KMi Publications

External Publications

13 publications | Chenghua Lin


He, Y., Lin, C., Gao, W. and Wong, K. (2012) Online Sentiment and Topic Dynamics Tracking from Social Media, ACM Transactions on Intelligent Systems and Technology

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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

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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., Lin, C., Gao, W. and Wong, K. (2012) Tracking Sentiment and Topic Dynamics from Social Media, Poster at The 6th International AAAI Conference on Weblogs and Social Media (ICWSM), Dublin, Ireland

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Pedrinaci, C., Liu, D., Lin, C. and Domingue, J. (2012) Harnessing the Crowds for Automating the Identification of Web APIs, Workshop: Intelligent Web Services Meet Social Computing at AAAI Spring Symposium 2012, Stanford, California

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Lin, C., He, Y. and Everson, R. (2011) Sentence Subjectivity Detection with Weakly-Supervised Learning, The 5th International Joint Conference on Natural Language Processing (IJCNLP), Chiang Mai, Thailand

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He, Y., Lin, C. and Alani, H. (2011) Automatically Extracting Polarity-Bearing Topics for Cross-Domain Sentiment Classification, The 49th Annual Meeting of the Association for Computational Linguistics (ACL), Portland, Oregon

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Lin, C., He, Y., Everson, R. and Rueger, S. (2011) Weakly-Supervised Joint Sentiment-Topic Detection from Text, IEEE Transactions on Knowledge and Data Engineering (TDKE)

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Lin, C., He, Y. and Everson, R. (2010) A Comparative Study of Bayesian Models for Unsupervised Sentiment Detection, The 14th Conference on Computational Natural Language Learning (CoNLL), Uppsala, Sweden

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Lin, C. and He, Y. (2009) Joint Sentiment/Topic Model for Sentiment Analysis, The 18th ACM Conference on Information and Knowledge Management (CIKM), Hong Kong, China

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He, Y. and Lin, C. (2009) Protein-Protein Interactions Classification from Text via Local Learning with Class Priors, 14th International Conference on Applications of Natural Language to Information Systems (NLDB), Saabrucken, Germany

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Liu, K., Lin, C. and Qiao, B. (2008) A Multi-agent System for Intelligent Pervasive Spaces, IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI), Beijing, China

Lin, C., Liu, K. and Wei, H. (2008) Review of Computer Vision in Intelligent Environment Design, SSE System Engineering Conference, Reading, UK

 
 
 

Future Internet is...


Future Internet
With over a billion users, today's Internet is arguably the most successful human artifact ever created. The Internet's physical infrastructure, software, and content now play an integral part of the lives of everyone on the planet, whether they interact with it directly or not. Now nearing its fifth decade, the Internet has shown remarkable resilience and flexibility in the face of ever increasing numbers of users, data volume, and changing usage patterns, but faces growing challenges in meetings the needs of our knowledge society. Globally, many major initiatives are underway to address the need for more scientific research, physical infrastructure investment, better education, and better utilisation of the Internet. Within Japan, USA and Europe major new initiatives have begun in the area.

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