Media of University of Babylon | Two Researchers from the College of Information Technology Publish a Scientific Paper in a Global Journal on Key Phrase Detection for Candidate Topics

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Two Researchers from the College of Information Technology Publish a Scientific Paper in a Global Journal on Key Phrase Detection for Candidate Topics

by : Duhaa Fadill Abbas

Date : 04/5/2025 52:46:07 PM

Veiw : 112

Two Researchers from the College of Information Technology Publish a Scientific Paper in a Global Journal on Key Phrase Detection for Candidate Topics

Duhaa Fadill Abbas
In a new academic achievement that adds to the research and innovation record of the College of Information Technology – Software Department, researchers M. Programmer Yasser Saad Joudi and Prof. Dr. Wafaa Mohammed Saeed have published a scientific paper titled:

"Toward Salient Key Phrase for Candidate Topic Detection"

The paper was published in the Kufa Journal of Engineering, a peer-reviewed international journal indexed in the fourth quartile (Q4) globally. It is accessible via the digital object identifier (DOI):
https://doi.org/10.30572/2018/KJE/160213

Abstract:
Amidst the rapid growth of digital content, there is a growing demand for intelligent tools capable of automatically and efficiently extracting key phrases. This study aims to develop a model that identifies salient phrases which capture the central meaning of textual content and associate them with their relevant topics.

The researchers propose a novel approach that integrates both statistical and contextual features—such as phrase position, proximity, and semantics—within a comprehensive text analysis framework that ensures high accuracy and effectiveness in information extraction.

The proposed model, PhraeRank, is distinguished by its ability to cluster extracted phrases into focused thematic groups. It employs advanced techniques such as approximate matching with initial key sentences, hotspot analysis, and prioritization of frequently occurring and semantically significant phrases.

This work reflects the College of Information Technology’s dedication to advancing scientific research and developing AI-based tools that enhance information retrieval and digital content analysis.