Name: AKEC
Description: The corpus consists in 160 arabic documents and their keyphrases.
Provider: University of Udine,University of Sheffield
Paper Title: Towards building a standard dataset for Arabic keyphrase extraction evaluation
Tasks: keyphrase extraction
Venue Name: International Conference on Asian Language Processing
Authors: Muhammad Helmy,Marco Basaldella,Eddy Maddalena,S. Mizzaro,Gianluca Demartini
Abstract: Keyphrases are short phrases that best represent a document content. They can be useful in a variety of applications, including document summarization and retrieval models. In this paper, we introduce the first dataset of keyphrases for an Arabic document collection, obtained by means of crowdsourcing. We experimentally evaluate different crowdsourced answer aggregation strategies and validate their performances against expert annotations to evaluate the quality of our dataset. We report about our experimental results, the dataset features, some lessons learned, and ideas for future work.