Similar researcher search in academic environments

  • Authors:

  • Sujatha Das Gollapalli;Prasenjit Mitra;C. Lee Giles

  • Affiliations:

  • The Pennsylvania State University, State College, PA, USA;The Pennsylvania State University, State College, PA, USA;The Pennsylvania State University, State College, PA, USA

  • Venue:
  • Proceedings of the 12th ACM/IEEE-CS joint conference on Digital Libraries
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

Abstract

Entity search is an emerging IR and NLP task that involves the retrieval of entities of a specific type in response to a query. We address the similar researcher search" or the "researcher recommendation" problem, an instance of similar entity search" for the academic domain. In response to a researcher name' query, the goal of a researcher recommender system is to output the list of researchers that have similar expertise as that of the queried researcher. We propose models for computing similarity between researchers based on expertise profiles extracted from their publications and academic homepages. We provide results of our models for the recommendation task on two publicly-available datasets. To the best of our knowledge, we are the first to address content-based researcher recommendation in an academic setting and demonstrate it for Computer Science via our system, ScholarSearch.