People | Alumni | Yulan He
Senior LecturerI am interested in investigating machine learning techniques in enabling rich access to information. My current research interests are sentiment analysis and optinion mining; text mining; information extraction; natural language processing; business intelligence and data mining; machine learning; bioinformatics; spoken language understanding and information retrieval.
Keys: Sentiment analysis, opinion mining, information extraction, machine learning, natural language processing.
He, Y., Lin, C., Gao, W. and Wong, K. (2012) Dynamic Joint Sentiment-Topic Model, ACM Transactions on Intelligent Systems and Technology, In Press
Saif, H., He, Y. and Alani, H. (2012) Semantic Sentiment Analysis of Twitter, International Semantic Web Conference, Boston, US
Lin, C., He, Y., Pedrinaci, C. and Domingue, J. (2012) Feature LDA: a Supervised Topic Model for Automatic Detection of Web API Documentations from the Web, The 11th International Semantic Web Conference (ISWC), Boston, USA
He, Y., Lin, C. and Cano Basave, E. (2012) Online Sentiment and Topic Dynamics Tracking over the Streaming Data, IEEE International Conference on Social Computing (SocialCom), Amsterdam, The Nethelands
He, Y. (2012) A Bayesian Modeling Approach to Multi-Dimensional Sentiment Distributions Prediction, Workshop: Workshop on Issues of Sentiment Discovery and Opinion Mining at The 18th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)
Bayesian Models for Sentence-Level Subjectivity Detection
Techreport ID: kmi-10-02
Date: 2010
Author(s): Yulan He
ManagementMultimedia &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
Future Internet is...

To succeed the Future Internet will need to address a number of cross-cutting challenges including:
- Scalability in the face of peer-to-peer traffic, decentralisation, and increased openness
- Trust when government, medical, financial, personal data are increasingly trusted to the cloud, and middleware will increasingly use dynamic service selection
- Interoperability of semantic data and metadata, and of services which will be dynamically orchestrated
- Pervasive usability for users of mobile devices, different languages, cultures and physical abilities
- Mobility for users who expect a seamless experience across spaces, devices, and velocities
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