Jianxi Luo

Bio: Jianxi Luo is an academic researcher from Singapore University of Technology and Design. The author has contributed to research in topics: Engineering design process & Semantic network. The author has an hindex of 21, co-authored 115 publications receiving 1386 citations. Previous affiliations of Jianxi Luo include Massachusetts Institute of Technology & New York University.

TechNet: Technology semantic network based on patent data

Abstract: The growing developments in general semantic networks, knowledge graphs and ontology databases have motivated us to build a large-scale comprehensive semantic network of technology-related data for engineering knowledge discovery, technology search and retrieval, and artificial intelligence for engineering design and innovation. Specially, we constructed a technology semantic network (TechNet) that covers the elemental concepts in all domains of technology and their semantic associations by mining the complete U.S. patent database from 1976. To derive the TechNet, natural language processing techniques were utilized to extract terms from massive patent texts and recent word embedding algorithms were employed to vectorize such terms and establish their semantic relationships. We report and evaluate the TechNet for retrieving terms and their pairwise relevance that is meaningful from a technology and engineering design perspective. The TechNet may serve as an infrastructure to support a wide range of applications, e.g., technical text summaries, search query predictions, relational knowledge discovery, and design ideation support, in the context of engineering and technology, and complement or enrich existing semantic databases. To enable such applications, the TechNet is made public via an online interface and APIs for public users to retrieve technology-related terms and their relevancies.

Measuring technological distance for patent mapping

Abstract: Recent works in the information science literature have presented cases of using patent databases and patent classification information to construct network maps of technology fields, which aim to aid in competitive intelligence analysis and innovation decision making. Constructing such a patent network requires a proper measure of the distance between different classes of patents in the patent classification systems. Despite the existence of various distance measures in the literature, it is unclear how to consistently assess and compare them, and which ones to select for constructing patent technology network maps. This ambiguity has limited the development and applications of such technology maps. Herein, we propose to compare alternative distance measures and identify the superior ones by analyzing the differences and similarities in the structural properties of resulting patent network maps. Using United States patent data from 1976 to 2006 and the International Patent Classification IPC system, we compare 12 representative distance measures, which quantify interfield knowledge base proximity, field-crossing diversification likelihood or frequency of innovation agents, and co-occurrences of patent classes in the same patents. Our comparative analyses suggest the patent technology network maps based on normalized coreference and inventor diversification likelihood measures are the best representatives.

The past, present and future of China's automotive industry: a value chain perspective

Abstract: The economic growth and industrial development in China over the last decade has been of considerable interest to industry and policy-makers alike, and also been subject of many academic studies. Considerable research on the macro-economic growth and process of industrialisation, as well as the subsequent increase in the domestic demand has been reported. In case of the automotive industry, previous studies have analysed the rather complex industry structure, still dominated by a range of joint ventures between domestic and foreign manufacturers, and specifically commented on the potential and sustainability of domestic demand. In this study we aim to extend the focus by analysing the key features and challenges not only at the manufacturer, but also at the supplier and distribution tiers in the automotive supply chain in China. Reviewing the governmental policies that led the auto industry's development since 1950, we analyse the current capabilities and challenges at the different tiers in the automotive value chain, before concluding with an outlook on the factors impacting on the future development of the automotive industry in China.

Detecting evolving patterns of self-organizing networks by flow hierarchy measurement

Abstract: Hierarchies occur widely in evolving self-organizing ecological, biological, technological, and social networks, but detecting and comparing hierarchies is difficult. Here we present a metric and technique to quantitatively assess the extent to which self-organizing directed networks exhibit a flow hierarchy. Flow hierarchy is a commonly observed but theoretically overlooked form of hierarchy in networks. We show that the ecological, neurobiological, economic, and information processing networks are generally more hierarchical than their comparable random networks. We further discovered that hierarchy degree has increased over the course of the evolution of Linux kernels. Taken together, our results suggest that hierarchy is a central organizing feature of real-world evolving networks, and the measurement of hierarchy opens the way to understand the structural regimes and evolutionary patterns of self-organizing networks. Our measurement technique makes it possible to objectively compare hierarchies of different networks and of different evolutionary stages of a single network, and compare evolving patterns of different networks. It can be applied to various complex systems, which can be represented as directed networks. © 2011 Wiley Periodicals, Inc. Complexity, 2011 © 2011 Wiley Periodicals, Inc.

Design Prototypes: A Knowledge Representation Schema for Design

Abstract: A prevalent and pervasive view of designing is that it can be modeled using variables and decisions made about what values should be taken by these variables. The activity of designing is carried out with the expectation that the designed artifact will operate in the natural world and the social world. These worlds impose constraints on the variables and their values; so, design could be described as a goal-oriented, constrained, decision- making activity. However, design distinguish- es itself from other similarly described activities not only by its domain but also by additional necessary features. Designing involves exploration, exploring what variables might be appropriate. The process of explo- ration involves both goal variables and deci- sion variables. In addition, designing involves learning: Part of the exploration activity is learning about emerging features as a design proceeds. Finally, design activity occurs within two contexts: the context within which the designer operates and the context produced by the developing design itself. The designer’s perception of what the context is affects the implication of the context on the design. The context shifts as the designer’s perceptions change. Design activity can be now characterized as a goal-oriented, con- strained, decision-making, exploration, and learning activity that operates within a con- text that depends on the designer’s percep- tion of the context.

国际刊物《Scientometrics》文献计量研究

Abstract: 本文对国际科学计量学杂志《Ｓｃｉｅｎｔｏｍｅｔｒｉｃｓ》１９７９－１９９１年的研究论文内容、栏目、作者及国别和编委及国别作了计量分析，揭示出科学计量学研究的重点、活动的中心及发展趋势，说明了学科带头人在发展科学计量学这门新兴学科中的作用。