Profile

Title: Dr
First Name: Ebuka
Surname: Ibeke
Position: Lecturer
Telephone: +44 (0) 1224 263564
Email:
Linkedin: LinkedIn Icon http://www.linkedin.com/in/ebuka-ibeke-52251936
ORCID: ORCID Icon https://orcid.org/0000-0002-2560-499X

Duties and Responsibilities

Previously a Lecturer (P/T) in Computer Science. Taught courses include:

Database Management and Big Data Visualisation.

Currently teaching Data Analytics for Business Decisions and Data Visualisation. And bringing Analytics to other areas in the School of Creative and Cultural Business.

Academic Background

Dr Ibeke holds a BSc in Computer Science from Nnamdi Azikiwe University, Nigeria, an MSc in Information Engineering from the Robert Gordon University, UK, and a PhD in Computing Science from the University of Aberdeen, UK.

Research Interests

Big Data Analysis; Sentiment Analysis; Topic Modelling; Neural Networks and Deep Learning; Information/Data Extraction; Business Analytics; Machine Learning; Clustering Techniques; Social Network Analysis; Data Security.

Desire PhD Supervision in the above areas and Data Analytics in general.

Publications

Ibeke E., Lin C., and Wyner A. A Unified Latent Variable Model for Contrastive Opinion Mining. Frontier of Computer Science, Springer,2017. Published August, 2019. doi: 10.1007/s11704-018-7073-5 

Ibeke E., Lin C., Wyner A, and Barawi M. Extracting and understanding contrastive opinion through topic relevant sentences. The 8th International Joint Conference on Natural Language Processing (IJCNLP), Taiwan,2017.

Ibeke E., Lin C., Coe, C., Wyner, A., Liu, D., Barawi, M. and Yusof, N. A Curated Corpus for Sentiment-Topic Analysis. The Emotion and Sentiment Analysis Workshop in the 10th Language Resources and Evaluation Conference (LREC), Slovenia, 2016.

Lin C., Ibeke E., Wyner A. and Guerin F. Sentiment-Topic Modelling in Text Mining. Data Mining and Knowledge Discovery, Wiley, 2015. doi:10.1002/widm.1161