Patent Classification Research Articles

Microbial bioremediation of oil contaminated seawater: A survey of patent deposits and the characterization of the top genera applied

Petroleum has been the world's major source of energy since the middle of the twentieth century, leading to positive changes but also social, political, and environmental problems worldwide. Oil contamination affects all ecosystems, and the remediation of polluted sites using environmentally friendly strategies is crucial. Here, we report an analysis of the patent documents of potential petroleum bioremediation techniques that use microbes to clean seawater. The patent search was performed using Orbit Intelligence®, SciFinder® and the Derwent World Patents Index®. A group of 500 patent documents were validated according to the search objective and carefully studied. Increases in patent deposits coincide with periods following widely reported oil spills, suggesting a relationship between media disclosure and stimulation of innovation activities. China leads the list of countries with patent applications in bioremediation with 152 deposits, followed by Russia with 133 and the US with 48. These three countries have completely different temporal deposit profiles, influenced by their historical, political, and economic scenarios. A total of 368 patents described degradation of the oil compounds exclusively by bacteria, 24 by fungi and yeasts, 1 by Archaea, 1 using a microalgal strain, and 32 by mixed consortia. The leading microbial genera found in the patents are Pseudomonas (114 patents), Bacillus (75), and Rhodococcus (60). In the top-10 list of microbial strains mostly cited/claimed, no genera are obligate hydrocarbonoclastic bacteria. This fact, together with the broad pattern found in the main International Patent Classification (IPC) codes, suggest that most of the documents are general bioremediation approaches and not focused on oil-polluted seawater. This work highlights the importance of stimulating the development of innovative environmentally friendly strategies focused on the degradation of oil hydrocarbons in marine ecosystems.

BRIEF OF AMICI CURIAE INTELLECTUAL PROPERTY AND INNOVATION PROFESSORS, ENGINE ADVOCACY, AND THE R STREET INSTITUTE IN SUPPORT OF PETITIONERS, Hikma Pharms. USA Inc. v. Vanda Pharms. USA Inc., No. 18-817 (U.S. Supreme Court)

The Federal Circuit’s decision below directly conflicts with this Court’s patentable subject matter precedent by upholding patent claims to routine, conventional applications of a law of nature. If allowed to stand, the decision will eviscerate this Court’s unanimous and repeated determinations that such claims lack the “inventive concept” that is required of patentable subject matter. Alice Corp. Pty. Ltd. v. CLS Bank Int’l., 573 U.S. 208, 217 (2014); Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66, 72 (2012). The divided Federal Circuit panel held the claims at issue here were not “directed to” a law of nature because they claim a “specific method of treatment.” Pet. App. 35a. This interpretation of the term “directed to” is incompatible with the Court’s usage in Alice, 573 U.S. 208. It is also directly at odds with the Court’s invalidation of the method-of-treatment claims at issue in Mayo, 566 U.S. 66, on patentable subject matter grounds. The Mayo decision reaffirmed the principle that patentability requires more than simply directing a practitioner to apply an otherwise ineligible natural law in a “routine, conventional” way. 566 U.S. at 73. The panel in this case sought to distinguish Mayo on the grounds that the patent at issue explicitly recites the step of adjusting a drug dose in applying a natural law, whereas the dose adjustment was merely implicit in the claims invalidated in Mayo. This distinction is untenable, as it depends on the “draftsman’s art,” Alice, 573 U.S. at 224, and ignores this Court’s repeated ruling that mere specificity is not sufficient to transform a natural law into patent eligible subject matter. Mayo, 566 U.S. at 88-89 (citing Parker v. Flook, 437 U.S. 584 (1978)). The Federal Circuit is obligated to follow this Court’s guidance by elaborating the limits on 35 U.S.C. § 101 patent eligible subject matter in a manner that conforms with the legal interpretation and rationale set out in this Court’s precedents. The decision below shirks that duty. This Court has adopted a two-step framework for analyzing patentable subject matter in order to ensure that patents are awarded only to claims that add an “inventive concept” to the underlying natural law. The Federal Circuit majority’s interpretation of this analysis would render this framework toothless because no method of treatment applying a discovered law of nature would ever be considered “directed to” that law of nature, regardless of whether the claim adds only “well-understood, routine, conventional activity” to the otherwise-ineligible subject matter. Mayo, 566 U.S. at 73. The harmful consequences of this decision are real and immediate. The U.S. Patent and Trademark Office (USPTO) has issued guidance that explicitly adopts the reasoning of the majority’s holding and instructs examiners that “method of treatment” claims that apply natural relationships should be considered per se eligible subject matter so long as integrated into a practical application — such as a treatment claim — even if that application is uncreative, routine, or conventional, once the ineligible discovery has been made. This guidance, like the decision below, ignores the standards of § 101 articulated by this Court for patentable subject matter in general and for medical treatment patents in particular. Moreover, the reasoning of the decision below need not apply only to medical treatment patents. It is thus likely that the decision’s erroneous interpretation of “directed to” will be extended to other classes of patents, enabling clever patent drafters to avoid the critical second step of this Court’s patent eligible subject matter analysis. The decision below is exceptionally important. The Federal Circuit’s and USPTO’s disregard of Mayo and Alice are unmistakable and growing. Review and correction by this Court are vital now, before the harmful effects of the decision and its implementation by the USPTO become widespread. Only immediate review will prevent thousands of ineligible patents from being improperly issued and improperly upheld in the courts below and remaining in effect until some potential future opportunity for this Court to consider and invalidate them. Left uncorrected, the Federal Circuit’s decision and the USPTO guidance based on it will allow the piecemeal appropriation of the public domain. Patent law carefully limits the subject matter of patents to ensure the existence of a robust and unrestricted public domain for routine and conventional uses of the laws of nature, even if those laws are newly discovered. Patents must not be allowed to monopolize the basic ideas and natural laws that provide the foundation for medical innovation, research and treatment. If they do, downstream innovation will be hampered or blocked and vital medical practices and decisions will face undue interference.

The impact of competition strength and density on performance: The technological competition networks in the wind energy industry

Technological competition plays an important role in technological development and innovation. However, technological competition networks have long been ignored in research. Based on the social network theory, we proposed that the innovation of an organization is greatly affected by the technological competition networks that it is embedded in. We introduced International Patent Classifications (IPCs) information to construct technological competition networks of organizations, and explored how competition network characteristics influence the organizational competitive capability and innovation performance.Based on the wind energy patent data between 2005 and 2014, we synthetically investigated the technological development and competition networks in the industry. Our findings show that (1) the evolutionary trends of patents and technology elements growth exhibit similar patterns (i.e., increasing before 2011 and decreasing after 2011); (2) the burst detection algorithm detects that 140 technological elements and 132 organizations experienced a sudden growth in production; (3) wind energy organizations intensively compete with each other, and in each year, only 10% of organizations can improve their technological competitive positions in the following year; (4) competition density in a competition network increases the technological competitive capability and innovation performance of firms. Additionally, competition strength has an inverted-U shaped relationship with both the aforementioned outcomes.

How to Measure and Draw Causal Inferences with Patent Scope

This paper presents an easy-to-use measure of patent scope that is grounded both in patent law and in the practices of patent attorneys. We validate our measure by showing both that patent attorneys’ subjective assessments of scope agree with our estimates, and that the behavior of patenters is consistent with it. Using our validation exercise, we find that previous measures of patent scope (i.e., the number of patent classes, the number of citations made by future patents, and the number of claims in a patent) are uninformative or misleading. To facilitate drawing causal inferences with our measure, we show how it can be used to create an instrumental variable, patent examiner scope toughness, which we also validate. We then demonstrate the power of this instrument by examining standard-essential patents. We show that an (exogenous) diminishment of patent scope leads to patents being much less likely to be declared standard essential.

Áreas do conhecimento em que as universidades do Sul do Brasil possuem patentes concedidas

O estudo tem como objetivo geral analisar as patentes concedidas nas universidades públicas do Sul do Brasil no que se refere às áreas do conhecimento – de onde provêm, e em quais áreas elas são classificadas de acordo com a Classificação Internacional de Patentes - e como objetivos específicos mapear as universidades públicas do Sul do país e suas patentes; identificar as áreas da Classificação Internacional de Patentes e as áreas do conhecimento do Conselho Nacional de Desenvolvimento Científico e Tecnológico, às quais as patentes pertencem; e estabelecer relação de contribuição que cada área do conhecimento do Conselho Nacional de Desenvolvimento Científico e Tecnológico realiza em cada área da Classificação Internacional de Patentes. O levantamento das patentes foi realizado na base de dados do Instituto Nacional da Propriedade Industrial. De posse do número da classificação, realizou-se o cruzamento com as áreas do conhecimento da tabela do Conselho Nacional de Desenvolvimento Científico e Tecnológico. Os resultados reuniram 11 universidades públicas que apresentaram 68 patentes concedidas. A seção da Classificação Internacional de Patentes que apresentou maior número de concessões de patentes foi a “C - Química; Metalurgia”, com 25 registros. As áreas de conhecimento do Conselho Nacional de Desenvolvimento Científico e Tecnológico que publicaram na seção foram: Bioquímica, Engenharia Civil, Engenharia de Materiais e Metalúrgica, Engenharia Química, Engenharia Sanitária e Química. A grande área "Engenharias" foi a que obteve o maior volume de patentes, totalizando 24. A formação dos inventores mais produtivos, que pertencem à Universidade Federal do Rio Grande do Sul, concentrou-se na área de Química.

Big Data Analytics for Venture Capital Application：Towards Innovation Performance Improvement

By using the panel date of Chinese enterprises, this paper analyzes the influence of venture capital on innovation performance. In this paper, the number of patent application and the patent quality(invention patent applications, number of effective patents, IPC number of international patent classification, and patent claims) are used to measure the innovation performance of enterprises, and the regression results show that the innovation performance is significantly promoted by the venture capital; for industries with higher dependence on external financing and high technology intensity and areas with better protection of property rights, venture capital promotes innovation performance more significantly. In this paper, it further distinguishes the characteristics of venture capital institutions, and finds that the promotion effect of non-state-owned venture capital on innovation performance is significantly greater than that of state-owned venture capital; the venture capital institutions with high reputation and high network capital play a more significant role in promoting innovation performance.

Patent Review on Laser Interference Lithography Technique for Producing Periodic Nanostructure.

Because line width has been close to atom size, for semiconductor industry, except for achieving the target of line width, the cost will be more important. The mask-less laser interference lithography (LIL) technique lowers the cost makes it standing out in the market of lithographic equipment of the excessive cost in the semiconductor industry. The Keywords of patent retrieval with the theme of LIL are based on the technical features of both the conditions of producing interference lithography and different types of experimental configuration of LIL. Method of patent retrieval include Boolean logic operators are used to express the relationship between sets. Furthermore, it's necessary to find whether common patent classification codes exist in the highly correlated patents and confirm the definition of that. The patent review in this research show the patents of LIL technique are classified according to optical method and lithographic equipment. The patents related to optical method of LIL technique take beam splitter based configuration as the main stream; in the technique of lithographic equipment, the patents of system planning technique are the most. The findings of this review confirm the importance of improving the precision of LIL technique for avoiding the defocus of high-density line width. Besides, it's particularly suitable for the micro nanofluid device in the emerging bionanotechnology to observe fluid behavior at the minimum scale. It doesn't need mask and can produce periodic pattern with nanoscale make it devote to the field of periodicity.

Ontology-based heuristic patent search

PurposeLarge collections of patent documents disclosing novel, non-obvious technologies are publicly available and beneficial to academia and industries. To maximally exploit its potential, searching these patent documents has increasingly become an important topic. Although much research has processed a large size of collections, a few studies have attempted to integrate both patent classifications and specifications for analyzing user queries. Consequently, the queries are often insufficiently analyzed for improving the accuracy of search results. This paper aims to address such limitation by exploiting semantic relationships between patent contents and their classification.Design/methodology/approachThe contributions are fourfold. First, the authors enhance similarity measurement between two short sentences and make it 20 per cent more accurate. Second, the Graph-embedded Tree ontology is enriched by integrating both patent documents and classification scheme. Third, the ontology does not rely on rule-based method or text matching; instead, an heuristic meaning comparison to extract semantic relationships between concepts is applied. Finally, the patent search approach uses the ontology effectively with the results sorted based on their most common order.FindingsThe experiment on searching for 600 patent documents in the field of Logistics brings better 15 per cent in terms of F-Measure when compared with traditional approaches.Research limitations/implicationsThe research, however, still requires improvement in which the terms and phrases extracted by Noun and Noun phrases making less sense in some aspect and thus might not result in high accuracy. The large collection of extracted relationships could be further optimized for its conciseness. In addition, parallel processing such as Map-Reduce could be further used to improve the search processing performance.Practical implicationsThe experimental results could be used for scientists and technologists to search for novel, non-obvious technologies in the patents.Social implicationsHigh quality of patent search results will reduce the patent infringement.Originality/valueThe proposed ontology is semantically enriched by integrating both patent documents and their classification. This ontology facilitates the analysis of the user queries for enhancing the accuracy of the patent search results.

Discovering business diversification opportunities using patent information and open innovation cases

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.

Technology convergence capability and firm innovation in the manufacturing sector: an approach based on patent network analysis

As a consequence of the convergence between manufacturing technology and the foundation technologies of Industry 4.0, it is becoming more important for firms to formulate an innovation strategy for their technological capabilities. In this context, the present study measures firm‐level technology convergence (TC) capability using patent network analysis. A firm’s TC capabilities are measured using three centrality indices pertaining to a patent network, which is constructed based on the relationship between patents and their international patent classification. For the empirical analysis, panel regression is conducted to observe the effect of TC capabilities on innovation for the top 30 firms in four manufacturing industries. We find that the TC degree positively influences the firms’ overall innovation, namely their total number of patents, and negatively influences their convergent innovation, calculated as the ratio between the number of TC patents and the total number of patents, while the effect of TC betweenness is the opposite. These findings imply that while concentrating on similar technologies may promote quick technology application, it could hamper the enhancement of a TC’s potential. To promote TC, a firm should thus develop technologies more likely to be involved in TC.

Technology Evolution in Membrane-Based CCS

In recent years, many CO2 capture technologies have been developed due to growing awareness about the importance of reducing greenhouse gas emissions. In this paper, publications from the last decade addressing this topic were analyzed, paying special attention to patent status to provide useful information for policymakers, industry, and businesses and to help determine the direction of future research. To show the most current patent activity related to carbon capture using membrane technology, we collected 2749 patent documents and 572 scientific papers. The results demonstrated that membranes are a developing field, with the number of applications growing at a steady pace, exceeding 100 applications per year in 2013 and 2014. North American assignees were the main contributors, with the greatest number of patents owned by companies such as UOP LLC, Kilimanjaro Energy Inc., and Membrane Technology and Research Inc., making up 26% of the total number of published patents. Asian countries (China, Japan, and Korea) and international offices were also important knowledge sources, providing 29% and 24% of the documents, respectively. Furthermore, this paper highlights 10 more valuable patents regarding their degree of innovation and citations, classified as Y02C 10/10 according to the Cooperative Patent Classification (CPC) criteria.

Fast and Accurate Patent Classification in Search Engines

This article presents a new approach to large scale patent classification. The need to classify documents often takes place in professional information retrieval systems. In this paper we describe our approach, based on linguistically-supported k-nearest neighbors. We experimentally evaluate it on the Russian and English datasets and compare modern classification technique fastText. We show that KNN is a viable alternative to traditional text classifiers, achieving comparable accuracy while using less additional hardware resources.

Inter‐firm R&D collaborations and green innovation value: The role of family firms' involvement and the moderating effects of proximity dimensions

AbstractThe present paper investigates the relationship between the involvement of family firms in R&D collaborations aimed at developing green solutions and the value of resulting innovations. To dig into this relationship, the moderating effects of two proximity dimensions (i.e., geographical distance and technological relatedness) are also assessed. Analyses are based on a sample of 156 joint patents classified into the “Alternative energy production” field, as defined by the International Patent Classification Green Inventory and successfully filed at the United States Patent and Trademark Office in the period 1997–2010 by publicly listed companies. According to our conjectures, results reveal a positive relationship between the involvement of family firms and green innovation value. Moreover, our findings show that this relationship is hindered when partners are geographically distant or technologically proximate. Eventually, we contribute to the literature on green innovation by unveiling under which conditions inter‐firm R&D collaborations lead to more valuable innovations.

Use of patents as a tool to map the technological development involving the hydrogen economy

The use of fossil fuels favors the emission of greenhouse gases (GHG). With that in mind, there is a growing need to find sustainable energy options for the transport sector. Hydrogen appears as a potential substitute for fossil fuels. In this way, the objective of this study is to map the hydrogen economy through the patent consultation in the period 1998–2018. The documents found were tabulated in order to characterize the technological advance over the 1998–2018, showing countries that publish and priority patents and the major assignees. This time range was chosen due to the fact that prior to 1998 the number of patents for these technologies was not significant. The searches were conducted on the Questel Orbit platform. Data were filtered using some keywords and the International Patent Classification (IPC). The results show that Japan and United States are the countries with the highest number of patent families by priority. This fact indicates that there are expressive efforts for the technological advance, thus contributing, to be the countries that stand out in these technologies. This research shows that the assignees with the highest number of patents families by priority are Toyota Motor and Honda Motor.

DeepPatent: patent classification with convolutional neural networks and word embedding

Patent classification is an essential task in patent information management and patent knowledge mining. However, this task is still largely done manually due to the unsatisfactory performance of current algorithms. Recently, deep learning methods such as convolutional neural networks (CNN) have led to great progress in image processing, voice recognition, and speech recognition, which has yet to be applied to patent classification. We proposed DeepPatent, a deep learning algorithm for patent classification based on CNN and word vector embedding. We evaluated the algorithm on the standard patent classification benchmark dataset CLEF-IP and compared it with other algorithms in the CLEF-IP competition. Experiments showed that DeepPatent with automatic feature extraction achieved a classification precision of 83.98%, which outperformed all the existing algorithms that used the same information for training. Its performance is better than the state-of-art patent classifier with a precision of 83.50%, whose performance is, however, based on 4000 characters from the description section and a lot of feature engineering while DeepPatent only used the title and abstract information. DeepPatent is further tested on USPTO-2M, a patent classification benchmark data set that we contributed with 2,000,147 records after data cleaning of 2,679,443 USA raw utility patent documents in 637 categories at the subclass level. Our algorithms achieved a precision of 73.88%.

Supporting global initiatives on climate change: The EPO's “Y02-Y04S” tagging scheme

The EPO has developed a dedicated classification scheme for climate change mitigation technologies (CCMTs), where relevant patent publications are “tagged” and classified into a separated scheme which is fully integrated within the Cooperative Patent Classification (CPC). This allows for non-patent experts to search for climate change-related technologies in a more user-friendly fashion. The scheme has been continually expanded in recent years and is now considered complete for CCMTs, covering seven main categories, namely energy, greenhouse gases (GHG) capture, buildings, industry (including agriculture), transport and waste and wastewater management. A classification scheme for smart grids, Y04S (a spin-off of Y02), has been also developed. Both classifications ease the access to patent documentation in sustainable technologies. An overview of the structure of the Y02/Y04S scheme is presented together with examples of how this can be used (i) to find relevant technologies and their owners and (ii) to provide technical, legal and business information to support strategic decision-making in the field of climate change.

Analysis of the patent documentation coverage of the CPC in comparison with the IPC with a focus on Asian documentation

In this study we analyse the patent documentation coverage of the Cooperative Patent Classification system (CPC) in comparison with the coverage of the International Patent Classification system (IPC). We demonstrate that for patent searchers the coverage in terms of patent families is more relevant than the coverage in terms of patent documents. Of all the patent families classified in the IPC only about one third thereof is currently classified in the CPC. Most of the patent families that are not classified in the CPC are patent families including published patent applications filed at the three major Asian patent offices (JPO, KIPO and SIPO). We demonstrate a method of comparing the CPC patent documentation coverage to the IPC patent documentation coverage down to IPC subgroup level and how this can be applied to improve the efficiency of classification based search. The coverage of the CPC relative to the IPC must be understood in terms of: the CPC being assigned to families, and the IPC being assigned to individual documents. Furthermore, the CPC has only been implemented relatively recently compared to the IPC, with SIPO and KIPO focusing on the classification of their front files in the CPC.

Searching with combination sets in CPC: An efficient way to retrieve relevant documents

Combination sets can be allocated in a limited number of technical areas within the Cooperative Patent Classification (CPC) scheme. They provide a means of accelerating searches for relevant documents. The purpose of this paper is to highlight the efficiency of using such combinations of individual symbols for classification as well as for search.

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.

Community evolution in patent networks: technological change and network dynamics

When studying patent data as a way to understand innovation and technological change, the conventional indicators might fall short, and categorizing technologies based on the existing classification systems used by patent authorities could cause inaccuracy and misclassification, as shown in literature. Gao et al. (International Workshop on Complex Networks and their Applications, 2017) have established a method to analyze patent classes of similar technologies as network communities. In this paper, we adopt the stabilized Louvain method for network community detection to improve consistency and stability. Incorporating the overlapping community mapping algorithm, we also develop a new method to identify the central nodes based on the temporal evolution of the network structure and track the changes of communities over time. A case study of Germany’s patent data is used to demonstrate and verify the application of the method and the results. Compared to the non-network metrics and conventional network measures, we offer a heuristic approach with a dynamic view and more stable results.