Monitoring trends of technological changes based on the dynamic patent lattice: A modified formal concept analysis approach

The strategic importance of monitoring technological changes is highlighted given the ever faster pace and increasing complexity of technological innovation. In this respect, patent citation analysis has been the most frequently adopted tool among others. However, patent citation analysis is subject to certain drawbacks that stem from only consideration of citing-cited information and time lags between citing and cited patents. This study proposes a formal concept analysis (FCA)-based approach to developing a dynamic patent lattice that can analyze complex relations among patents and monitor trends of technological changes. The FCA is a mathematical tool for grouping objects with shared properties based on the lattice theory. The distinct strengths of FCA, vis-á-vis other methods, lie in structuring and displaying the relations among objects from a massive amount of data. For the purpose of technology monitoring, the FCA is modified to take into account time periods and changes of patent keywords. A patent context is first constructed with the aid of domain experts and text mining technique. Two types of dynamic patent lattices are then developed by executing the modified FCA algorithm. A case study of laser technology in lithography for semiconductor manufacturing shows that the suggested dynamic patent lattice has considerable advantages over conventional patent citation maps in terms of visualization and informative power.     

An analysis of East Asian currency area: Bayesian dynamic factor model approach

There has recently been an increasing interest in the establishment of a common currency area in East Asia in the aftermath of the East Asian financial crisis. In this article I examine the desirability and feasibility of forming a currency area in the region by checking the symmetry of shocks as an important criterion of the theory of Optimum Currency Area. I employ a dynamic factor model to decompose aggregate output into world, regional and country‐specific components and estimate the model using a Gibbs sampling simulation. Persistent properties of those components are examined and variance decomposition analysis is performed to investigate the role of each component in output variance. The European Monetary Union, with the successful launch of the euro, is the natural benchmark for comparison. Based on variance analysis, it is found that East Asian countries, on average, are less plausible candidates for a currency area than European counterparts. However, a subgroup of countries in East Asia is as qualified as those in Europe. Given the ongoing integration in East Asia, it is not premature to prepare for such a currency area in this region.     

Human settlement＇s social network analysis based on spatial trend surface model：a case study of Chongqing Municipality

Integrated with GIS and remote sensing（RS） technology,a systematic analysis and its methodology for human-settlements social environment has been introduced.This methodology has been called spatial trend field model（STFM）.STFM＇s application history in the field of human-settlements social environment has been discussed at first.Then,some index data models have been created through STFM,which include population density trend field,human activity strength trend field,city-town spatial density trend field,urbanization ratio trend field,road density trend field,GDP spatial density trend field and PER-GDP spatial density trend field.With all above-mentioned indexes as input data,through Iterative Self-Organizing Data Analysis Techniques Algorithm（ISODATA）,this paper makes a verification study of Chongqing municipality.The result of the case study confirms that STFM methodology is credible and has high efficiency for regional human-settlements study.