Development and application of a keyword-based knowledge map for effective R&D planning

Abstract

With the growing recognition of the importance of knowledge creation, knowledge maps are being regarded as a critical tool for successful knowledge management. However, the various methods of developing knowledge maps mostly depend on unsystematic processes and the judgment of domain experts with a wide range of untapped information. Thus, this research aims to propose a new approach to generate knowledge maps by mining document databases that have hardly been examined, thereby enabling an automatic development process and the extraction of significant implications from the maps. To this end, the accepted research proposal database of the Korea Research Foundation (KRF), which includes a huge knowledge repository of research, is investigated for inducing a keyword-based knowledge map. During the developmental process, text mining plays an important role in extracting meaningful information from documents, and network analysis is applied to visualize the relations between research categories and measure the value of network indices. Five types of knowledge maps (core R&D map, R&D trend map, R&D concentration map, R&D relation map, and R&D cluster map) are developed to explore the main research themes, monitor research trends, discover relations between R&D areas, regions, and universities, and derive clusters of research categories. The results can be used to establish a policy to support promising R&D areas and devise a long-term research plan.

Product and process innovation in manufacturing firms: a 30-year bibliometric analysis

“…Further analysis for mapping the specific research area is based on author keywords that appeared in at least two papers. The usage of keywords is accepted by the literature and successfully applied also to other research areas (Su and Lee, 2010;Yoon et al, 2010;Chang et al, 2015;Khan and Wood, 2015). After this, each selected paper is given a binary value (0, 1) for each descriptor.…”

“…For example, if a journal is in the first quadrant it does not necessarily have the same keywords shown in the first quadrant of keyword's proximity map. According to the literature (Su and Lee, 2010;Yoon et al, 2010;Chang et al, 2015;Khan and Wood, 2015), the keywords included in our analysis are summarized in Table 4. In the journal positioning map we include the most repeated words given by authors with a total number of fifteen or more appearances.…”

Identifying trends and flows in communication and information processing by means of keyword network analysis

“…Visualisation techniques have been applied effectively to explore themes, monitor trends and locate interrelated fields [25], [24].…”

Understanding Faculty Collaboration and Productivity: A Case Study

“…Similarly, in this paper, we also apply SNA to analyze faculty members' research productivity, collaboration, and publication strategies. Yoon et al (2010) state that because of the rapid growth of knowledge creation, knowledge maps are an important research tool for successful knowledge management, and have been widely applied in bibliometrics, scientometrics, and other informatics fields (Xiao et al, 2013). Knowledge maps allow people to visualize data that displays the progress, structural relationships, or pattern flow of scientific knowledge (Chen & Liu, 2005 PFNET).…”