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South Korea has experienced rapid aging, and it is predicted that people aged 65 years or older will account for 20% of the total population by 2047. The proportion of one-person households is also increasing rapidly at the same time, and is expected to account for 37% of the total number of households by 2047. Such a demographic shift has led to more isolated households and social isolation, and consequently, to higher risks of solitary deaths. Central and local governments have implemented various measures, such as care services for the elderly living alone and regular checks on their status; however, there are limitations due to workforce and budget constraints. Therefore, it is necessary to explore innovative solutions that utilize digital technologies such as the internet of things (IoT) and artificial intelligence (AI) as new low-cost, high-efficiency alternatives. Innovations in digital technology have the potential to suggest new solutions to the issue of solitary death. Advanced technologies can play an important role in maximizing the effectiveness of solitary death prevention, management, and the prevention of social isolation. Although there is a growing body of research on the development of digital technology-based care services for the elderly, these studies have primarily focused on the applicability and early implementation stages of specific technologies. These studies have limitations in fully understanding the market trends of technologies and competition patterns within the industry. Therefore, it is essential to investigate trends in the latest technologies and R&D directions in a particular technology field through patents filed to protect new technologies. This study is intended to contribute to an in-depth understanding of the current status and development direction of digital technologies for the prevention of solitary deaths, and to provide a basis for future technology development. This study also contributes to establishing government policies and R&D strategies. [ABSTRACT FROM AUTHOR]

Revolutionary advances in technology have been seen in many industries, with the IIoT being a prime example. The IIoT creates a network of interconnected devices, allowing smooth communication and interoperability in industrial settings. This not only boosts efficiency, productivity, and safety but also provides transformative solutions for various sectors. This research looks into open-source IIoT and edge platforms that are applicable to a range of applications with the aim of finding and developing high-potential solutions. It highlights the effect of open-source IIoT and edge computing platforms on traditional IIoT applications, showing how these platforms make development and deployment processes easier. Popular open-source IIoT platforms include DeviceHive and Thingsboard, while EdgeX Foundry is a key platform for edge computing, allowing IIoT applications to be deployed closer to data sources, thus reducing latency and conserving bandwidth. This study seeks to identify potential future domains for the implementation of IIoT solutions using these open-source platforms. Additionally, each sector is evaluated based on various criteria, such as development requirement analyses, market demand projections, the examination of leading companies and emerging startups in each domain, and the application of the International Patent Classification (IPC) scheme for in-depth sector analysis. [ABSTRACT FROM AUTHOR]

Revolutionary advances in technology have been seen in many industries, with the IIoT being a prime example. The IIoT creates a network of interconnected devices, allowing smooth communication and interoperability in industrial settings. This not only boosts efficiency, productivity, and safety but also provides transformative solutions for various sectors. This research looks into open-source IIoT and edge platforms that are applicable to a range of applications with the aim of finding and developing high-potential solutions. It highlights the effect of open-source IIoT and edge computing platforms on traditional IIoT applications, showing how these platforms make development and deployment processes easier. Popular open-source IIoT platforms include DeviceHive and Thingsboard, while EdgeX Foundry is a key platform for edge computing, allowing IIoT applications to be deployed closer to data sources, thus reducing latency and conserving bandwidth. This study seeks to identify potential future domains for the implementation of IIoT solutions using these open-source platforms. Additionally, each sector is evaluated based on various criteria, such as development requirement analyses, market demand projections, the examination of leading companies and emerging startups in each domain, and the application of the International Patent Classification (IPC) scheme for in-depth sector analysis.

Wastewater is a major source of water pollution, as it contains contaminants from human waste, chemicals, industrial runoff, and other sources that can be harmful to the environment and human health. Therefore, treatment is necessary to reduce its harmful effects. However, wastewater treatment (WWT) is often costly and difficult to implement in many areas. With conventional WWT designs lacking robustness and adaptability, modular designs can be a viable solution for this problem. In this review, a patent survey covering patents from 1996 to 2021 yielded 66 patents regarding modular WWT. The patent search showed increasing patents regarding modular WWT in recent years. Most of the patents were filed by companies in China. The International Patent Classification (IPC) was used to determine the current trends in modular WWT. Current patented designs suggest that there have been attempts to develop modularized electrochemical, separation, and sorption methods. Also, multistep patent designs showed fully integrated modular units from conventional WWT design and offer robustness and adaptability. This patent review showed that modular WWT technologies are capable and ready to be used in different settings. [ABSTRACT FROM AUTHOR]

South Korea has experienced rapid aging, and it is predicted that people aged 65 years or older will account for 20% of the total population by 2047. The proportion of one-person households is also increasing rapidly at the same time, and is expected to account for 37% of the total number of households by 2047. Such a demographic shift has led to more isolated households and social isolation, and consequently, to higher risks of solitary deaths. Central and local governments have implemented various measures, such as care services for the elderly living alone and regular checks on their status; however, there are limitations due to workforce and budget constraints. Therefore, it is necessary to explore innovative solutions that utilize digital technologies such as the internet of things (IoT) and artificial intelligence (AI) as new low-cost, high-efficiency alternatives. Innovations in digital technology have the potential to suggest new solutions to the issue of solitary death. Advanced technologies can play an important role in maximizing the effectiveness of solitary death prevention, management, and the prevention of social isolation. Although there is a growing body of research on the development of digital technology-based care services for the elderly, these studies have primarily focused on the applicability and early implementation stages of specific technologies. These studies have limitations in fully understanding the market trends of technologies and competition patterns within the industry. Therefore, it is essential to investigate trends in the latest technologies and R&D directions in a particular technology field through patents filed to protect new technologies. This study is intended to contribute to an in-depth understanding of the current status and development direction of digital technologies for the prevention of solitary deaths, and to provide a basis for future technology development. This study also contributes to establishing government policies and R&D strategies.

This paper studies whether and how IURAs affect corporate technological diversification. Taking the ChiNext-listed companies that are both active in IURAs and innovation activities as our research objects, we analyzed the mechanisms of IURAs and their effect on corporate technological diversification based on the International Patent Classification information of new inventions. Our results, using propensity score matching and difference-in-differences regressions, show that IURAs can promote corporate technological diversification. Moreover, such effects are further proved using a dynamic analysis model. Furthermore, the absorptive capacity of the firm has a moderating effect on technological diversification after participating in the IURAs. This paper empirically advances our understanding of IURAs in the emerging markets and has meaningful policy implications for how governments and firms can deepen innovation. [ABSTRACT FROM AUTHOR]

Self-similar growth and fractality are important properties found in many real-world networks, which could guide the modeling of network evolution and the anticipation of new links. However, in technology-convergence networks, such characteristics have not yet received much attention. This study provides empirical evidence for self-similar growth and fractality of the technology-convergence network in the field of intelligent transportation systems. This study further investigates the implications of such fractal properties for link prediction via partial information decomposition. It is discovered that two different scales of the network (i.e., the micro-scale structure measured by local similarity indices and the scaled-down structure measured by community-based indices) have significant synergistic effects on link prediction. Finally, we design a synergistic link prediction (SLP) approach which enhances local similarity indices by considering the probability of link existence conditional on the joint distribution of two scales. Experimental results show that SLP outperforms the benchmark local similarity indices in most cases, which could further validate the existence and usefulness of the synergistic effect between two scales on link prediction. [ABSTRACT FROM AUTHOR]

Fast and effective forecasting of the new generation of products is key to enhancing the competitiveness of a company in the market. Although the technological evolution laws in the theory of the solution of inventive problems (TRIZ) have been used to predict the potential states of products for innovation, there is a lack of effective methods to select the best technological evolution law consistently with product replacement and update, and acquiring potentially new technologies and solutions, which relies heavily on designers' experience and makes it impossible for designers to efficiently use the technological evolution laws to stimulate product innovation. Aimed to bridge this gap, this paper proposes an integrated method consisting of three main steps, combining the technological evolution laws with back propagation neural network (BPNN), international patent classification (IPC) knowledge and company's technological distance. The best technical evolution law is first searched by a BPNN. The functional verbs and effects in the IPC are then extracted and searched for potential technologies in the Spyder-integrated development environment. Finally, the company's technological distance is used to select analogous sources of potential solutions in the patent database. The final innovative design is determined based on the ideality. The proposed method is applied in the development of a steel pipe-cutting machine to verify its feasibility. The proposed method reduces the dependence on designers' experience and provides a way to access cross-domain technologies, providing a systematic approach for the technological evolution laws to motivate innovative product design. [ABSTRACT FROM AUTHOR]

The article focuses on recent judicial rulings in patent law, particularly two cases involving the University of Minnesota and multiple cellular network companies. It is reported that these cases address complex issues such as the designation of the U.S. in international patent applications and the validity of reissued patents under the original patent rule.

Identifying technological opportunities early on is critical for the development of radical inventions (RIs). Patents are recognized as one of the most reliable resources for identifying technological opportunities. In line with this, this study aimed to suggest a novel approach for the identification of technological opportunities for RIs, based on the International Patent Classification (IPC), whose design knowledge has not been fully utilized. In this approach, technological opportunities for RIs are identified by measuring the value of technological novelty (VON) of each technology manifested in a patent set, and the value of difficulty (VOD) of each R&D theme contained in the patent set. Specifically, VONs are calculated through a novel map of technological changes over time, based on structured data from the patent set; and VODs are determined using natural language processing, K-means cluster analysis, and complex network analysis of the unstructured data from the patent set. The feasibility and operability of the proposed approach are verified in a case study of unmanned aerial vehicles. The proposed approach can help designers maximize the use of designs and expert knowledge in patent libraries, to formulate technical strategies for RIs. [ABSTRACT FROM AUTHOR]

As car original equipment manufacturers (OEMs) announce the electrification of their product line-ups, assessing the technological adaptability of their suppliers in the electric vehicle (EV) era is necessary. The technological adaptability of a supplier can vary significantly in terms of accumulated technologies. Herein, we propose a framework to assess adaptability from two aspects—EV-related and pivoting—based on patent portfolio analysis. First, adaptability to EV-related technologies is evaluated in terms of a supplier's patents applied individually and copatents with OEMs for parts to be modified. The degree of similarity of the patents related to internal combustion engine vehicle (ICEV) components with the patents related to EVs is calculated using PatentSBERTa, which reflects the modification degree required for ICEV components to be suitable for EVs. Second, we utilize automotive industry-related and unrelated diversity based on the entropy of International Patent Classification (IPC) codes to measure the supplier's technological adaptability to pivot within the automotive industry or other industries. The framework is empirically applied to suppliers in the drivetrain and climate control sectors to assess their technological adaptability to supply EV parts associated with the parts they are delivering. Our framework is expected to provide transition strategies for automotive suppliers in the EV era. • We propose a framework to assess the technological adaptability of automotive suppliers. • The framework is based on the patent portfolio analysis. • EV-related technological adaptability and the adaptability to pivot are measured. • The framework is applied to drivetrain and climate control suppliers. • We offer technological strategies to incumbent suppliers based on the framework. [ABSTRACT FROM AUTHOR]

Self-similar growth and fractality are important properties found in many real-world networks, which could guide the modeling of network evolution and the anticipation of new links. However, in technology-convergence networks, such characteristics have not yet received much attention. This study provides empirical evidence for self-similar growth and fractality of the technology-convergence network in the field of intelligent transportation systems. This study further investigates the implications of such fractal properties for link prediction via partial information decomposition. It is discovered that two different scales of the network (i.e., the micro-scale structure measured by local similarity indices and the scaled-down structure measured by community-based indices) have significant synergistic effects on link prediction. Finally, we design a synergistic link prediction (SLP) approach which enhances local similarity indices by considering the probability of link existence conditional on the joint distribution of two scales. Experimental results show that SLP outperforms the benchmark local similarity indices in most cases, which could further validate the existence and usefulness of the synergistic effect between two scales on link prediction.

Fast and effective forecasting of the new generation of products is key to enhancing the competitiveness of a company in the market. Although the technological evolution laws in the theory of the solution of inventive problems (TRIZ) have been used to predict the potential states of products for innovation, there is a lack of effective methods to select the best technological evolution law consistently with product replacement and update, and acquiring potentially new technologies and solutions, which relies heavily on designers’ experience and makes it impossible for designers to efficiently use the technological evolution laws to stimulate product innovation. Aimed to bridge this gap, this paper proposes an integrated method consisting of three main steps, combining the technological evolution laws with back propagation neural network (BPNN), international patent classification (IPC) knowledge and company’s technological distance. The best technical evolution law is first searched by a BPNN. The functional verbs and effects in the IPC are then extracted and searched for potential technologies in the Spyder-integrated development environment. Finally, the company’s technological distance is used to select analogous sources of potential solutions in the patent database. The final innovative design is determined based on the ideality. The proposed method is applied in the development of a steel pipe-cutting machine to verify its feasibility. The proposed method reduces the dependence on designers’ experience and provides a way to access cross-domain technologies, providing a systematic approach for the technological evolution laws to motivate innovative product design.

Identifying technological opportunities early on is critical for the development of radical inventions (RIs). Patents are recognized as one of the most reliable resources for identifying technological opportunities. In line with this, this study aimed to suggest a novel approach for the identification of technological opportunities for RIs, based on the International Patent Classification (IPC), whose design knowledge has not been fully utilized. In this approach, technological opportunities for RIs are identified by measuring the value of technological novelty (VON) of each technology manifested in a patent set, and the value of difficulty (VOD) of each R&D theme contained in the patent set. Specifically, VONs are calculated through a novel map of technological changes over time, based on structured data from the patent set; and VODs are determined using natural language processing, K-means cluster analysis, and complex network analysis of the unstructured data from the patent set. The feasibility and operability of the proposed approach are verified in a case study of unmanned aerial vehicles. The proposed approach can help designers maximize the use of designs and expert knowledge in patent libraries, to formulate technical strategies for RIs.

This paper investigates the relevance of patents as a competitive advantage with regard to the luxury industry. Within the framework of an explorative research design, more than two thousand patents were analyzed, using the international patent classification (IPC) to cluster those patents. The analysis shows that the sole ownership of patents as a resource is not sufficient to achieve business success. In addition, the findings suggest a two-sided relevance of patents within the luxury goods industry as two main groups can be identified: First, traditional manufacturers focusing more on craftmanship, secrecy, and tradition than on novelties and patents. Second, large business groups and high technology businesses dominating the IPC group G04 and emphasizing on the latest technology as well as on patents. Furthermore, the internationalization is also reflected in the patent applications: European patents within category G04 have gained in importance over the last 20 years, while national patents have declined. [ABSTRACT FROM AUTHOR]

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Patent bibliometrics data are the most reliable business performance metric for applied research and development activities when investigating the knowledge domains or the technological evolution of vehicle powertrain technologies in the automotive industry. Our paper describes a global patents dataset for the internal combustion engine vehicles (ICEV), hybrid electric vehicles (HEV) and battery electric vehicles (BEV) over 1985–2016. We extracted the patents granted in each powertrain field from Thomson Reuters' Derwent Innovations Index (DII). We applied a combined search strategy of international patent classifications (IPCs) and keywords as well as ‘patent families’ and ‘priority dates’ to construct our global patents dataset. This strategy returned a total of 78,732 patents, within which we identified 49,154 ICEV patents; 10,888 HEV patents; and 18,690 BEV patents. Our database includes numerous descriptive features of each patent such as title, abstract, claim, priority, application and publication dates, IPCs, assignees/applicants, inventors, and cited references. These data are associated with the research article ‘The evolution of dynamic interactions between the knowledge development of powertrain systems’ [1]. The full dataset, which is attached to this article, may be useful to both researchers and practitioners interested in investigating, modelling or forecasting the complexity and evolution of the technical and knowledge domains of the vehicle powertrains, across a variety of instruments such as social network analysis and regression models.

In Brazil, according to reports from the National Petroleum Agency - ANP, up to 2017, 41,984 automotive fuel dealer outlets were registered, showing that a big amount have leakage problems causing contamination of soil and groundwater, as well as occupational exposure to hydrocarbons. BTEX compound (benzene, toluene, ethyl benzene and xylenes) has been a major concern due to health problems resulting from direct and indirect ingestion. The objective of this work was to characterize the scenario of technologies used in the manufacture of low pressure tanks by outlining the methods that seek to promote tightness during its use. Data were collected by patent mining and subsequent prospecting in the Questel Orbit database. The presence of 67 industrial patent registrations directly related to the process that aim to prevent the leakage of the internal organic fluid to the low pressure tanks used in fuel resale stations was observed, with main codes of the International Patent Classification (IPC) B60S-005/02 (13 Records) and G01M-003/26 (13 Records), the main areas of study being Engineering and Transportation. [ABSTRACT FROM AUTHOR]

The analysis of the trends and structure of patenting developments in the field of biotechnologies is carried out. The study is based on the information contained in the databases of WIPO (World Intellectual Property Organization), which was used for international comparisons, and “Inventions (Utility Models) in Ukraine” of the Ukrainian Institute of Intellectual Property, which was used for a detailed study of patented developments at the national level. The analysis of patenting the Ukrainian developments for the period of 2000-2015 showed a weak patent activity of Ukraine at the international level. The largest number of active patents on biotechnology granted by the State Service for Intellectual Property of Ukraine to Ukrainian holders belongs to the subclass C12N – “Microorganisms or enzymes; their compositions; reproduction, preservation or storage of microorganisms; mutations or genetic engineering; nutrient media” and amounts to 315. In the structure of patents in the field of biotechnology with the C12N index that are owned by Ukrainian organizations, there prevail state scientific institutions of the NAS of Ukraine and UAAS (Ukrainian Academy of Agrarian Sciences). Representatives of the business sector among the patent holders are almost absent. Among the foreign patent holders the opposite trend is observed — representatives of business structures are leading. Thus, the prospects for the development of biotechnology in Ukraine depend considerably on intensifying the cooperation of scientific institutions with business, which should become a priority area of the state scientific and technical policy.

The objective of this paper is to analyze the impact of the factors that stimulate inspiration in the design process. An empirical study is proposed in this paper. Three factors were summarized, including knowledge, knowledge relations and innovative strategies. Representations of these three factors that were extracted from the international patent classification (IPC) were analyzed. An experimental scheme was designed, where 40 undergraduate students were selected as subjects and divided into five groups. One group was used as the control group with no materials provided, and the other four groups were used as the experimental subjects. The three factors and their combinations were provided to each of the four experimental groups. Subjects in each group were asked to propose preliminary designs of a coin-sorting device. The submitted designs were evaluated based on the novelty and practicality of the innovation. By comparing the groups, the impact of each factor on inspiration could be analyzed. The results show that the verb knowledge in the IPC has a significant impact on stimulating inspiration. For untrained students lacking experience, innovative strategies have a negative impact on the novelty of the inspiration. The knowledge relations can overcome the negative impact on the novelty induced by the innovative strategies. [ABSTRACT FROM AUTHOR]

Technological Convergence (TC) reflects developmental processes that overlap different technological fields. It holds promise to yield outcomes that exceed the sum of its subparts. Measuring emergence for a TC environment can inform innovation management. This paper suggests a novel approach to identify Emergent Topics (ETopics) of the TC environment within a target technology domain using patent information. A non-TC environment is constructed as a comparison group. First, TC is operationalized as a co-classification of a given patent into multiple 4-digit IPC codes (≥2-IPC). We take a set of patents and parse those into three sub-datasets based on the number of IPC codes assigned 1-IPC (Non-TC), 2-IPC and ≥3-IPC. Second, a method is applied to identify emergent terms (ETs) and calculate emergence score for each term in each sub-dataset. Finally, we cluster those ETs using Principal Components Analysis (PCA) to generate a factor map with ETopics. A convergent domain – 3D printing – is selected to present the illustrative results. Results affirm that for 3D printing, emergent topics in TC patents are distinctly different from those in non-TC patents. The number of ETs in the TC environment is increasing annually. • We present an approach to identify emergent topics of Technological Convergence (TC). • Principal Components Analysis clusters the emergent terms into one emergent topic. • Emergent topics of the TC have a broader range than those of the non-TC. [ABSTRACT FROM AUTHOR]

This paper aims to analyze the performance of Traditional Knowledge Digital Library (TKDL) in the protection of traditional knowledge and the interests of the indigenous people. The core of the paper is to analyze the various problems which are associated with TKDL. These problems are divided into five broad groups, these groups are Problem of treating traditional knowledge as property, Substantive Legal Problems, Procedural Problems, Problem of the Closed Access Model and lastly the Economic problems. Of all these problems the first one is against the idea of TKDL itself while the others are trying to find fault with the structure and working of TKDL. After analyzing all these problems the conclusions which emerge are that there is a need to find a balance between utilization of resources for the protection of the rights of the traditional communities so that they are empowered to ensure that their knowledge is not abused and utilization of resources for a TKDL because this database will play an important role in protection of the rights of the traditional communities once it shortcomings have been overcome. [ABSTRACT FROM AUTHOR]

Purpose/Thesis: The article analyses patent applications for inventions in the area of electronic publishing. Its investigates how the number of patent applications changed in the years 2014--2018, which companies were the most active in the field, and what was their providence. The issues of crucial importance to the inventors were identified by the study of the symbols used by International Patent Classification. Approach/Methods: The analysis was based on the data from the base Lens.org from years 2014--2018. In total, 1733 patent applications related to electronic publishing were identified. Results and conclusions: The study recorded an increasing activity of Chinese and Korean inventors, and a low number of patent applications filed by European firms. The applicants focus on specific functions facilitating interaction between the user and digital devices; a relatively high number of applications is concerned with electronic commerce, and with the use of electronic publishing in education. Originality/Value: An analysis of patent applications may help to identify specific phenomena occurring in the field of information technologies. It records the recent trends in research, and identifies the countries and agents which lead the development of widely understood electronic publishing. [ABSTRACT FROM AUTHOR]

International Patent Classification (IPC) was created for the purpose of sorting inventions and their documents into technical fields covering all areas of technology. Introduced in 1968, the IPC is used by all IP offices worldwide. IPC can be effective for searching patents worldwide under the condition that "each IP office provide IPC with the same quality." The authors conducted an international comparison on IPCs among IP offices, by analyzing patents by JPO, USPTO, EPO, CNIPA, and KIPO, which account for about 80% of the worldwide patent publications. The result shows especially that searching Chinese patents by IPC is difficult for the searchers/examiners in the United States and Japan, and vice versa. In the case that each IP office classifies patents by its own standard apart from other IP offices' standards, the important feature is lost in the process of classification of technical idea described in the patent. It means that even if IP offices share the common international language (like IPC) that everyone deeply comprehends, the key feature of the invention may be lost in translation into the common language. Moreover, in discussion part, a search method without patent classifications has been considered for the future plan. [ABSTRACT FROM AUTHOR]

Despite the rapid development of Chinese construction industry, there has been little research effort directed towards exploring patent cooperative patterns and evolution trends of construction enterprises, especially from the perspective of the patent development network. This paper extracts implicit collaborative information and introduces Social Network Analysis (SNA) method to conduct the patentometric analysis based on patent data from the "Top 500 Chinese Construction Enterprises" sourced from PatSnap database. The enterprise-enterprise networks and enterprise-university networks are analyzed quantitatively. The results reveal that: 1) there is a rising trend in the number of patents and patentees; 2) state-owned enterprises play a dominant role in patent development; 3) most of patents are classified as International Patent Classification E04G21; 4) the cooperative relationships are mainly within enterprises and their subsidiaries; 5) when enterprises choose to cooperate with universities, in addition to professional qualification, geographical factors should also be considered. Finally, the development and patent evolution trends are discussed. Some useful suggestions are proposed. The contribution lies in: (a) providing a visualization of the implicit collaboration information of patents in Chinese construction enterprises; (b) revealing cooperative patterns of construction enterprises on patents; and (c) providing enterprises some useful suggestions for patent cooperation. [ABSTRACT FROM AUTHOR]

Abstract This paper proposes a method to identify business diversification opportunities for a company. In particular, the method uses M&A cases related to business diversifications to identify atypical diversification opportunities. The underlying idea of the method is that industrial sectors of companies acquired by acquiring companies having similar characteristics with the focal company can be business diversification directions for the company. Industrial sectors of companies are identified by using IPC(International Patent Classification)-ISIC(International Standard Industrial Classification) concordance, and we updated the previous concordance to reflect the recent technological and business environments. For verification of the method, we used a successful M&A case related to business diversification and tested that the method can identify same industrial sector with the case as top priority. The results show that the method identified the same industrial sector as top ranking and other uncommon industrial sectors as recommended opportunities. Highlights • The proposed method identifies business diversification opportunities by using M&A and patent data. • M&A cases on business diversification are used as the key information to link a company to uncommon business sectors. • We updated the existing IPC-ISIC concordance to reflect recent technological and business environments. • The empirical analysis shows that the method well identifies atypical business diversification opportunities. [ABSTRACT FROM AUTHOR]

Semiconductors are among the most important core technologies contributing to the Fourth Industrial Revolution. The United States, Taiwan, and China have been investing heavily in semiconductor research and development. To achieve international competitiveness in the semiconductor industry, Korea needs to establish a research and development (R&D) roadmap for small- and medium-sized enterprises (SMEs). Our study identified trends in the semiconductor industry by analyzing the characteristics of core technologies based on patents that disclose technologies instead of holding exclusive ownership. Specifically, we analyzed registered patents concerned with artificial intelligence and machine learning pertaining to the semiconductor industry, which are attracting considerable attention. Using the Korea Intellectual Property Rights Information Service database, we identified 3569 patent specifications related to AI technology and the semiconductor industry. The text mining and network analysis results indicated that the application of deep neural networks is the most important and affects various aspects of R&D. Particularly, AI technology is actively studied for monitoring manufacturing and etch processes. Additionally, technology convergence among virtual reality, visualization, smart factories, and etching technology was identified. The analysis results identify promising technologies related to semiconductors and provide insights that would enable SMEs in the Korean semiconductor industry to establish a technology roadmap. • We identify technology trends suited for small-/medium-sized semiconductor companies. • Patent data were analyzed and related to predict upcoming profitable technologies. • The semiconductor industry is adopting solutions based on artificial intelligence. • Process monitoring and etching provide unique opportunities for competitiveness. • Solutions in the medical field seem promising for next-generation semiconductors. [ABSTRACT FROM AUTHOR]

Wind energy patents are conventionally defined using Cooperative Patent Classification (CPC) and International Patent Classification (IPC) codes that represent wind motors (F03D) and wind energy (Y02E 10/70). This study examines whether these codes sufficiently represent the wind energy patent domain. Using a combination of keywords and classification codes identified through expert input and manual review, we construct an expanded domain with a 7.5% increase in patent count, a 6% increase in recall, and only a 1% decrease in precision for wind energy patents. We also found that the conventional domain is not unbiased; it underrepresents patenting from China and patents published since 2010. This is important because an improved patent domain allows for a holistic patent data set, which is necessary to complete a thorough analysis of the wind industry. Through this wind energy application, we extend our methodology to form a generalized patent search process that can be used to target technology domains within a patent data set. • Our methodology improves patent retrieval with keywords and codes identified through expert input and manual review. • Improved wind energy domain observed 7.5% increase in patent count, 6% increase in recall, and only 1% decrease in precision. • Patents retrieved using conventional codes for wind energy underrepresent patents from China and published since 2010. • Methodology for wind energy application can be generalized for patent searching to target other technology domains. [ABSTRACT FROM AUTHOR]