Intent engine plays an important role in delivering great end user experience. In this project, we study various research problems, including intent representation, intent organization, algorithms to map user inputs to intent, intent prediction and how to connect users with different services. Particularly, we study how to scale up the intent engine, i.e., to enable intelligent task completion experiences for various task domains (shopping, travel, local, etc.). Furthermore, based on the research work, we are proposing new product features and even new products and evaluate user experiences on different types of computing devices.
Opinion data is widely spread on the Web, in various forms like product reviews, blogs and microblogs, etc. Since in many cases, user opinion is expressed in text format, it is not easy to digest/aggregate them efficiently. This project targets to organize opinion data and facilitate the usage of them. The following research problems are studied in this project:
- Sentiment classification
- Opinion topic mining
- Opinion summarization
- Cross-domain sentiment classification
- Opinion word extraction
- Comparative sentiment classification
Research algorithms of this project are also used by Microsoft Bing products.