Oct'20
Welcome to the IUP Journal of Knowledge Management
Focus
Knowledge management contributes to the development of several sectors like education, healthcare, business and technology. In the paper, "Knowledge Management in the European Union: Could It Improve Competitiveness?", the author, Magdolna Csath, highlights the importance of knowledge and its management for the development of a business and a country. The author also highlights the crucial role of knowledge management in making the European Union (EU) a knowledge-based and competitive region. The author focuses on the knowledge management practices in V4 (Visegrad Four) countries (Czechia, Hungary, Poland and Slovakia). Referring to the fact that knowledge management practices are not uniformly developed in the member states of EU, the author reports that there will be an imminent threat of imbalance in the development of the whole union. With the help of literature reports and statistical data derived from Eurostat, the author makes a statistical analysis of the problems in creating, managing and utilizing knowledge in the EU. The author concludes that the EU does not have an efficient knowledge management system, which is useful in capitalizing on the vast human skills available in the member states.
With the advances taking place in artificial intelligence and data science, Natural Language Processing (NLP) is aggressively growing. Different NLP applications are being developed in processing spoken or text messages to meet the analytical requirements of various fields, and they have the potential to be patentable in different countries like the US. Several big players including Google have already taken patents for their innovative NLP software systems and methods, and several patents are published covering the intended technical problems that are addressed therein. Brian Haney, in his paper, “Patents for NLP Software: An Empirical Review”, provides NLP patent analysis and review by addressing various issues, including novel software descriptions, market modeling and legal analysis relating to patent claims. The paper discusses the two main frameworks used for developing NLP systems-statistical models and knowledge models. It also presents an evolving NLP patent dataset with economic insights, analysis of legal claims and strategies for patent valuation.
Consulting Editor
Knowledge Management in the European Union: Could It Improve Competitiveness?
Knowledge is the currency for any nation as it can be used for achieving sustainable development and competitiveness. Knowledge has to be created, maintained and nurtured, in other words, managed. Knowledge management is a well-known practice for businesses, but it is less elaborated as theory and practice at the national or regional level. This paper argues that the objective of the European Union (EU) to become a knowledge-based and competitive region requires knowledge management throughout the region, which is not a tangible practice at present. The EU is interested rather in harmonizing industrial policy and financial and banking practices, and delegate knowledge creation and management to the member states. In conclusion, knowledge management practices are very different in the member states. In Central and Eastern Europe, for example, human resources are utilized for the advantage of the value chain operations of the corporations from the developed countries of the EU. This paper argues that a system with weak elements cannot be successful in the long run. Therefore, if Europe wants to be a harmoniously developing and competitive entity, it has to nurture and develop human capital in a balanced manner in every member country. Otherwise, parts of the Union will develop slowly, and may be stuck in the so-called middle income trap, creating not only economic but also social development problems for the EU.
Patents for NLP Software: An Empirical Review
Natural Language Processing (NLP) patents are one of the fastest growing niche segments in the technology patent marketplace. NLP technologies power the latest in Artificial Intelligence (AI) applications. For example, NLP technology supports Apple's Siri, Amazon's Alexa, and Facebook's friend recommendation system. Yet, while the literature on software patents is visibly scaling-the literature specifically focused on NLP patents is non-existent. This paper draws on a growing body of computational linguistics, intellectual property, and technology law scholarship to provide novel NLP patent analysis and critique. Further, this paper contributes the first empirical NLP patent review, including novel software descriptions, market modeling, and legal analysis relating to patent claims. First, this paper discusses the two main technical approaches to developing NLP software. Second, this paper models an evolving NLP patent dataset, offering economic insights, legal claims analysis, and patent valuation strategies.
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