The combination of the disciplines of techmining and semantic triz for better and faster analyzing technology evolution

Resumen

The purpose of the present thesis is to explore and to demonstrate how the combination of two methodological approaches, text mining plus the systemic vision of TRIZ empowered by semantics, can bring a larger and more comprehensive analysis of the evolution of a technology. Both approaches had been not combined before the first of the four papers constituents of the present thesis based in a compendium of publications. However, this combination applied to the evolution of technologies is increasingly being published in the scientific literature. Such combination shows a second benefit in the form of an improvement in accessing and connecting knowledge from disparate scientific literatures in a systematic manner. The common element in all these papers is the use of the technology mining approach, 'techmining', the application of text mining techniques based on technology management knowledge, combined with the use of semantic TRIZ, the advantage of syntactic applied to the systemic vision of TRIZ. These papers show that a better analysis of evolving technologies, e.g. by profiling technologies from a systemic point of view or, a better access to knowledge, e.g. by semantically connecting concepts with meaning, can be achieved. The research on applying the combination of these approaches to scientific and technological information analysis explores the advantages and new possibilities for technology trends assessment as well as the semantic connection of concepts which represents a change in the way information research can be done. The different applications of the aforementioned combination are explored by means of the here presented articles. The structure followed in this research is the collection of three papers published in international academic journals indexed in the most prestigious databases and one chapter in a proceedings book of an international congress. The attached articles show the research undertaken to demonstrate the aforementioned benefits of the proposed combination. Despite it can be found many methods and approaches about the assessment of the evolution of technologies, distributed across the literature, there is still a need to better understand which technologies may emerge, which may evolve faster and at what pace can they reach the market. The combination of the techmining approach and the semantic TRIZ approaches allows understanding the trends enriched with a systemic vision of the links, functions, and influences of constituent and enabling elements of a technology. Such systemic link of elements with its components and ecosystem also allows for a multi-dimensional view of a technology and further reduces the uncertainty to preview the progress of a technology. The papers presented in this dissertation are based on the combination of the TRIZ methodology, the techmining approach and the semantic TRIZ approach, applied to different technologies in different domains, to proof the advantages and implications of the combination. The articles try the different interactions of the combined approaches, applied to the assessment of different technologies, such as lithium batteries for the electric car, a medical case linked to a disease known as Meniére's Disease, the prognosis of prostate cancer, and the usage of probiotics as substitutes of antibiotics in the animal health. The wide range of technologies was selected to show the clear benefits of either combining the two approaches or applying predominantly one of them in the case of the Meniére's disease article. That difference in the nature of technologies also helped to better understand the systemic point of view of the technology, exploring new applications based on the general system theory from Bertalanffy as well as other related approaches about technologies.