Topic Models for Data Mining
This event took place on Friday 13 July 2012 at 12:00
Dr. Tomoharu Iwata NTT/University of Cambridge
This event took place on Friday 13 July 2012 at 12:00
A topic model is a probabilistic generative model for extracting a latent structure from discrete data such as text document. Topic models are successfully used in a wide variety of applications including information retrieval, collaborative filtering and image recognition. In this talk, first I will present basics of topic modelling, such as relations with other probabilistic models, and inference. Then, I will present three applications of topic modelling: social annotation data analysis, multi-scale dynamics analysis, and fashion coordinates recommendation, which I worked on recent years.
Future Internet
KnowledgeManagementMultimedia &
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
Future Internet from KMi.
Check out these Hot Future Internet Projects:
List all Future Internet Projects
Check out these Hot Future Internet Technologies:
List all Future Internet Technologies
List all Future Internet Projects
Check out these Hot Future Internet Technologies:
List all Future Internet Technologies



