A B C D E F G H I J K L M N O P Q R S T U V W X Y Z all

Alumni Member

Chenghua Lin (Alumni) Member status icon

Research Associate
Chenghua Lin Photograph

Website Icon

I joined KMi as research associate in Oct 2011 after receiving my PhD in computing from the University of Exeter. My PhD study focused on developing statistical topic models for sentiment analysis from the Web.

My current research effort is mainly devoted to developing theoretically principled machine learning models for social media analysis and semantic Web applications.

Keys: Sentiment analysis, Machine learning, Probabilistic Bayesian modelling, natural language processing, Text mining

News

Publications

Publications | Visit External Site for Details  

Peng, X., Zheng, Y., Lin, C. and Siddharthan, A. (2021) Summarising Historical Text in Modern Languages, Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics

Publications | Visit External Site for Details  

Barawi, M., Lin, C., Siddharthan, A. and Liu, Y. (2019) Extractive and Abstractive Sentence Labelling of Sentiment-bearing Topics, Frontiers of Computer Science, pp. (In Press), Springer

Publications | Download PDF Publications | Visit External Site for Details  

Wibowo, A., Siddharthan, A., Masthoff, J. and Lin, C. (2018) Understanding how to Explain Package Recommendations in the Clothes Domain, Workshop: Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS) at 12th ACM Conference on Recommender Systems (RecSys), Vancouver, Canada

Publications | Download PDF  

Wibowo, A., Siddharthan, A., Masthoff, J. and Lin, C. (2018) Incorporating Constraints into Matrix Factorization for Clothes Package Recommendation, Proceedings of the 26th ACM Conference on User Modelling, Adaptation and Personalization (UMAP)

Publications | Download PDF  

Wibowo, A., Siddharthan, A., Lin, C. and Masthoff, J. (2017) Matrix Factorization for Package Recommendations, Workshop: Workshop on Recommendation in Complex Scenarios (ComplexRec 2017) at RecSys, Como, Italy

View all 19 publications

View By

Research Themes

Latest Seminar
Dr Nicole Lotz
The Open University

Creative engagement and co-design for inclusion

Watch the live webcast

CONTACT US

Knowledge Media Institute
The Open University
Walton Hall
Milton Keynes
MK7 6AA
United Kingdom

Tel: +44 (0)1908 653800

Fax: +44 (0)1908 653169

Email: KMi Support

COMMENT

If you have any comments, suggestions or general feedback regarding our website, please email us at the address below.

Email: KMi Development Team