Year: 2017
Type: conference-paper
Abstract: This paper describes our submission to SemEval-2017 Task 3 Subtask D, "Question Answer Ranking in Arabic Community Question Answering".In this work, we applied a supervised machine learning approach to automatically re-rank a set of QA pairs according to their relevance to a given question.We employ features based on latent semantic models, namely WTMF, as well as a set of lexical features based on string length and surface level matching.The proposed system ranked first out of 3 submissions, with a MAP score of 61.16%.
DOI: 10.18653/v1/s17-2056
Authors: Nada Almarwani, Mona Diab
Institution: George Washington University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W2752059660