Predicting the future relevance of research institutions - The winning solution of the KDD Cup 2016
نویسندگان
چکیده
The world’s collective knowledge is evolving through research and new scientific discoveries. It is becoming increasingly difficult to objectively rank the impact research institutes have on global advancements. However, since the funding, governmental support, staff and students quality all mirror the projected quality of the institution, it becomes essential to measure the affiliation’s rating in a transparent and widely accepted way. We propose and investigate several methods to rank affiliations based on the number of their accepted papers at future academic conferences. We carry out our investigation using publicly available datasets such as the Microsoft Academic Graph, a heterogeneous graph which contains various information about academic papers. We analyze several models, starting with a simple probabilities-based method and then gradually expand our training dataset, engineer many more features and use mixed models and gradient boosted decision trees models to improve our predictions.
منابع مشابه
Ranking academic institutions on potential paper acceptance in upcoming conferences
The crux of the problem in KDD Cup 2016 involves developing data mining techniques to rank research institutions based on publications. Rank importance of research institutions are derived from predictions on the number of full research papers that would potentially get accepted in upcoming top-tier conferences, utilizing public information on the web. This paper describes our solution to KDD C...
متن کاملWinning the KDD Cup Orange Challenge with Ensemble Selection
We describe our wining solution for the KDD Cup Orange Challenge.
متن کاملRanking Research Institutions Based On Related Academic Conferences
The detection of influential nodes in a social network is an active research area with many valuable applications including marketing and advertisement. As a new application in academia, KDD Cup 2016 shed light on the lack of an existing objective ranking for institutions within their respective research areas and proposed a solution for it. In this problem, the academic fields are defined as s...
متن کاملFeature Engineering and Ensemble Modeling for Paper Acceptance Rank Prediction
Measuring research impact and ranking academic achievement are important and challenging problems. Having an objective picture of research institution is particularly valuable for students, parents and funding agencies, and also attracts attention from government and industry. KDD Cup 2016 proposes the paper acceptance rank prediction task, in which the participants are asked to rank the import...
متن کاملFinding Influential Institutions in Bibliographic Information Networks
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...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- CoRR
دوره abs/1609.02728 شماره
صفحات -
تاریخ انتشار 2016