Abstract
Research activities are composed of stacks of several tasks such as surveys, creation of novel ideas, writing of research documents, and their elaboration. It is quite important to successfully accumulate the results and circumstances of these tasks (i.e., contexts). It is further important but difficult to understand the contexts and to apply them to later work. In particular, it is much more difficult for research beginners to ensure noteworthy targets within contexts that continuously increase as the work progresses. The final goal of this research is to develop methods for supporting the accumulation of contexts and facilitating their utilization by visually presenting those that are noteworthy to research beginners. This paper mainly describes a method for organizing the contexts and extracting important portions from huge organized contexts. This paper also describes an experiment that was conducted by using actual history data, and discusses the features of the proposed methods on the basis of the results.
Original language | English |
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Pages (from-to) | S123-S134 |
Journal | Journal of Computational Methods in Sciences and Engineering |
Volume | 17 |
Issue number | S1 |
DOIs | |
Publication status | Published - 2017 |
Externally published | Yes |
Keywords
- Context information
- context network
- learning analytics
- research activity support
- research documenting
- small world
ASJC Scopus subject areas
- Engineering(all)
- Computer Science Applications
- Computational Mathematics