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KMi Seminars
Topic Models for Data Mining
This event took place on Friday 13 July 2012 at 12:00

 
Dr. Tomoharu Iwata NTT/University of Cambridge


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.



 
KMi Seminars
 

Narrative Hypermedia is...


Narrative Hypermedia
Narrative is concerned fundamentally with coherence, for instance, whether that be a fiction, an historical account or an argument, none of which 'make sense' unless they are put together in a coherent manner.

Hypermedia is the combination of hypertext for linking and structuring multimedia information.

Narrative Hypermedia is therefore concerned with how all of the above narrative forms, plus the many other diverse forms of discourse possible on the Web, can be effectively designed to communicate coherent conceptual structures, drawing inspiration from theories in narratology, semiotics, psycholinguistics and film.