A Novel Analytic Framework of Technology Mining Using the Main Path Analysis and the Decision-Making Trial and Evaluation Laboratory-Based Analytic Network Process

Tech mining is an analytical method of technology monitoring that can reveal technology trends in different industries. Patent databases are the major sources for information retrieval by tech mining methods. The majority of the commercially viable research and development results in the world can be found in patents. The time and cost of research and development can greatly be reduced if researchers properly analyze patents of prior arts. Appropriate analyses of patents also help firms avoid patent infringement while simultaneously developing new products or services. The main path analysis is a bibliometric method which can be used to derive the most dominant paths in a citation network of patents or academic works and has widely been adopted in tracing the development trajectory of a specific science or technology. Even though main path analysis can derive patent citation relationships and the weight associated with some specific arc of the citation network, the weights associated with patents and influence relationships among patents can hardly be derived based on methods of main path analysis. However, these influence relationships and weight can be crucial for defining research and development and patent aggregation strategies. Thus, the authors want to propose a novel analytic framework which consists of the Decision-Making Trial and Evaluation Laboratory (DEMATEL), the DEMATEL based Analytic Network Process (DANP) and the main path analysis. The proposed analytic framework can be used to derive the influence relationships and influence weights associated with the patents in a main path. Empirical cases based on the main path of a published work and the patent mining results of nanowire field effect transistors from the database of the United States Patent and Trademark Office will be used to demonstrate the feasibility of the proposed analytic framework. The analytic results of empirical research can be used as a basis for infringement evaluation, patent designing around and innovation.

Mapping the Research Landscape for the Motorcycle Market Policies: Sustainability as a Trend—A Systematic Literature Review

The motorcycle market has experienced an upward trend. That growth brings along mobility, accidents, and environment-related issues; nevertheless, there is a scarcity of literature on evaluating the impact of motorcycle market policies. Consequently, it has been challenging for researchers and policymakers to develop evidence-based strategies to promote or control the growth of this market. This paper aims to review and analyze the scientific literature about motorcycle market policies, using tech-mining techniques and a cluster analysis of keywords, to provide insights about the most relevant world trends in this research area. For this purpose, the bibliographic information of publications in the field was retrieved from the Scopus database. As a result, three thematic clusters (sustainability, mobility, and electric motorcycles) were identified and explained. According to our findings, greenhouse gas emissions, sustainability, environmental impact, and developing countries are the hot research topics. The research leader countries on said topics are the United States, Germany, and the United Kingdom. This study can, therefore, be used as a reference to define a future research agenda in the area. Consequently, it permits researchers and policymakers to identify trending topics and gaps in knowledge, as a baseline to include motorcycles in sustainable and affordable transport systems design.

Towards to author’s analytics: the case of DYNA journal

In this article, systematic mapping of literature, business intelligence, descriptive analytics and tech mining techniques are used to generate insights to made data-driven editorial decisions and to formulate editorial policies. The proposed methodology is called author analytics in this work, and it has the aim of providing an integral view of the authors and topics of the journal and the authors, topics, documents, and journals citing the journal under review. The proposed methodology is applied to the DYNA (Colombia) journal. The proposed analysis reveals different and complementary points of view of the analyzed journal.

Mining layered technological information in scientific papers: A semi-supervised method

Tech mining is the application of text mining tools to science and technology information resources. The ever-increasing volume of scientific outputs is a boom to technological innovation, but it also complicates efforts to obtain useful and concise information for problem solving. This challenge extends to tech mining, where the development of techniques compatible with big data is an urgent issue. This article introduces a semi-supervised method for extracting layered technological information from scientific papers in order to extend the reach of tech mining. Our method starts with several pre-set seed patterns used to extract candidate phrases by matching the dependency tree of each sentence. Then, after a series of judgements, phrases are divided into two categories: ‘main technique’ and ‘tech-component’. (A technique, for the purposes of this study, is a method or tool used in the article being analysed.) In order to generate new patterns for subsequent iterations, a weighted pattern learning method is also adopted. Finally, multiple iterations of the method are applied to extract technological information from each paper. A dataset from the field of optical switcher is used to verify the method’s effectiveness. Our findings are that (1) by two loops of extraction process in each iteration, our method realises the layered technological information extraction, which contains the ‘part–whole’ relationships between main techniques and tech-components; (2) the recall rate for main techniques is superior to the baseline after iterating 23 rounds; (3) when layering is disregarded, in the aspect of the precision and the volume of techniques, the new method is higher than that for the baseline; and (4) adjusting another two parameters can optimise the efficiency – however, the effect is neither pronounced nor straightforward.