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Welcome to the latest quarterly Literature Listing intended as a current awareness service for readers indicating newly published books, journal, and conference articles on IP management; Information Retrieval Techniques; Patent Landscapes; Education & Certification; and Legal & Intellectual Property Office Matters. The current Literature Listing was compiled February 2023. Key resources include Scopus, Digital Commons, publishers' RSS feeds, and serendipity! This article gives a selection of interesting references to whet your appetite - the full list of references can be found in the companion datafile.

The identification of relevant prior art for patent applications is of key importance for the work of patent examiners. The recent advancements in the field of natural language processing in the form of language models such as BERT enable the creation of the next generation of prior art search tools. These models can generate vectorial representations of input text, enabling the use of vector similarity as proxy for semantic text similarity. We fine-tuned a patent-specific BERT model for prior art search on a large set of real-world examples of patent claims, corresponding passages prejudicing novelty or inventive step, and random text fragments, creating the SEARCHFORMER. We show in retrospective ranking experiments that our model is a real improvement. For this purpose, we compiled an evaluation collection comprising 2014 pairs of patent application and related potential prior art documents. We employed two representative baselines for comparison: (i) an optimized combination of automatically built queries and the BM25 ranking function, and (ii) several state-of-the-art language models, including SentenceTransformers optimized for semantic retrieval. Ranking performance was measured as rank of the first relevant result. Using t-tests, we show that the achieved ranking improvements of the SEARCHFORMER over the baselines are statistically significant ($\alpha =0.01$).

Welcome to the latest quarterly Literature Listing intended as a current awareness service for readers indicating newly published books, journal, and conference articles on IP management; Information Retrieval Techniques; Patent Landscapes; Education & Certification; and Legal & Intellectual Property Office Matters. The current Literature Listing was compiled end-November 2022. Key resources include Scopus, Digital Commons, publishers' RSS feeds, and serendipity! This article gives a selection of interesting references to whet your appetite - the full list of references can be found in the companion datafile.

Innovations related to artificial intelligence (AI) can impact many technological fields and gather attention of several sectors from industry. Brazil is a developing country with a large territory and consumer market, attracting investment from foreign companies, including AI technologies. In the present work, we carry out a review of the Brazilian IP Law, Guidelines and Resolutions regarding patentability of AI inventions in Brazil, and also perform comparative analyses with the guidelines from the EPO and USPTO. Then, patent searches are carried out to analyze filing indicators of patent applications for AI inventions, wherein it is possible to verify that most of the filing applicants in Brazil are foreign companies, mainly from the US. Brazilian entities, which rank second overall in filing for patent applications in Brazil, do not even appear among the main applicants for AI inventions. We conclude that Brazil is not a competitive country in the production of patents related to AI, and it is important for Brazil to establish some degree of legal certainty regarding patent protection for AI inventions and disseminate knowledge about protecting such inventions by patents, so that inventors opt to disclose their AI inventions instead of keeping them as a trade secret. Therefore, more and more sectors of society might benefit from innovations arising from AI.

Generative language models are promising for assisting human writing in various domains. This manuscript aims to build generative language models in the patent domain and evaluate model performance from a human-centric perspective. The perspective is to measure the ratio of keystrokes that can be saved by autocompletion based on generative patent language models. A higher ratio means a more effective model which can save more keystrokes. This metric can be used to benchmark model performance. The metric is keystroke-based and different from conventional machine-centric metrics that are token-based. In terms of model size, the largest model built in this manuscript is PatentGPT-J-6B, which is state-of-the-art in the patent domain. Based on the metric, it is found that the largest model is not necessarily the best for the human-centric metric. The finding means that keeping increasing model sizes in the patent domain might be unnecessary if the purpose is to assist human writing with autocompletion. Several patent language models are pre-trained from scratch in this research. The pre-trained models are released for future researchers. Several visualization tools are also provided. The importance of building a generative language model in the patent domain is its potential to facilitate creativity and innovations in the future.

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

Efficient patentability searching demands that the searcher has the ability to identify efficiently the best sources of likely prior art for each invention being searched. This applies both within industry, at the point of drafting a patent application, and within patent offices conducting searches to support substantive examination. Industry 4.0 inventions are characterised by a particular nature and combination of technologies, notably the inclusion of aspects of Information and Communication Technologies (ICT). The default information sources currently used to establish patentability of ‘conventional’ inventions may be inappropriate for this new class of invention. This is partly due to the different structures of publication and methods of dissemination of research results found within computer science professions. It is suggested that searching in the secondary or tertiary literature may be a more fruitful approach to establish patentability in these areas of technology. However, expertise in the use of these types of source has been substantially lost, as the information industry has concentrated on production of full-text primary sources. Database production, database usage and search protocols all need to be reassessed if they are to meet the challenges of searching Industry 4.0 inventions.

This study investigates coopetition among the 16 semiconductor firms that figured among the top 10 by revenue from 2009 to 2019 using patent data obtained from the Derwent World Patents Index™ (DWPI), considering records available for the selected firms published and indexed up to July 26, 2020. Only 1791 (0.17%) records from a total of more than 1.1 million have two or more of these competing firms as assignees (i.e., they are records for joint patents involving these firms), indicating the existence of coopetition in this scenario. These joint patents demonstrate coopetition between firms from different countries and in the main areas in which their patents are classified, indicating that they may coopete in those areas. Furthermore, mergers and acquisitions and joint ventures may influence coopetition and innovation, resulting in joint patents. Finally, a framework that consolidates the main findings is presented to guide future research. We contribute to the coopetition literature with novel inputs. From a managerial perspective, the findings can be used to build strategies to better exploit the potential of patents.

This study presents an overview and a short critical review of patented antibiofilm technologies. Patent information was used to determine scenarios that could be used by decision-makers or business intelligence. The study found that academia, mainly from the USA, has been applying for the most patents since 1997. Based on the S-curve analysis, the maturity of this technology sector is emerging. The technological specialization for the 10 most prominent patent applicants and state-of-the-art antibiofilm patents are presented.

The high dispersion of patent applicants, the presence of universities among the most active patent applicants, and the content of the patents analyzed are good indicators to infer that developed technologies are close to the academic level. Moreover, many efforts are necessary to bring these technologies into the market.

Polymers-N-based, amino acids and peptides, P and S compounds, chelating agents and organometallic complexes, nanoparticles, or composites are claimed to be active against biofilm formation. Such compounds are presented in this work, and in rare cases, they are described as compositions ready for use as marketable products.

Managing intellectual property (IP) value appropriation remains a central challenge for business-to-business (B2B) networks due to B2B co-creation prospects for improved value-in-exchange and value-in-use for co-creation beneficiaries. This article aims to explore the management practices of B2B networks that enhance IP value from B2B co-creation. Using semi-structured interviews with sixteen IP management experts from the Kingdom of Saudi Arabia, the article proposes an integrated model of management strategies and guidelines for B2B co-creation with respect to IP value. The model posits that at the intra-organisational level, the main enabling processes for value appropriation are building communication skills, implementing hiring processes, and developing management systems for negotiations, talents, and intellectual assets, respectively. This level benefits from priorities placed on selecting strategic partners and fostering learning cultures for knowledge, technology, and venture co-creation processes. For the inter-organisational level, the proposed enabling processes are pursuing research funds and creating optimum designs for technology development and market positioning, respectively. Priorities at this level involve aligning complementary resources, developing clear agreements, and utilising supportive capabilities for technology and market co-creation.