Finding Influential Institutions in Bibliographic Information Networks
This work provides a solution for measuring institutional impact in bibliographic networks, which is incremental as it builds on existing ranking methods for papers and authors.
The paper tackled the problem of ranking research institutions in bibliographic networks, as addressed in the KDD Cup 2016 competition, and achieved an average NDCG@20 score of 0.7483, placing eleventh.
Ranking in bibliographic information networks is a widely studied problem due to its many applications such as advertisement industry, funding, search engines, etc. Most of the existing works on ranking in bibliographic information network are based on ranking of research papers and their authors. But the bibliographic information network can be used for solving other important problems as well. The KDD Cup $2016$ competition considers one such problem, which is to measure the impact of research institutions, i.e. to perform ranking of research institutions. The competition took place in three phases. In this paper, we discuss our solutions for ranking institutions in each phase. We participated under team name "anu@TASL" and our solutions achieved the average NDCG@$20$ score of $0.7483$, ranking in eleventh place in the contest.