From Sentiment Analysis to Topic Discovery
Event details
| Date | 02.06.2014 |
| Hour | 10:00 |
| Speaker | Bing LIU, University of Illinois at Chicago |
| Location | |
| Category | Conferences - Seminars |
Sentiment analysis (SA) or opinion mining is the computational study of people's opinions, sentiments, attitudes, and emotions expressed in written language. It is one of the most active research areas in natural language processing (NLP) and data mining. The popularity of SA is mainly due to two factors: seemingly unlimited applications and many challenging research problems. SA can be regarded as a semantic analysis problem, but it is also highly targeted and bounded because a SA system does not need to fully "understand" each sentence or document, but only needs to comprehend some aspects of it, e.g., positive/negative opinions and their targets. SA, however, does not seem to be just a sub-problem of NLP. It is more like a mini version of full NLP because SA touches upon every core issue of NLP.
However, due to the targeted and bounded nature of SA, it allows us to perform deeper language analyses to gain much better insights into NLP than in the general setting because the complexity of the general setting of NLP is simply too overwhelming. In this talk, I will first define SA and discuss the current state of the art, and then go into details to discuss one recent study that aims to solve a SA problem but also contributes to machine learning in the areas of topic modeling, lifelong learning, and big data.
However, due to the targeted and bounded nature of SA, it allows us to perform deeper language analyses to gain much better insights into NLP than in the general setting because the complexity of the general setting of NLP is simply too overwhelming. In this talk, I will first define SA and discuss the current state of the art, and then go into details to discuss one recent study that aims to solve a SA problem but also contributes to machine learning in the areas of topic modeling, lifelong learning, and big data.
Links
Practical information
- General public
- Free
Organizer
- Boi Faltings
Contact
- Sylvie Thomet