in undirected networks such as co-authorship networks, but rarely touched in citation networks due to the limitations of the presumptions. We propose the reachable path length and citation clustering in the revised small world model for acyclic directed networks and provide the realistic meaning of the new measures.     

Dynamic patterns of technological convergence in printed electronics technologies: patent citation network

The importance of the convergent approach to technology development has increased recently. Therefore, understanding the characteristics of technology convergence, which refers to the combination of two or more technological elements in order to create a new system with new functions, is an important issue not only for researchers in technology development, but also for company directors for their successful management of product competitiveness. Therefore, in order to investigate the patterns and the mechanism of technological convergence, we examine the printed electronics technology which has typical characteristics of technology convergence. Based on the printed electronics-related patents registered between 1976 and 2012, we perform network analysis of the technology components in order to identify key technologies which played a central role among the groups of convergence technologies and to examine their dynamic role corresponding to the development of technology convergence. The results show that control technologies which control the role of other technologies over the technology convergence process play significant role. The centrality value is highest in the case of control technology, and devices related technologies have the largest number of patents quantitatively, thereby confirming the results. In addition, the trajectory analysis of the centrality value reveals a co-evolution pattern in technology convergence.