Chief Investigator:

Dr. YEUNG Chi Ho

Project Year:

2019-2020

Description:

An efficient and accurate literature search is a crucial first step in research, but it is never easy; research ideas are often combinations of entities, concepts, theories and methodologies, related in a complex way, difficult to be searched for or identified by conventional keyword-based search engines. This is further complicated by the rapidly expanding literature and the increasingly cross-disciplinary nature of research. One may have to spend extensive time and effort, even with the aid of intuition and luck, to complete literature search but remain at risk of missing relevant information. Nevertheless, even with a very powerful search engine which outputs a list of the most relevant literature, there are non-trivial connections underlying these different research-papers which constitute a holistic picture of research development in the area. Such picture is not identified by search engines, and hence is not known to the searchers. As literature search over a comprehensive database is the major channel of knowledge flow within the research community, the ineffectiveness of search systems has rendered knowledge flow sub-optimal. In the long run, this impacts negatively on research development in every area. In our proposed research, we aim to employ techniques in text mining and statistical inference, integrated with the Physics approaches of optimization, and the approaches for complex networks and the Science of Science, to reveal the extent of effectiveness of knowledge flow in the research community.