Learning to Rank for Expert Search in Digital Libraries of Academic Publications
Information Retrieval
2013-02-05 v1 Digital Libraries
Abstract
The task of expert finding has been getting increasing attention in information retrieval literature. However, the current state-of-the-art is still lacking in principled approaches for combining different sources of evidence in an optimal way. This paper explores the usage of learning to rank methods as a principled approach for combining multiple estimators of expertise, derived from the textual contents, from the graph-structure with the citation patterns for the community of experts, and from profile information about the experts. Experiments made over a dataset of academic publications, for the area of Computer Science, attest for the adequacy of the proposed approaches.
Keywords
Cite
@article{arxiv.1302.0413,
title = {Learning to Rank for Expert Search in Digital Libraries of Academic Publications},
author = {Catarina Moreira and Pável Calado and Bruno Martins},
journal= {arXiv preprint arXiv:1302.0413},
year = {2013}
}