Keyword Extraction for Identifying Social Actors
Mahyuddin K. M. Nasution, Shahrul Azman Mohd Noah

TL;DR
This paper presents a novel keyword extraction approach based on the overlap principle to identify social actors by filtering relevant web snippets, improving accuracy in social actor identification tasks.
Contribution
The paper introduces an overlap principle-based method that combines multiple web snippet features to enhance social actor identification accuracy.
Findings
Effective filtering of irrelevant web pages
Improved accuracy in social actor identification
Utilization of web snippet features
Abstract
Identifying the social actor has become one of tasks in Artificial Intelligence, whereby extracting keyword from Web snippets depend on the use of web is steadily gaining ground in this research. We develop therefore an approach based on overlap principle for utilizing a collection of features in web snippets, where use of keyword will eliminate the un-relevant web pages.
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Taxonomy
TopicsAdvanced Text Analysis Techniques · Information Retrieval and Data Mining · Biomedical Text Mining and Ontologies
