Cognitive SenticNet and Multimodal Topic Structure Parsing Techniques for Both Chinese and English Languages

  • Yang, Erfu (Co-investigator)
  • Hussain, Amir (Co-investigator)
  • Abel, Andrew (Principal Investigator)
  • Zhou, Qiang (Principal Investigator)

Project: Projects from Previous Employment

Description

The objectives of this joint project are two-fold:
(i) To collaboratively develop and apply novel machine learning and natural language processing (NLP) based technologies in order to blend MIT’s OpenMind database (which will be extended with Common Sense knowledge expressed in Chinese) with any given ontology, and hence build a novel intelligent software engine that can auto-categorise and analyse documents for intelligent web applications. The software engine will also employ novel language modelling, sentimental classification and adaptation techniques for Bi-lingual (English and Chinese) document analysis.
(ii) To collaboratively exploit the intelligent software engine (from (i)) to develop the next generation of semantic web applications whose design and content can dynamically adapt to the user, including through the use of novel multi-modal emotion-sensitive conversational agents.
Funded by the Royal Society of Edinburgh (RSE) and The National Natural Science Foundation of China (NNSCF), £24,000

Notes

Funded by the Royal Society of Edinburgh (RSE) and The National Natural Science Foundation of China (NNSCF), £24,000
StatusFinished
Effective start/end date1/04/1431/03/16