Information retrieval which aims to provide people with easy access to all kinds of information is now becoming more and more emphasized. However, most approaches to information r...
Low-dimensional topic models have been proven very useful for modeling a large corpus of documents that share a relatively small number of topics. Dimensionality reduction tools s...
In this paper, we present the results of a project that seeks to transform low-level features to a higher level of meaning. This project concerns a technique, latent semantic inde...
We describe a class of causal, discrete latent variable models called Multiple Multiplicative Factor models (MMFs). A data vector is represented in the latent space as a vector of...
Term-based representations of documents have found widespread use in information retrieval. However, one of the main shortcomings of such methods is that they largely disregard le...