New publication in IEEE Access

I am delighted to announce the publication of my recent research paper titled “Systematic Literature Review of Information Extraction From Textual Data: Recent Methods, Applications, Trends, and Challenges” in IEEE Access. As you are aware, information extraction (IE) from textual data presents a complex challenge, requiring customized approaches that cater to specific data types and target information.

In this study, my co-authors and I reviewed the most recent strategies for extracting information from textual data, as well as their advantages and limitations. We used a systematic mapping technique to summarize works published between 2017 and 2022, covering the fundamental concepts, recent approaches, applications, trends, challenges, and future research prospects in this subject area.

Our research analysis, based on 161 selected studies, revealed that state-of-the-art models primarily leverage deep learning to extract information from textual data. By providing a holistic perspective of this domain, our study aims to guide novice and experienced researchers in their future research and serve as a foundational resource for this research area.

I would also like to express my gratitude to Universiti Teknologi PETRONAS for providing research facilities and funding, which made this study possible. I hope this study proves valuable to anyone interested in IE from textual data. We welcome any questions or feedback you may have. Full access to the article is available via IEEE Xplore.

Co-authors:

Norshakirah Aziz, Said Jadid Abdulkadir, Dr. Hitham Alhussian, Noureen Talpur