Work

Improving random walk rankings with feature selection and imputation Science4cast competition, team Hash Brown

Year: 2021

Type: conference-paper

Abstract: The Science4cast Competition consists of predicting new links in a semantic network, with each node representing a concept and each edge representing a link proposed by a paper relating two concepts. This network contains information from 1994-2017, with a discretization of days (which represents the publication date of the underlying papers). Team Hash Brown’s final submission, ee5a, achieved a score of 0.92738 on the test set. Our team’s score ranks second place, 0.01 below the winner’s score. This paper details our model, its intuition, and the performance of its variations in the test set.

Source: IEEE International Conference on Big Data (BigData)

DOI: 10.1109/bigdata52589.2021.9671785

Authors: Ngoc Mai Tran, Yangxinyu Xie

Institution: The University of Texas at Austin

Language: English

Topic: Complex Network Analysis Techniques

Subfield: Statistical and Nonlinear Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W4205446169

FWCI: 0.76

Cites: 27

Cited by: 3

Related to: 10