Search Results for author: Rushdi Shams

Found 5 papers, 0 papers with code

Semi-supervised Classification for Natural Language Processing

no code implementations25 Sep 2014 Rushdi Shams

This study explores the possibilities and achievements as well as complexity and limitations of semi-supervised classification for several natural langue processing tasks like parsing, biomedical information processing, text classification, and summarization.

Classification General Classification +2

Performance of Stanford and Minipar Parser on Biomedical Texts

no code implementations25 Sep 2014 Rushdi Shams

The performance of te parsers to assignm dependencies between two biomedical concepts that are already proved to be connected is not satisfying.

Extracting Connected Concepts from Biomedical Texts using Fog Index

no code implementations30 Jul 2013 Rushdi Shams, Robert E. Mercer

We rank sentences of a text according to their FI and select 30 percent of the most difficult sentences.

Association

Extracting Information-rich Part of Texts using Text Denoising

no code implementations30 Jul 2013 Rushdi Shams

The aim of this paper is to report on a novel text reduction technique, called Text Denoising, that highlights information-rich content when processing a large volume of text data, especially from the biomedical domain.

Denoising

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