M
Muhidin Mohamed
Researcher at Aston University
Publications - 17
Citations - 190
Muhidin Mohamed is an academic researcher from Aston University. The author has contributed to research in topics: Semantic similarity & WordNet. The author has an hindex of 6, co-authored 14 publications receiving 113 citations. Previous affiliations of Muhidin Mohamed include King Fahd University of Petroleum and Minerals & South Valley University.
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Journal ArticleDOI
SRL-ESA-TextSum : a text summarization approach based on semantic role labeling and explicit semantic analysis
Muhidin Mohamed,Mourad Oussalah +1 more
TL;DR: The findings demonstrate the power of the role-based and vectorial semantic representation when combined with the crowd-sourced knowledge base in Wikipedia.
Journal ArticleDOI
An Approach for ECG Feature Extraction using Daubechies 4 (DB4) Wavelet
Muhidin Mohamed,Mohamed Deriche +1 more
TL;DR: An ECG feature extraction algorithm based on Daubechies Wavelet Transform is presented and DB4 Wavelet is selected due to the similarity of its scaling function to the shape of the ECG signal.
Journal ArticleDOI
A hybrid approach for paraphrase identification based on knowledge-enriched semantic heuristics
Muhidin Mohamed,Mourad Oussalah +1 more
TL;DR: A hybrid approach based on the integration of word semantic similarity derived from WordNet taxonomic relations, and named-entity semantic relatedness inferred from Wikipedia entity co-occurrences and underpinned by Normalized Google Distance is proposed for sentence paraphrase identification.
Proceedings ArticleDOI
An Iterative Graph-Based Generic Single and Multi Document Summarization Approach Using Semantic Role Labeling and Wikipedia Concepts
Muhidin Mohamed,Mourad Oussalah +1 more
TL;DR: The empirical evaluation of the proposed summarization model on a standard dataset from the Document Understanding Conference showed the effectiveness of the approach which outperformed the baseline comparators in terms of ROUGE scores.
Journal ArticleDOI
Identifying and Extracting Named Entities from Wikipedia Database Using Entity Infoboxes
Muhidin Mohamed,Mourad Oussalah +1 more
TL;DR: Experiments on CoNLL2003 shared task named entity recognition (NER) dataset disclosed the system's outstanding performance in comparison to three different state- of-the-art systems.