Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10358361 | Journal of Informetrics | 2014 | 16 Pages |
Abstract
A new link-based document ranking framework is devised with at its heart, a contents and time sensitive random literature explorer designed to more accurately model the behaviour of readers of scientific documents. In particular, our ranking framework dynamically adjusts its random walk parameters according to both contents and age of encountered documents, thus incorporating the diversity of topics and how they evolve over time into the score of a scientific publication. Our random walk framework results in a ranking of scientific documents which is shown to be more effective in facilitating literature exploration than PageRank measured against a proxy gold standard based on papers' potential usefulness in facilitating later research. One of its many strengths lies in its practical value in reliably retrieving and placing promisingly useful papers at the top of its ranking.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Han Xu, Eric Martin, Ashesh Mahidadia,