English

Using Semantic Role Knowledge for Relevance Ranking of Key Phrases in Documents: An Unsupervised Approach

Information Retrieval 2019-08-21 v1 Computation and Language

Abstract

In this paper, we investigate the integration of sentence position and semantic role of words in a PageRank system to build a key phrase ranking method. We present the evaluation results of our approach on three scientific articles. We show that semantic role information, when integrated with a PageRank system, can become a new lexical feature. Our approach had an overall improvement on all the data sets over the state-of-art baseline approaches.

Keywords

Cite

@article{arxiv.1908.03313,
  title  = {Using Semantic Role Knowledge for Relevance Ranking of Key Phrases in Documents: An Unsupervised Approach},
  author = {Prateeti Mohapatra and Neelamadhav Gantayat and Gargi B. Dasgupta},
  journal= {arXiv preprint arXiv:1908.03313},
  year   = {2019}
}

Comments

5 pages

R2 v1 2026-06-23T10:43:28.826Z