Establishing Knowledge Networks via Analysis of Research Abstracts
The extraction and propagation of knowledge inherent in a social network environment is demanding higher significance in research. The knowledge hidden within a social network would be easier to be comprehended if provided in a collective form. In the field of scientific research, such presentation of appreciated knowledge evolved from research communities would aid researchers. In this paper, we propose the evolution of a knowledge network from the information available in digital bibliographic repositories like DBLP [DBLP]. The most important characteristic of this knowledge network would be the comprehension of the proficiency of the scientist in the perspective of an area of research. This is achieved by categorizing the research articles published by an author into specific domains. The quality of the research articles are ascertained by analysing the abstracts within the domain. This analysis is used to determine the quality of the research article in terms of originality, relevancy and thereby, the impact of the article with respect to a research area. This quality measure provides knowledge on the impact of the scientist on the research community is arrived at as a cumulative entity. This knowledge helps in the evolution of the knowledge network from the social network of a research community.
knowledge networks fuzzy cognitive maps